On oriented arc-coloring of subcubic graphs
计算机术语介绍
DP(Dual Processor,双处理器) DSM(Dedicated Stack Manager,专门堆栈管理) DSMT(Dynamic Simultaneous Multithreading,动态同步多线程) DST(Depleted Substrate Transistor,衰竭型底层晶体管) DTV(Dual Threshold Voltage,双重极限电压) DUV(Deep Ultra-Violet,纵深紫外光) EBGA(Enhanced Ball Grid Array,增强形球状网阵排列) EBL(electron beam lithography,电子束平版印刷) EC(Embedded Controller,嵌入式控制器) EDEC(Early Decode,早期解码) Embedded Chips(嵌入式) EPA(edge pin array,边缘针脚阵列) EPF(Embedded Processor Forum,嵌入式处理器论坛) EPL(electron projection lithography,电子发射平版印刷)
IOPs(Integer Operations Per Second,整数操作/秒) IPC(Instructions Per Clock Cycle,指令/时钟周期) ISA(instruction set architecture,指令集架构) ISD(inbuilt speed-throttling device,内藏速度控制设备) ITC(Instruction Trace Cache,指令追踪缓存) ITRS(International Technology Roadmap for Semiconductors,国 际半导体技术发展蓝图) KNI(Katmai New Instructions,Katmai 新指令集,即 SSE) Latency(潜伏期) LDT(Lightning Data Transport,闪电数据传输总线) LFU(Legacy Function Unit,传统功能单元) LGA(land grid array,接点栅格阵列) LN2(Liquid Nitrogen,液氮) Local Interconnect(局域互连)
专业术语中英文对照表计算机专业
1、CPU3DNow!(3D no waiting,无须等待的3D处理)AAM(AMD Analyst Meeting,AMD分析家会议)ABP(Advanced Branch Prediction,高级分支预测)ACG(Aggressive Clock Gating,主动时钟选择)AIS(Alternate Instruction Set,交替指令集)ALAT(advanced load table,高级载入表)ALU(Arithmetic Logic Unit,算术逻辑单元)Aluminum(铝)AGU(Address Generation Units,地址产成单元)APC(Advanced Power Control,高级能源控制)APIC(Advanced rogrammable Interrupt Controller,高级可编程中断控制器)APS(Alternate Phase Shifting,交替相位跳转)ASB(Advanced System Buffering,高级系统缓冲)ATC(Advanced Transfer Cache,高级转移缓存)ATD(Assembly Technology Development,装配技术发展)BBUL(Bumpless Build-Up Layer,内建非凹凸层)BGA(Ball Grid Array,球状网阵排列)BHT(branch prediction table,分支预测表)Bops(Billion Operations Per Second,10亿操作/秒)BPU(Branch Processing Unit,分支处理单元)BP(Brach Pediction,分支预测)BSP(Boot Strap Processor,启动捆绑处理器)BTAC(Branch Target Address Calculator,分支目标寻址计算器)CBGA (Ceramic Ball Grid Array,陶瓷球状网阵排列)CDIP (Ceramic Dual-In-Line,陶瓷双重直线)Center Processing Unit Utilization,中央处理器占用率CFM(cubic feet per minute,立方英尺/秒)CMT(course-grained multithreading,过程消除多线程)CMOS(Complementary Metal Oxide Semiconductor,互补金属氧化物半导体)CMOV(conditional move instruction,条件移动指令)CISC(Complex Instruction Set Computing,复杂指令集计算机)CLK(Clock Cycle,时钟周期)CMP(on-chip multiprocessor,片内多重处理)CMS(Code Morphing Software,代码变形软件)co-CPU(cooperative CPU,协处理器)COB(Cache on board,板上集成缓存,做在CPU卡上的二级缓存,通常是内核的一半速度))COD(Cache on Die,芯片内核集成缓存)Copper(铜)CPGA(Ceramic Pin Grid Array,陶瓷针型栅格阵列)CPI(cycles per instruction,周期/指令)CPLD(Complex Programmable Logic Device,複雜可程式化邏輯元件)CPU(Center Processing Unit,中央处理器)CRT(Cooperative Redundant Threads,协同多余线程)CSP(Chip Scale Package,芯片比例封装)CXT(Chooper eXTend,增强形K6-2内核,即K6-3)Data Forwarding(数据前送)dB(decibel,分贝)DCLK(Dot Clock,点时钟)DCT(DRAM Controller,DRAM控制器)DDT(Dynamic Deferred Transaction,动态延期处理)Decode(指令解码)DIB(Dual Independent Bus,双重独立总线)DMT(Dynamic Multithreading Architecture,动态多线程结构)DP(Dual Processor,双处理器)DSM(Dedicated Stack Manager,专门堆栈管理)DSMT(Dynamic Simultaneous Multithreading,动态同步多线程)DST(Depleted Substrate Transistor,衰竭型底层晶体管)DTV(Dual Threshold Voltage,双重极限电压)DUV(Deep Ultra-Violet,纵深紫外光)EBGA(Enhanced Ball Grid Array,增强形球状网阵排列)EBL(electron beam lithography,电子束平版印刷)EC(Embedded Controller,嵌入式控制器)EDEC(Early Decode,早期解码)Embedded Chips(嵌入式)EPA(edge pin array,边缘针脚阵列)EPF(Embedded Processor Forum,嵌入式处理器论坛)EPL(electron projection lithography,电子发射平版印刷)EPM(Enhanced Power Management,增强形能源管理)EPIC(explicitly parallel instruction code,并行指令代码)EUV(Extreme Ultra Violet,紫外光)EUV(extreme ultraviolet lithography,极端紫外平版印刷)FADD(Floationg Point Addition,浮点加)FBGA(Fine-Pitch Ball Grid Array,精细倾斜球状网阵排列)FBGA(flipchip BGA,轻型芯片BGA)FC-BGA(Flip-Chip Ball Grid Array,反转芯片球形栅格阵列)FC-LGA(Flip-Chip Land Grid Array,反转接点栅格阵列)FC-PGA(Flip-Chip Pin Grid Array,反转芯片针脚栅格阵列)FDIV(Floationg Point Divide,浮点除)FEMMS:Fast Entry/Exit Multimedia State,快速进入/退出多媒体状态FFT(fast Fourier transform,快速热欧姆转换)FGM(Fine-Grained Multithreading,高级多线程)FID(FID:Frequency identify,频率鉴别号码)FIFO(First Input First Output,先入先出队列)FISC(Fast Instruction Set Computer,快速指令集计算机)flip-chip(芯片反转)FLOPs(Floating Point Operations Per Second,浮点操作/秒)FMT(fine-grained multithreading,纯消除多线程)FMUL(Floationg Point Multiplication,浮点乘)FPRs(floating-point registers,浮点寄存器)FPU(Float Point Unit,浮点运算单元)FSUB(Floationg Point Subtraction,浮点减)GFD(Gold finger Device,金手指超频设备)GHC(Global History Counter,通用历史计数器)GTL(Gunning Transceiver Logic,射电收发逻辑电路)GVPP(Generic Visual Perception Processor,常规视觉处理器)HL-PBGA: 表面黏著,高耐热、轻薄型塑胶球状网阵封装HTT(Hyper-Threading Technology,超级线程技术)Hz(hertz,赫兹,频率单位)IA(Intel Architecture,英特尔架构)IAA(Intel Application Accelerator,英特尔应用程序加速器)ICU(Instruction Control Unit,指令控制单元)ID(identify,鉴别号码)IDF(Intel Developer Forum,英特尔开发者论坛)IEU(Integer Execution Units,整数执行单元)IHS(Integrated Heat Spreader,完整热量扩展)ILP(Instruction Level Parallelism,指令级平行运算)IMM: Intel Mobile Module, 英特尔移动模块Instructions Cache,指令缓存Instruction Coloring(指令分类)IOPs(Integer Operations Per Second,整数操作/秒)IPC(Instructions Per Clock Cycle,指令/时钟周期)ISA(instruction set architecture,指令集架构)ISD(inbuilt speed-throttling device,内藏速度控制设备)ITC(Instruction Trace Cache,指令追踪缓存)ITRS(International Technology Roadmap for Semiconductors,国际半导体技术发展蓝图)KNI(Katmai New Instructions,Katmai新指令集,即SSE)Latency(潜伏期)LDT(Lightning Data Transport,闪电数据传输总线)LFU(Legacy Function Unit,传统功能单元)LGA(land grid array,接点栅格阵列)LN2(Liquid Nitrogen,液氮)Local Interconnect(局域互连)MAC(multiply-accumulate,累积乘法)mBGA (Micro Ball Grid Array,微型球状网阵排列)nm(namometer,十亿分之一米/毫微米)MCA(machine check architecture,机器检查体系)MCU(Micro-Controller Unit,微控制器单元)MCT(Memory Controller,内存控制器)MESI(Modified, Exclusive, Shared, Invalid:修改、排除、共享、废弃)MF(MicroOps Fusion,微指令合并)mm(micron metric,微米)MMX(MultiMedia Extensions,多媒体扩展指令集)MMU(Multimedia Unit,多媒体单元)MMU(Memory Management Unit,内存管理单元)MN(model numbers,型号数字)MFLOPS(Million Floationg Point/Second,每秒百万个浮点操作)MHz(megahertz,兆赫)mil(PCB 或晶片佈局的長度單位,1 mil = 千分之一英寸)MIPS(Million Instruction Per Second,百万条指令/秒)MOESI(Modified, Owned, Exclusive, Shared or Invalid,修改、自有、排除、共享或无效)MOF(Micro Ops Fusion,微操作熔合)Mops(Million Operations Per Second,百万次操作/秒)MP(Multi-Processing,多重处理器架构)MPF(Micro processor Forum,微处理器论坛)MPU(Microprocessor Unit,微处理器)MPS(MultiProcessor Specification,多重处理器规范)MSRs(Model-Specific Registers,特别模块寄存器)MSV(Multiprocessor Specification Version,多处理器规范版本)NAOC(no-account OverClock,无效超频)NI(Non-Intel,非英特尔)NOP(no operation,非操作指令)NRE(Non-Recurring Engineering charge,非重複性工程費用)OBGA(Organic Ball Grid Arral,有机球状网阵排列)OCPL(Off Center Parting Line,远离中心部分线队列)OLGA(Organic Land Grid Array,有机平面网阵包装)OoO(Out of Order,乱序执行)OPC(Optical Proximity Correction,光学临近修正)OPGA(Organic Pin Grid Array,有机塑料针型栅格阵列)OPN(Ordering Part Number,分类零件号码)PAT(Performance Acceleration Technology,性能加速技术)PBGA(Plastic Pin Ball Grid Array,塑胶球状网阵排列)PDIP (Plastic Dual-In-Line,塑料双重直线)PDP(Parallel Data Processing,并行数据处理)PGA(Pin-Grid Array,引脚网格阵列),耗电大PLCC (Plastic Leaded Chip Carriers,塑料行间芯片运载)Post-RISC(加速RISC,或后RISC)PR(Performance Rate,性能比率)PIB(Processor In a Box,盒装处理器)PM(Pseudo-Multithreading,假多线程)PPGA(Plastic Pin Grid Array,塑胶针状网阵封装)PQFP(Plastic Quad Flat Package,塑料方块平面封装)PSN(Processor Serial numbers,处理器序列号)QFP(Quad Flat Package,方块平面封装)QSPS(Quick Start Power State,快速启动能源状态)RAS(Return Address Stack,返回地址堆栈)RAW(Read after Write,写后读)REE(Rapid Execution Engine,快速执行引擎)Register Contention(抢占寄存器)Register Pressure(寄存器不足)Register Renaming(寄存器重命名)Remark(芯片频率重标识)Resource contention(资源冲突)Retirement(指令引退)RISC(Reduced Instruction Set Computing,精简指令集计算机)ROB(Re-Order Buffer,重排序缓冲区)RSE(register stack engine,寄存器堆栈引擎)RTL(Register Transfer Level,暫存器轉換層。
中国地质大学(北京)考博专业英复习材料
晶) is said to have a porphyritic texture(斑状结构). The classification of fine-grained rocks, then, is based on the proportion of minerals which form phenocrysts and these phenocrysts (斑晶)reflect the general composition of the remainder(残留) of the rock. The fine-grained portion of a porphyritic(斑岩) rock is generally referred to as the groundmass(基质) of the phenocrysts. The terms "porphyritic" and "phenocrysts" are not restricted to fine-grained rocks but may also apply to coarse-grained rocks which contain a few crystals distinctly larger than the remainder. The term obsidian(黑曜岩) refers to a glassy rock of rhyolitic(流纹岩) composition. In general, fine-grained rocks consisting of small crystals cannot readily be distinguished from③ glassy rocks in which no crystalline material is present at all. The obsidians, however, are generally easily recognized by their black and highly glossy appearanceass of the same composition as obsidian. Apparently the difference between the modes of formation of obsidian and pumice is that in pumice the entrapped water vapors have been able to escape by a frothing(起泡) process which leaves a network of interconnected pore(气孔) spaces, thus giving the rock a highly porous (多孔的)and open appearance(外观较为松散). ④ Pegmatite(结晶花岗岩) is a rock which is texturally(构造上地) the exact opposite of obsidian. ⑤ Pegmatites are generally formed as dikes associated with major bodies of granite (花岗岩) . They are characterized by extremely large individual crystals (单个晶体) ; in some pegmatites crystals up to several tens of feet in length(宽达几十英尺)have been identified, but the average size is measured in inches (英寸) . Most mineralogical museums contain a large number of spectacular(壮观的) crystals from pegmatites. Peridotite(橄榄岩) is a rock consisting primarily of olivine, though some varieties contain pyroxene(辉石) in addition. It occurs only as coarse-grained intrusives(侵入), and no extrusive(喷出的) rocks of equivalent chemical composition have ever been found. Tuff (凝灰岩)is a rock which is igneous in one sense (在某种意义上) and sedimentary in another⑥. A tuff is a rock formed from pyroclastic (火成碎 屑的)material which has been blown out of a volcano and accumulated on the ground as individual fragments called ash. Two terms(igneous and sedimentary) are useful to refer solely to the composition of igneous rocks regardless of their textures. The term silicic (硅质 的)signifies an abundance of silica-rich(富硅) and light-colored minerals(浅 色矿物), such as quartz, potassium feldspar(钾长石), and sodic plagioclase (钠长石) . The term basic (基性) signifies (意味着) an abundance of dark colored minerals relatively low in silica and high in calcium, iron, and
Fronts propagating with curvature dependent speed Algorithms Based on Hamilton-Jacobi Formulations
reaching out into the unburnt gas somehow propagate slower than do concave regions which are hot gases surrounding a small unburnt pocket. At the same time, particles along the flame front undergo an increase in volume as they burn, creating a jump in velocity across the flame front. This discontinuity in the velocity field creates vorticity along the burning flame, which can be related to the local curvature, and this new vorticity field contributes to the advection of the propagating flame. Thus, there are at least two distinct ways in which the speed of the moving flame depends on the local curvature. Typically, there have been two types of numerical algorithms employed in the solution of such problems. The first parameterizes the moving front by some variable and discretizes this parameterization into a set of marker points [39]. The positions of the marker points are updated in time according to approximations to the equations of motion. Such techniques can be extremely accurate in the attempt to follow the motions of small perturbations. However, for large, complex motion, several problems soon occur. First, marker particles come together in regions where the curvature of the propagating front builds, causing numerical instability unless a regridding technique is employed. The regridding mechanism usually contains a error term which resembles diffusion and dominates the real effects of curvature under analysis. Secondly, such methods suffer from topological problems; when two regions "burn" together to form a single one, ad-hoc techniques to eliminate parts of the boundary are required to make the algorithm work. Other algorithms commonly employed fall under the category of "volume of fluid " techniques, which, rather than track the boundary of the propagating front, track the motion of the interior region. An example of this type of algorithm is SLIC [26]. In these algorithms, the interior is discretized, usually by employing a grid on the domain and assigning to each cell a "volume fraction" corresponding to the amount of interior fluid currently located in that cell. An advantage of such techniques is that no new computational elements are required as the calculation progresses (unlike the parameterization methods), and complicated topological boundaries are easily handled, see [4,32]. Unfortunately, it is difficult to calculate the curvature of the front from such a representa-
雅思考试阅读常见题材-11自然 detection of a meteorite lake
Detection of a meteorite LakeA A s the sun rose over picturesque Lake Bosumtwi, a team of SyracuseUniversity researchers prepared for another day of using state-of-the-art equipment to help unlock the mysteries hidden below the lake bottom.Nestled in the heart of Ghana (加纳),the lake holds an untapped reservoir of information that could help scientists predict future climate changes by looking at evidence from the past. This information will also improve the scientists’understanding of the changes that occur in a region struck by a massive meteorite (陨石).B T he project, led by earth sciences professor Christopher Scholz of the Collegeof Arts and Sciences and funded by the National Science Foundation (NSF), is the fi rst large-scale effort to study Lake Bosumtwi, which formed 1.1 million years ago when a giant meteor crashed into the Earth’s surface. The resulting crater is one of the largest and most well-preserved geologically young craters (火山口)in the world, says Scholz, who is collaborating on the project with researchers from the University of Arizona, the University of South Carolina, the University of Rhode Island, and several Ghanaian institutions. “Our data should provide information about what happens when an impact hits hard, pre-Cambrian (前寒武纪),crystalline rocks (结晶岩)that are a billion years old, he says.C E qually important is the fact that the lake, which is about 8 kilometers indiameter, has no natural outlet. The rim of the crater rises about 250 meters above the water’s surface. Streams flow into the lake, Scholz says, but the water leaves only by evaporation, or by seeping through the lake sediments.For the past million years, the lake has acted as a tropical rain gauge (测量器),fi lling and drying with changes in precipitation and the tropical climate.The record of those changes is hidden in sediment below the lake bottom. “The lake is one of the best sites in the world for the study of tropical climate (热带气候)changes,” Scholz says. “The tropics are the heat engine for the Earth’s climate. To understand global climate, we need to have records of climatechanges from many sites around the world, including the tropics.”D B efore the researchers could explore the lake’s subsurface, they needed aboat with a large, working deck area that could carry eight tons of scienti fi c equipment. The boat—dubbed R/V Kilindi—was built in Florida last year. It was constructed in modules that were dismantled, packed inside a shipping container, and reassembled over a 10-day period in late November and early December 1999 in the rural village of Abono, Ghana. The research team then spent the next two weeks testing the boat and equipment before returning to the United States for the holidays.E I n mid-January, fi ve members of the team—Keely Brooks, an earth sciencesgraduate student; Peter Cattaneo, a research analyst; and Kir am Lezzar, a postdoctoral scholar, all from SU; James McGill, a geophysical fi eld engineer;and Nick Peters, a Ph.D. student in geophysics from the University of Miami—returned to Abono to begin collecting data about the lake’s subsurface using a technique called seismic re fl ection pro fi ling. In this process, a high-pressure air gun is used to create small, pneumatic explosions in the water. The sound energy penetrates about 1,000 to 2,000meters into the lake’s subsurface beforebouncing back to the surface of the water.F T he reflected sound energy is detectedby underwater microphones—calledhydrophones—embedded in a 50-meter-long cable that is towed behind the boat asit crosses the lake in a carefully designedgrid pattern. On-board computers recordthe signals, and the resulting data are thenprocessed and analyzed in the laboratory.“The results will give us a good idea ofthe shape of the sediment are, and whenand where there were major changes insediment accumulation,” Scholz says. “Weare now developing three-dimensional perspective of the lake’s subsurface and the layers of sediment that have been laid down.”G T eam members spent about four weeks in Ghana collecting the data. Theyworked seven days a week, arriving at the lake just after sunrise. On a good day, when everything went as planned, the team could collect data and be back at the dock by early afternoon. Except for a few relatively minor adjustments, the equipment and the boat worked well. Problems that arose were primarily non-scientific— tree stumps, fishing nets, cultural barriers, and occasional misunderstandings with local villagers.H L ake Bosumtwi, the largest natural freshwater lake in the country, is sacred tothe Ashanti people, who believe their souls come to the lake to bid farewell to their god. The lake is also the primary source of fi sh for the 26 surrounding villages. Conventional canoes and boats are forbidden. Fishermen travel on the lake by fl oating on traditional planks (木板)they propel with small paddles (船桨).Before the research project could begin, Scholz and his Ghanaian counterparts had to secure special permission from tribal chiefs to put the R/V Kilindi on the lake.I W hen the team began gathering data, rumors (谣言)fl ew around the lake asto why the researchers were there. “Some thought we were dredging the lake for gold, others thought we were going to drain the lake or that we had bought the lake,” Cattaneo says. “But once the local people understood why we were there, they were very helpful.”Questions 14-18 .............................................................................Do the following statements agree with the information given in Reading Passage 1?In boxes 14-18 on your answer sheet, writeTRUE if the sataement agrees with the informationFALSE if the statement contradicts the informationNOT GIVEN if there is no information on this14W ith the analysis of the bottom of the lake, scientist will predict the climate changes in the future.15T he water stored in lake Bosumtwi was gone only by seeping through the lake sediments.16T he crater resulted from a meteorite impact is the largest and most preserved one in the world.17H istorical climate changes can be detected by the analysis of the sediment of the lake.18R esearch of scientist and co-workers had been interfered by the locals due to their indigenous believes.Questions 19-22 .............................................................................There are three steps of collecting data from the lake as followings, please filling the blanks in the Flow Chart below:Step 1a 50-meter 19 ,with many 20embededStep 2a 21 isneeded to create theexplosion into thewaterStep 3the 22enters deep intothe water andreturn backQuestions 23-27 ............................................................................. SummaryComplete the following summary of the paragraphs of Reading Passage, using no more than three words from the Reading Passage for each answer. Write your answers in boxes 23-27 on your answer sheet.The boat-double R/V Kilindi crossed the lake was dismantled and stored in a 23. The technology they used called 24; They created sound energy in to 1000-2000 metres in to the bottom of the lake, and used separate equipment to collect the returned waves. Then the data had been analyzed and processed in the 25. Scholz also added that they were now building 26view of the sediment or sub-image in the bottom of the lake. Whole set of equipment works well yet the ship should avoid tree stumps or 27fl oating on the surface of the Bosumtwi lake.。
arcmap面试题目(3篇)
第1篇一、基础知识1. 什么是GIS?请简述GIS的主要功能。
解析:GIS(地理信息系统)是一种将地理空间数据与属性数据相结合,用于捕捉、存储、分析、管理和展示地理空间信息的系统。
GIS的主要功能包括数据采集、数据存储、数据处理、数据分析和数据可视化。
2. 请解释以下概念:矢量数据、栅格数据、拓扑关系。
解析:- 矢量数据:以点、线、面等几何对象表示地理空间实体,适用于表示清晰的边界和形状,如道路、河流、行政区划等。
- 栅格数据:以网格的形式表示地理空间信息,每个网格单元包含一个或多个属性值,适用于表示连续的地理现象,如遥感影像、地形高程等。
- 拓扑关系:描述地理空间实体之间的相互关系,如相邻、包含、连接等,用于提高空间数据的查询和分析效率。
3. 请简述ArcGIS软件的主要组件。
解析:ArcGIS软件主要包括以下组件:- ArcGIS Desktop:用于数据采集、编辑、分析、管理和可视化。
- ArcGIS Server:用于发布GIS服务和应用程序。
- ArcGIS Online:提供云基础上的GIS服务、应用程序和地图。
- ArcGIS API for Developers:用于开发GIS应用程序。
二、ArcGIS Desktop操作1. 如何创建一个新的地图文档?解析:在ArcGIS Desktop中,可以通过以下步骤创建一个新的地图文档:- 打开ArcGIS Desktop。
- 选择“文件”菜单中的“新建”选项。
- 选择“地图”类型,然后点击“确定”。
- 在弹出的“新建地图”对话框中,输入地图文档的名称,选择保存位置,然后点击“保存”。
2. 如何添加图层到地图文档中?解析:在ArcGIS Desktop中,可以通过以下步骤添加图层到地图文档中:- 打开地图文档。
- 在“内容”窗口中,右键点击“图层”或“组”,选择“添加数据”。
- 在弹出的“添加数据”对话框中,选择数据源,如文件、数据库或网络,然后选择要添加的图层,点击“添加”。
Universities in Evolutionary Systems(系统变革中的大学)
Universities in Evolutionary Systems of InnovationMarianne van der Steen and Jurgen EndersThis paper criticizes the current narrow view on the role of universities in knowledge-based economies.We propose to extend the current policy framework of universities in national innovation systems(NIS)to a more dynamic one,based on evolutionary economic principles. The main reason is that this dynamic viewfits better with the practice of innovation processes. We contribute on ontological and methodological levels to the literature and policy discussions on the effectiveness of university-industry knowledge transfer and the third mission of uni-versities.We conclude with a discussion of the policy implications for the main stakeholders.1.IntroductionU niversities have always played a major role in the economic and cultural devel-opment of countries.However,their role and expected contribution has changed sub-stantially over the years.Whereas,since1945, universities in Europe were expected to con-tribute to‘basic’research,which could be freely used by society,in recent decades they are expected to contribute more substantially and directly to the competitiveness offirms and societies(Jaffe,2008).Examples are the Bayh–Dole Act(1982)in the United States and in Europe the Lisbon Agenda(2000–2010) which marked an era of a changing and more substantial role for universities.However,it seems that this‘new’role of universities is a sort of universal given one(ex post),instead of an ex ante changing one in a dynamic institutional environment.Many uni-versities are expected nowadays to stimulate a limited number of knowledge transfer activi-ties such as university spin-offs and university patenting and licensing to demonstrate that they are actively engaged in knowledge trans-fer.It is questioned in the literature if this one-size-fits-all approach improves the usefulness and the applicability of university knowledge in industry and society as a whole(e.g.,Litan et al.,2007).Moreover,the various national or regional economic systems have idiosyncratic charac-teristics that in principle pose different(chang-ing)demands towards universities.Instead of assuming that there is only one‘optimal’gov-ernance mode for universities,there may bemultiple ways of organizing the role of univer-sities in innovation processes.In addition,we assume that this can change over time.Recently,more attention in the literature hasfocused on diversity across technologies(e.g.,King,2004;Malerba,2005;Dosi et al.,2006;V an der Steen et al.,2008)and diversity offormal and informal knowledge interactionsbetween universities and industry(e.g.,Cohenet al.,1998).So far,there has been less atten-tion paid to the dynamics of the changing roleof universities in economic systems:how dothe roles of universities vary over time andwhy?Therefore,this article focuses on the onto-logical premises of the functioning of univer-sities in innovation systems from a dynamic,evolutionary perspective.In order to do so,we analyse the role of universities from theperspective of an evolutionary system ofinnovation to understand the embeddednessof universities in a dynamic(national)systemof science and innovation.The article is structured as follows.InSection2we describe the changing role ofuniversities from the static perspective of anational innovation system(NIS),whereasSection3analyses the dynamic perspective ofuniversities based on evolutionary principles.Based on this evolutionary perspective,Section4introduces the characteristics of a LearningUniversity in a dynamic innovation system,summarizing an alternative perception to thestatic view of universities in dynamic economicsystems in Section5.Finally,the concludingVolume17Number42008doi:10.1111/j.1467-8691.2008.00496.x©2008The AuthorsJournal compilation©2008Blackwell Publishingsection discusses policy recommendations for more effective policy instruments from our dynamic perspective.2.Static View of Universities in NIS 2.1The Emergence of the Role of Universities in NISFirst we start with a discussion of the literature and policy reports on national innovation system(NIS).The literature on national inno-vation systems(NIS)is a relatively new and rapidly growingfield of research and widely used by policy-makers worldwide(Fagerberg, 2003;Balzat&Hanusch,2004;Sharif,2006). The NIS approach was initiated in the late 1980s by Freeman(1987),Dosi et al.(1988)and Lundvall(1992)and followed by Nelson (1993),Edquist(1997),and many others.Balzat and Hanusch(2004,p.196)describe a NIS as‘a historically grown subsystem of the national economy in which various organizations and institutions interact with and influence one another in the carrying out of innovative activity’.It is about a systemic approach to innovation,in which the interaction between technology,institutions and organizations is central.With the introduction of the notion of a national innovation system,universities were formally on the agenda of many innovation policymakers worldwide.Clearly,the NIS demonstrated that universities and their interactions with industry matter for innova-tion processes in economic systems.Indeed, since a decade most governments acknowl-edge that interactions between university and industry add to better utilization of scienti-fic knowledge and herewith increase the innovation performance of nations.One of the central notions of the innovation system approach is that universities play an impor-tant role in the development of commercial useful knowledge(Edquist,1997;Sharif, 2006).This contrasts with the linear model innovation that dominated the thinking of science and industry policy makers during the last century.The linear innovation model perceives innovation as an industry activity that‘only’utilizes fundamental scientific knowledge of universities as an input factor for their innovative activities.The emergence of the non-linear approach led to a renewed vision on the role–and expectations–of universities in society. Some authors have referred to a new social contract between science and society(e.g., Neave,2000).The Triple Helix(e.g.,Etzkowitz &Leydesdorff,1997)and the innovation system approach(e.g.,Lundvall,1988)and more recently,the model of Open Innovation (Chesbrough,2003)demonstrated that innova-tion in a knowledge-based economy is an inter-active process involving many different innovation actors that interact in a system of overlapping organizationalfields(science, technology,government)with many interfaces.2.2Static Policy View of Universities in NIS Since the late1990s,the new role of universi-ties in NIS thinking emerged in a growing number of policy studies(e.g.,OECD,1999, 2002;European Commission,2000).The con-tributions of the NIS literature had a large impact on policy makers’perception of the role of universities in the national innovation performance(e.g.,European Commission, 2006).The NIS approach gradually replaced linear thinking about innovation by a more holistic system perspective on innovations, focusing on the interdependencies among the various agents,organizations and institutions. NIS thinking led to a structurally different view of how governments can stimulate the innovation performance of a country.The OECD report of the national innovation system (OECD,1999)clearly incorporated these new economic principles of innovation system theory.This report emphasized this new role and interfaces of universities in knowledge-based economies.This created a new policy rationale and new awareness for technology transfer policy in many countries.The NIS report(1999)was followed by more attention for the diversity of technology transfer mecha-nisms employed in university-industry rela-tions(OECD,2002)and the(need for new) emerging governance structures for the‘third mission’of universities in society,i.e.,patent-ing,licensing and spin-offs,of public research organizations(OECD,2003).The various policy studies have in common that they try to describe and compare the most important institutions,organizations, activities and interactions of public and private actors that take part in or influence the innovation performance of a country.Figure1 provides an illustration.Thefigure demon-strates the major building blocks of a NIS in a practical policy setting.It includesfirms,uni-versities and other public research organiza-tions(PROs)involved in(higher)education and training,science and technology.These organizations embody the science and tech-nology capabilities and knowledge fund of a country.The interaction is represented by the arrows which refer to interactive learn-ing and diffusion of knowledge(Lundvall,Volume17Number42008©2008The AuthorsJournal compilation©2008Blackwell Publishing1992).1The building block ‘Demand’refers to the level and quality of demand that can be a pull factor for firms to innovate.Finally,insti-tutions are represented in the building blocks ‘Framework conditions’and ‘Infrastructure’,including various laws,policies and regula-tions related to science,technology and entre-preneurship.It includes a very broad array of policy issues from intellectual property rights laws to fiscal instruments that stimulate labour mobility between universities and firms.The figure demonstrates that,in order to improve the innovation performance of a country,the NIS as a whole should be conducive for innovative activities in acountry.Since the late 1990s,the conceptual framework as represented in Figure 1serves as a dominant design for many comparative studies of national innovation systems (Polt et al.,2001;OECD,2002).The typical policy benchmark exercise is to compare a number of innovation indicators related to the role of university-industry interactions.Effective performance of universities in the NIS is judged on a number of standardized indica-tors such as the number of spin-offs,patents and licensing.Policy has especially focused on ‘getting the incentives right’to create a generic,good innovative enhancing context for firms.Moreover,policy has also influ-enced the use of specific ‘formal’transfer mechanisms,such as university patents and university spin-offs,to facilitate this collabo-ration.In this way best practice policies are identified and policy recommendations are derived:the so-called one-size-fits-all-approach.The focus is on determining the ingredients of an efficient benchmark NIS,downplaying institutional diversity and1These organizations that interact with each other sometimes co-operate and sometimes compete with each other.For instance,firms sometimes co-operate in certain pre-competitive research projects but can be competitors as well.This is often the case as well withuniversities.Figure 1.The Benchmark NIS Model Source :Bemer et al.(2001).Volume 17Number 42008©2008The AuthorsJournal compilation ©2008Blackwell Publishingvariety in the roles of universities in enhanc-ing innovation performance.The theoretical contributions to the NIS lit-erature have outlined the importance of insti-tutions and institutional change.However,a further theoretical development of the ele-ments of NIS is necessary in order to be useful for policy makers;they need better systemic NIS benchmarks,taking systematically into account the variety of‘national idiosyncrasies’. Edquist(1997)argues that most NIS contribu-tions are more focused onfirms and technol-ogy,sometimes reducing the analysis of the (national)institutions to a left-over category (Geels,2005).Following Hodgson(2000), Nelson(2002),Malerba(2005)and Groenewe-gen and V an der Steen(2006),more attention should be paid to the institutional idiosyncra-sies of the various systems and their evolution over time.This creates variety and evolving demands towards universities over time where the functioning of universities and their interactions with the other part of the NIS do evolve as well.We suggest to conceptualize the dynamics of innovation systems from an evolutionary perspective in order to develop a more subtle and dynamic vision on the role of universities in innovation systems.We emphasize our focus on‘evolutionary systems’instead of national innovation systems because for many universities,in particular some science-based disciplinaryfields such as biotechnology and nanotechnology,the national institutional environment is less relevant than the institu-tional and technical characteristics of the technological regimes,which is in fact a‘sub-system’of the national innovation system.3.Evolutionary Systems of Innovation as an Alternative Concept3.1Evolutionary Theory on Economic Change and InnovationCharles Darwin’s The Origin of Species(1859)is the foundation of modern thinking about change and evolution(Luria et al.,1981,pp. 584–7;Gould,1987).Darwin’s theory of natural selection has had the most important consequences for our perception of change. His view of evolution refers to a continuous and gradual adaptation of species to changes in the environment.The idea of‘survival of thefittest’means that the most adaptive organisms in a population will survive.This occurs through a process of‘natural selection’in which the most adaptive‘species’(organ-isms)will survive.This is a gradual process taking place in a relatively stable environment, working slowly over long periods of time necessary for the distinctive characteristics of species to show their superiority in the‘sur-vival contest’.Based on Darwin,evolutionary biology identifies three levels of aggregation.These three levels are the unit of variation,unit of selection and unit of evolution.The unit of varia-tion concerns the entity which contains the genetic information and which mutates fol-lowing specific rules,namely the genes.Genes contain the hereditary information which is preserved in the DNA.This does not alter sig-nificantly throughout the reproductive life-time of an organism.Genes are passed on from an organism to its successors.The gene pool,i.e.,the total stock of genetic structures of a species,only changes in the reproduction process as individuals die and are born.Par-ticular genes contribute to distinctive charac-teristics and behaviour of species which are more or less conducive to survival.The gene pool constitutes the mechanism to transmit the characteristics of surviving organisms from one generation to the next.The unit of selection is the expression of those genes in the entities which live and die as individual specimens,namely(individual) organisms.These organisms,in their turn,are subjected to a process of natural selection in the environment.‘Fit’organisms endowed with a relatively‘successful’gene pool,are more likely to pass them on to their progeny.As genes contain information to form and program the organisms,it can be expected that in a stable environment genes aiding survival will tend to become more prominent in succeeding genera-tions.‘Natural selection’,thus,is a gradual process selecting the‘fittest’organisms. Finally,there is the unit of evolution,or that which changes over time as the gene pool changes,namely populations.Natural selec-tion produces changes at the level of the population by‘trimming’the set of genetic structures in a population.We would like to point out two central principles of Darwinian evolution.First,its profound indeterminacy since the process of development,for instance the development of DNA,is dominated by time at which highly improbable events happen (Boulding,1991,p.12).Secondly,the process of natural selection eliminates poorly adapted variants in a compulsory manner,since indi-viduals who are‘unfit’are supposed to have no way of escaping the consequences of selection.22We acknowledge that within evolutionary think-ing,the theory of Jean Baptiste Lamarck,which acknowledges in essence that acquired characteris-tics can be transmitted(instead of hereditaryVolume17Number42008©2008The AuthorsJournal compilation©2008Blackwell PublishingThese three levels of aggregation express the differences between ‘what is changing’(genes),‘what is being selected’(organisms),and ‘what changes over time’(populations)in an evolutionary process (Luria et al.,1981,p.625).According to Nelson (see for instance Nelson,1995):‘Technical change is clearly an evolutionary process;the innovation generator keeps on producing entities superior to those earlier in existence,and adjustment forces work slowly’.Technological change and innovation processes are thus ‘evolutionary’because of its characteristics of non-optimality and of an open-ended and path-dependent process.Nelson and Winter (1982)introduced the idea of technical change as an evolutionary process in capitalist economies.Routines in firms function as the relatively durable ‘genes’.Economic competition leads to the selection of certain ‘successful’routines and these can be transferred to other firms by imitation,through buy-outs,training,labour mobility,and so on.Innovation processes involving interactions between universities and industry are central in the NIS approach.Therefore,it seems logical that evolutionary theory would be useful to grasp the role of universities in innovation pro-cesses within the NIS framework.3.2Evolutionary Underpinnings of Innovation SystemsBased on the central evolutionary notions as discussed above,we discuss in this section how the existing NIS approaches have already incor-porated notions in their NIS frameworks.Moreover,we investigate to what extent these notions can be better incorporated in an evolu-tionary innovation system to improve our understanding of universities in dynamic inno-vation processes.We focus on non-optimality,novelty,the anti-reductionist methodology,gradualism and the evolutionary metaphor.Non-optimality (and Bounded Rationality)Based on institutional diversity,the notion of optimality is absent in most NIS approaches.We cannot define an optimal system of innovation because evolutionary learning pro-cesses are important in such systems and thus are subject to continuous change.The system never achieves an equilibrium since the evolu-tionary processes are open-ended and path dependent.In Nelson’s work (e.g.,1993,1995)he has emphasized the presence of contingent out-comes of innovation processes and thus of NIS:‘At any time,there are feasible entities not present in the prevailing system that have a chance of being introduced’.This continuing existence of feasible alternative developments means that the system never reaches a state of equilibrium or finality.The process always remains dynamic and never reaches an optimum.Nelson argues further that diversity exists because technical change is an open-ended multi-path process where no best solu-tion to a technical problem can be identified ex post .As a consequence technical change can be seen as a very wasteful process in capitalist economies with many duplications and dead-ends.Institutional variety is closely linked to non-optimality.In other words,we cannot define the optimal innovation system because the evolutionary learning processes that take place in a particular system make it subject to continuous change.Therefore,comparisons between an existing system and an ideal system are not possible.Hence,in the absence of any notion of optimality,a method of comparing existing systems is necessary.According to Edquist (1997),comparisons between systems were more explicit and systematic than they had been using the NIS approaches.Novelty:Innovations CentralNovelty is already a central notion in the current NIS approaches.Learning is inter-preted in a broad way.Technological innova-tions are defined as combining existing knowledge in new ways or producing new knowledge (generation),and transforming this into economically significant products and processes (absorption).Learning is the most important process behind technological inno-vations.Learning can be formal in the form of education and searching through research and development.However,in many cases,innovations are the consequence of several kinds of learning processes involving many different kinds of economic agents.According to Lundvall (1992,p.9):‘those activities involve learning-by-doing,increasing the efficiency of production operations,learning-characteristics as in the theory of Darwin),is acknowledged to fit better with socio-economic processes of technical change and innovation (e.g.,Nelson &Winter,1982;Hodgson,2000).Therefore,our theory is based on Lamarckian evolutionary theory.However,for the purpose of this article,we will not discuss the differences between these theo-ries at greater length and limit our analysis to the fundamental evolutionary building blocks that are present in both theories.Volume 17Number 42008©2008The AuthorsJournal compilation ©2008Blackwell Publishingby-using,increasing the efficiency of the use of complex systems,and learning-by-interacting, involving users and producers in an interac-tion resulting in product innovations’.In this sense,learning is part of daily routines and activities in an economy.In his Learning Economy concept,Lundvall makes learning more explicit,emphasizing further that ‘knowledge is assumed as the most funda-mental resource and learning the most impor-tant process’(1992,p.10).Anti-reductionist Approach:Systems and Subsystems of InnovationSo far,NIS approaches are not yet clear and systematic in their analysis of the dynamics and change in innovation systems.Lundvall’s (1992)distinction between subsystem and system level based on the work of Boulding implicitly incorporates both the actor(who can undertake innovative activities)as well as the structure(institutional selection environment) in innovation processes of a nation.Moreover, most NIS approaches acknowledge that within the national system,there are different institu-tional subsystems(e.g.,sectors,regions)that all influence each other again in processes of change.However,an explicit analysis of the structured environment is still missing (Edquist,1997).In accordance with the basic principles of evolutionary theory as discussed in Section 3.1,institutional evolutionary theory has developed a very explicit systemic methodol-ogy to investigate the continuous interaction of actors and institutional structures in the evolution of economic systems.The so-called ‘methodological interactionism’can be per-ceived as a methodology that combines a structural perspective and an actor approach to understand processes of economic evolu-tion.Whereas the structural perspective emphasizes the existence of independent institutional layers and processes which deter-mine individual actions,the actor approach emphasizes the free will of individuals.The latter has been referred to as methodological individualism,as we have seen in neo-classical approaches.Methodological indi-vidualism will explain phenomena in terms of the rational individual(showingfixed prefer-ences and having one rational response to any fully specified decision problem(Hodgson, 2000)).The interactionist approach recognizes a level of analysis above the individual orfirm level.NIS approaches recognize that national differences exist in terms of national institu-tions,socio-economic factors,industries and networks,and so on.So,an explicit methodological interactionist approach,explicitly recognizing various insti-tutional layers in the system and subsystem in interaction with the learning agents,can improve our understanding of the evolution of innovation.Gradualism:Learning Processes andPath-DependencyPath-dependency in biology can be translated in an economic context in the form of(some-times very large)time lags between a technical invention,its transformation into an economic innovation,and the widespread diffusion. Clearly,in many of the empirical case studies of NIS,the historical dimension has been stressed.For instance,in the study of Denmark and Sweden,it has been shown that the natural resource base(for Denmark fertile land,and for Sweden minerals)and economic history,from the period of the Industrial Revolution onwards,has strongly influenced present specialization patterns(Edquist& Lundvall,1993,pp.269–82).Hence,history matters in processes of inno-vation as the innovation processes are influ-enced by many institutions and economic agents.In addition,they are often path-dependent as small events are reinforced and become crucially important through processes of positive feedback,in line with evolutionary processes as discussed in Section3.1.Evolutionary MetaphorFinally,most NIS approaches do not explicitly use the biological metaphor.Nevertheless, many of the approaches are based on innova-tion theories in which they do use an explicit evolutionary metaphor(e.g.,the work of Nelson).To summarize,the current(policy)NIS approaches have already implicitly incorpo-rated some evolutionary notions such as non-optimality,novelty and gradualism.However, what is missing is a more explicit analysis of the different institutional levels of the economic system and innovation subsystems (their inertia and evolution)and how they change over time in interaction with the various learning activities of economic agents. These economic agents reside at established firms,start-upfirms,universities,govern-ments,undertaking learning and innovation activities or strategic actions.The explicit use of the biological metaphor and an explicit use of the methodological interactionst approach may increase our understanding of the evolu-tion of innovation systems.Volume17Number42008©2008The AuthorsJournal compilation©2008Blackwell Publishing4.Towards a Dynamic View of Universities4.1The Logic of an Endogenous‘Learning’UniversityIf we translate the methodological interaction-ist approach to the changing role of universities in an evolutionary innovation system,it follows that universities not only respond to changes of the institutional environment(government policies,business demands or changes in scientific paradigms)but universities also influence the institutions of the selection envi-ronment by their strategic,scientific and entre-preneurial actions.Moreover,these actions influence–and are influenced by–the actions of other economic agents as well.So,instead of a one-way rational response by universities to changes(as in reductionist approach),they are intertwined in those processes of change.So, universities actually function as an endogenous source of change in the evolution of the inno-vation system.This is(on an ontological level) a fundamental different view on the role of universities in innovation systems from the existing policy NIS frameworks.In earlier empirical research,we observed that universities already effectively function endogenously in evolutionary innovation system frameworks;universities as actors (already)develop new knowledge,innovate and have their own internal capacity to change,adapt and influence the institutional development of the economic system(e.g., V an der Steen et al.,2009).Moreover,univer-sities consist of a network of various actors, i.e.,the scientists,administrators at technology transfer offices(TTO)as well as the university boards,interacting in various ways with indus-try and governments and embedded in various ways in the regional,national or inter-national environment.So,universities behave in an at least partly endogenous manner because they depend in complex and often unpredictable ways on the decision making of a substantial number of non-collusive agents.Agents at universities react in continuous interaction with the learn-ing activities offirms and governments and other universities.Furthermore,the endogenous processes of technical and institutional learning of univer-sities are entangled in the co-evolution of institutional and technical change of the evo-lutionary innovation system at large.We propose to treat the learning of universities as an inseparable endogenous variable in the inno-vation processes of the economic system.In order to structure the endogenization in the system of innovation analysis,the concept of the Learning University is introduced.In thenext subsection we discuss the main character-istics of the Learning University and Section5discusses the learning university in a dynamic,evolutionary innovation system.An evolution-ary metaphor may be helpful to make theuniversity factor more transparent in theco-evolution of technical and institutionalchange,as we try to understand how variouseconomic agents interact in learning processes.4.2Characteristics of the LearningUniversityThe evolution of the involvement of universi-ties in innovation processes is a learningprocess,because(we assume that)universitypublic agents have their‘own agenda’.V ariousincentives in the environment of universitiessuch as government regulations and technol-ogy transfer policies as well as the innovativebehaviour of economic agents,compel policymakers at universities to constantly respondby adapting and improving their strategiesand policies,whereas the university scientistsare partly steered by these strategies and partlyinfluenced by their own scientific peers andpartly by their historically grown interactionswith industry.During this process,universityboards try to be forward-looking and tobehave strategically in the knowledge thattheir actions‘influence the world’(alsoreferred to earlier as‘intentional variety’;see,for instance,Dosi et al.,1988).‘Intentional variety’presupposes that tech-nical and institutional development of univer-sities is a learning process.University agentsundertake purposeful action for change,theylearn from experience and anticipate futurestates of the selective environment.Further-more,university agents take initiatives to im-prove and develop learning paths.An exampleof these learning agents is provided in Box1.We consider technological and institutionaldevelopment of universities as a process thatinvolves many knowledge-seeking activitieswhere public and private agents’perceptionsand actions are translated into practice.3Theinstitutional changes are the result of inter-actions among economic agents defined byLundvall(1992)as interactive learning.Theseinteractions result in an evolutionary pattern3Using a theory developed in one scientific disci-pline as a metaphor in a different discipline mayresult,in a worst-case scenario,in misleading analo-gies.In the best case,however,it can be a source ofcreativity.As Hodgson(2000)pointed out,the evo-lutionary metaphor is useful for understandingprocesses of technical and institutional change,thatcan help to identify new events,characteristics andphenomena.Volume17Number42008©2008The AuthorsJournal compilation©2008Blackwell Publishing。
磁性 neutron scattering说明书
Methods and Tutorials – Single Crystal DiffractionSingle crystal diffraction and magnetism▪Background material:Piccoli P. M. B., Koetzle T. F., Schultz A. J., “Single crystal neutron diffraction for the inorganic chemist - A practical guide”, Comments on Inorganic Chemistry,28, 3-38 (2007).Michels-Clark T. M., Savici A. T., Lynch V. E., Wang X. P., Hoffmann C. M., "Expanding Lorentz and spectrum corrections to large volumes of reciprocal space for single-crystal time-of-flight neutron diffraction", Journal of Applied Crystallography,49, 497-506 (2016).Sheldrick G. M., “Crystal structure refinement with SHELXL”, Acta Crystallographica Section C-Structural Chemistry,71, 3-8 (2015).Petricek V., Dusek M., Plasil J., “Crystallographic computing system Jana2006: solution and refinement of twinned structures”, Zeitschrift für Kristallographie - Crystalline Materials,231, 583-599 (2016).Coll in Broholm’s lecture on magnetic neutron scattering, online:http://cins.ca/docs/ss2013/lectures/Broholm.pdfWills A. S., “A walk through of the maths behind Bertaut’s method of representational analysis of magnetic structures”Petricek V., Henriques M. S., Dusek M., “Solution and Refinement of Magnetic Structures with Jana2006”, Acta Physica Polonica A130, 848-851 (2016).Wilson C. C., “Single crystal neutron diffraction from molecular materials”, World Scientific, 2000 (book).Squires G. L., "Introduction to the Theory of Thermal Neutron Scattering", CambridgeUniversity Press, 2012 (book).Lovesey S. W., "The Theory of Neutron Scattering from Condensed Matter Volume II", Oxford University Press, 1986 (book).Data reductionTOPAZ IntroductionNeutron TOF Data Reduction for Modulated Crystals (TOPAZ)Instruction videos for Single Crystal data reduction. (HB-2C data)Manuals for Single Crystal data reduction. (HB-2C data)Data analysisSHELX Tutorials and TalksSHELX for neutrons George SheldrickRefinement of small molecules against neutron data Xiaoping WangGSAS & EXPGUI GSAS/EXPGUI refinement example Xiaoping WangGSAS-II Single crystal structure refinement with TOF data in GSAS-II Robert Von Dreele (Argonne, 2016)JANA2006 Installation notes Vaclav Petricek and Margarida S. HenriquesTutorial A CsLiSO4: Structure with pseudomerohedric 3-fold twinningTutorial B Y(PO3)3: Modulated crystal structure with crenelTutorial C DyMn6Ge6: A conical magnetic structure with k1 = (0, 0, 0) and k2 = (0, 0, 0.1651) Tutorial D K2V3O8: Solution of (3+1)-dimensional incommensurately modulated structure with twinning (TOPAZ data)ISODISTORT Instructions Branton CampbellISOVIZ and ISOVIZQ InstallersTutorial ExercisesFULLPROFHands-on example Single Crystal, Commensurate Huibo CaoHands-on example Single Crystal, Incommensurate Huibo CaoBilbao Crystallographic Server Hands-on demonstration Manuel Perez-Mato▪SoftwareSHELX https://shelx.uni-goettingen.de/Program package for the determination of small and macromolecular crystal structuresShelXle https:///shelx/eingabe.phpA graphical interface for SHELXLOlex² Crystallography Software /SoftwareProgram package to solve, refine and finish small-molecule crystal structures using an intuitive user interfaceJANA http://jana.fzu.cz/Crystallographic Computing System for Standard and Modulated StructuresStructure solution and refinement of crystal / magnetic structures (CW and TOF neutron)GSAS & EXPGUI https:///xtal/software/downloads.htmlSoftware package to fit structural models to x-ray and neutron diffraction data. It can be used with both single-crystal and powder diffraction data (Rietveld analysis). EXPGUI is a Graphical user interface to GSASGSAS II https:///trac/pyGSASPython project for determination of crystal structures using both powder and single-crystal diffraction with extensive visualization capabilities.FullProf https://www.ill.eu/sites/fullprof/Crystallographic programs mainly developed for Rietveld analysis of neutron (constantwavelength, time of flight, nuclear and magnetic scattering) or X-ray powder diffraction data collected at constant or variable step in scattering angle 2theta.Isotropy Software Suite https:///iso/isotropy.phpA collection of software which applies group theoretical methods to the analysis of phasetransitions in crystalline solids.SARAh /spaces/willsgroup/software/Simulated annealing and representation analysis of magnetic structuresSpinWaveGenie https:///SpinWaveGenie/SpinWaveGenieLibrary for simplifying linear spin wave calculations of magnetic structuresVESTA https:///vesta/en/download.htmlA three-dimensional visualization system for crystal and magnetic structure analysisCCP14 Program repository /mirror.htmCollection of software for single crystal and powder diffraction.Diffuse Scattering▪Tutorials and Manuals:Data analysisrmc-discord Tutorial examples for the refinement of magnetic, occupational and displacive disorder for single crystal in two and three dimensions▪Softwarermc-discord https://zjmorgan.github.io/rmc-discord/An atomistic reverse Monte Carlo (RMC) refinement program for the analysis of diffusescattering from disordered single crystalsDISCUS_SUITE Diffuse program collection https:///tproffen/DiffuseCodeDiffuse scattering & defect structure simulation and refinement, including PDFs from n/X data Javelin https:///rosswhitfield/javelinPython program for X-ray and neutron single crystal nuclear and magnetic diffuse scattering analysisYELL https:///YellProgram/YellDiffuse scattering interpretation using the X-ray 3D-∆PDF refinementUltrafast calculation of diffuse-scattering patterns from atomistic modelsProtein Crystallography▪Background material:Blakeley M. P., Podjarny A. D., “Neutron macromolecular crystallography”,Emerging Topics in Life Science2, 39-55 (2018).Ashkar R., Bilheux H. Z., Bordallo H., Briber R., Callaway D. J. E., Cheng X.,. Chu X.-Q, Curtis J. E., Dadmun M., Fenimore P., Fushman D., Gabel F., Gupta K., Herberle F., Heinrich F., Hong L., Katsaras J., Kelman Z., Kharlampieva E., Kneller G. R., Kovalevsky A., Krueger S., Langan P., Lieberman R., Liu Y., Losche M., Lyman E., Mao Y., Marino J., Mattos C., Meilleur F., Moody P., Nickels J. D., O’Dell W. B., O’Neill H., Perez-Salas U., Peters J., Petridis L., Sokolov A. P., Stanley C., Wagner N., Weinrich M., Weiss K., Wymore T., Zhang Y., Smith J. C., “Neutron scattering in the biological sciences: progress and prospects”,Acta Crystallographica Section D 74, 1129-1168 (2018).Oksanen, E.; Chen, J. C.-H.; Fisher, S. Z., “Neutron Crystallography for the Study of Hydrogen Bonds in Macromolecules”,Molecules22, 596 (2017).Fisher Z., Jackson A., Kovalevsky A., Oksanen E., Wacklin H., Chapter 1 – Biological Structures, in Exp. Methods Phys. Sci., Ed. F. Fernandez-Alonso and D. Price, Elsevier, 49, pp 1-75 (2017).Niimura, N., Takimoto-Kamimura, M., Tanaka, I., “Neutron diffraction in studies of protein dynamics and functions Application of”, Encyclopedia of Analytical Chemistry: Applications, Theory and Instrumentation, 1-30 (2016).O’Dell, W. B., Bodenheimer, A. M., Meilleur, F., “Neutron protein crystallography: a complementary tool for locating hydrogens in proteins”, Archives of Biochemistry and Biophys ics 602, 48-60 (2016).Golden, E. A., Vrielink, A., “Looking for hydrogen atoms: neutron crystallography provides novel insights into protein structure and function”, Australian Journal of Chemistry67, 1751-1762 (2014).Langan, P., Chen, J. C.-H., “Seeing the chemistry in biology with neutron crystallography”, Physical Chemistry Chemical Phys ics15, 13705 (2013).Niimura, N. and Podjarny, A., “Neutron protein crystallography”, Oxford University Press. 250 pp. (2011)Glusker J., Kovalevsky A., Hanson L., Fisher Z., Mustyakimov M., Mason S., Forsyth T., Langan P., “Using Neutron Protein Crystallography to Understand Enzyme Mechanism”,Acta Crystallographica Section D 66, 1257-1261 (2010).Adams, P. D.; Mustyakimov, M.; Afonine, P. V.; Langan, P., “Generalized X-ray and Neutron Crystallographic Analysis: More Accurate and Complete Structures for Biological Macromolecules”, Acta Crystallographica Section D65, 567-573 (2009).Blakeley, M. P., “Neutron macromolecular crystallography”, Crystallography Reviews15, 157-218 (2009).Langan P., Fisher Z., Kovalevsky A., Mustyakimov M., Valone A. S., Unkefer C., Waltman M.J., Coates L., Adams P. D., Afonine P. V., Bennett B., Dealwis C., Schoenborn B. P., “Protein Structures by Spallation Neutron Crystallography”, Journal of Synchrotron Radiation15, 215-218 (2008).Niimura, N., Bau, R., “Neutron protein crystallography: beyond the folding structure of biological macromolecules”, Acta Crystallographica Section A 64, 12-22 (2008).Blakeley, M. P., Langan, P., Niimura, N., Podjarny, A. “Neutron crystallography: opportunities, challenges, and limitations”, Current Opinion in Structural Biol ogy 18, 593-600 (2008).▪Tutorials and Manuals:Data reductionMaNDi https:///neutrons/mandi_autoreduction_scriptsData analysisCCP4 CCP4 YouTube ChannelsPhenix Videos from Phenix workshops▪SoftwareCCP4 https:///Software for Macromolecular X-Ray CrystallographyPhenix https:///Software suite for the automated determination of molecular structures using X-raycrystallography and other methods。
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Modeling of morphology evolution in the injection moldingprocess of thermoplastic polymersR.Pantani,I.Coccorullo,V.Speranza,G.Titomanlio* Department of Chemical and Food Engineering,University of Salerno,via Ponte don Melillo,I-84084Fisciano(Salerno),Italy Received13May2005;received in revised form30August2005;accepted12September2005AbstractA thorough analysis of the effect of operative conditions of injection molding process on the morphology distribution inside the obtained moldings is performed,with particular reference to semi-crystalline polymers.The paper is divided into two parts:in the first part,the state of the art on the subject is outlined and discussed;in the second part,an example of the characterization required for a satisfactorily understanding and description of the phenomena is presented,starting from material characterization,passing through the monitoring of the process cycle and arriving to a deep analysis of morphology distribution inside the moldings.In particular,fully characterized injection molding tests are presented using an isotactic polypropylene,previously carefully characterized as far as most of properties of interest.The effects of both injectionflow rate and mold temperature are analyzed.The resulting moldings morphology(in terms of distribution of crystallinity degree,molecular orientation and crystals structure and dimensions)are analyzed by adopting different experimental techniques(optical,electronic and atomic force microscopy,IR and WAXS analysis).Final morphological characteristics of the samples are compared with the predictions of a simulation code developed at University of Salerno for the simulation of the injection molding process.q2005Elsevier Ltd.All rights reserved.Keywords:Injection molding;Crystallization kinetics;Morphology;Modeling;Isotactic polypropyleneContents1.Introduction (1186)1.1.Morphology distribution in injection molded iPP parts:state of the art (1189)1.1.1.Modeling of the injection molding process (1190)1.1.2.Modeling of the crystallization kinetics (1190)1.1.3.Modeling of the morphology evolution (1191)1.1.4.Modeling of the effect of crystallinity on rheology (1192)1.1.5.Modeling of the molecular orientation (1193)1.1.6.Modeling of theflow-induced crystallization (1195)ments on the state of the art (1197)2.Material and characterization (1198)2.1.PVT description (1198)*Corresponding author.Tel.:C39089964152;fax:C39089964057.E-mail address:gtitomanlio@unisa.it(G.Titomanlio).2.2.Quiescent crystallization kinetics (1198)2.3.Viscosity (1199)2.4.Viscoelastic behavior (1200)3.Injection molding tests and analysis of the moldings (1200)3.1.Injection molding tests and sample preparation (1200)3.2.Microscopy (1202)3.2.1.Optical microscopy (1202)3.2.2.SEM and AFM analysis (1202)3.3.Distribution of crystallinity (1202)3.3.1.IR analysis (1202)3.3.2.X-ray analysis (1203)3.4.Distribution of molecular orientation (1203)4.Analysis of experimental results (1203)4.1.Injection molding tests (1203)4.2.Morphology distribution along thickness direction (1204)4.2.1.Optical microscopy (1204)4.2.2.SEM and AFM analysis (1204)4.3.Morphology distribution alongflow direction (1208)4.4.Distribution of crystallinity (1210)4.4.1.Distribution of crystallinity along thickness direction (1210)4.4.2.Crystallinity distribution alongflow direction (1212)4.5.Distribution of molecular orientation (1212)4.5.1.Orientation along thickness direction (1212)4.5.2.Orientation alongflow direction (1213)4.5.3.Direction of orientation (1214)5.Simulation (1214)5.1.Pressure curves (1215)5.2.Morphology distribution (1215)5.3.Molecular orientation (1216)5.3.1.Molecular orientation distribution along thickness direction (1216)5.3.2.Molecular orientation distribution alongflow direction (1216)5.3.3.Direction of orientation (1217)5.4.Crystallinity distribution (1217)6.Conclusions (1217)References (1219)1.IntroductionInjection molding is one of the most widely employed methods for manufacturing polymeric products.Three main steps are recognized in the molding:filling,packing/holding and cooling.During thefilling stage,a hot polymer melt rapidlyfills a cold mold reproducing a cavity of the desired product shape. During the packing/holding stage,the pressure is raised and extra material is forced into the mold to compensate for the effects that both temperature decrease and crystallinity development determine on density during solidification.The cooling stage starts at the solidification of a thin section at cavity entrance (gate),starting from that instant no more material can enter or exit from the mold impression and holding pressure can be released.When the solid layer on the mold surface reaches a thickness sufficient to assure required rigidity,the product is ejected from the mold.Due to the thermomechanical history experienced by the polymer during processing,macromolecules in injection-molded objects present a local order.This order is referred to as‘morphology’which literally means‘the study of the form’where form stands for the shape and arrangement of parts of the object.When referred to polymers,the word morphology is adopted to indicate:–crystallinity,which is the relative volume occupied by each of the crystalline phases,including mesophases;–dimensions,shape,distribution and orientation of the crystallites;–orientation of amorphous phase.R.Pantani et al./Prog.Polym.Sci.30(2005)1185–1222 1186R.Pantani et al./Prog.Polym.Sci.30(2005)1185–12221187Apart from the scientific interest in understandingthe mechanisms leading to different order levels inside a polymer,the great technological importance of morphology relies on the fact that polymer character-istics (above all mechanical,but also optical,electrical,transport and chemical)are to a great extent affected by morphology.For instance,crystallinity has a pro-nounced effect on the mechanical properties of the bulk material since crystals are generally stiffer than amorphous material,and also orientation induces anisotropy and other changes in mechanical properties.In this work,a thorough analysis of the effect of injection molding operative conditions on morphology distribution in moldings with particular reference to crystalline materials is performed.The aim of the paper is twofold:first,to outline the state of the art on the subject;second,to present an example of the characterization required for asatisfactorilyR.Pantani et al./Prog.Polym.Sci.30(2005)1185–12221188understanding and description of the phenomena, starting from material description,passing through the monitoring of the process cycle and arriving to a deep analysis of morphology distribution inside the mold-ings.To these purposes,fully characterized injection molding tests were performed using an isotactic polypropylene,previously carefully characterized as far as most of properties of interest,in particular quiescent nucleation density,spherulitic growth rate and rheological properties(viscosity and relaxation time)were determined.The resulting moldings mor-phology(in terms of distribution of crystallinity degree, molecular orientation and crystals structure and dimensions)was analyzed by adopting different experimental techniques(optical,electronic and atomic force microscopy,IR and WAXS analysis).Final morphological characteristics of the samples were compared with the predictions of a simulation code developed at University of Salerno for the simulation of the injection molding process.The effects of both injectionflow rate and mold temperature were analyzed.1.1.Morphology distribution in injection molded iPP parts:state of the artFrom many experimental observations,it is shown that a highly oriented lamellar crystallite microstructure, usually referred to as‘skin layer’forms close to the surface of injection molded articles of semi-crystalline polymers.Far from the wall,the melt is allowed to crystallize three dimensionally to form spherulitic structures.Relative dimensions and morphology of both skin and core layers are dependent on local thermo-mechanical history,which is characterized on the surface by high stress levels,decreasing to very small values toward the core region.As a result,the skin and the core reveal distinct characteristics across the thickness and also along theflow path[1].Structural and morphological characterization of the injection molded polypropylene has attracted the interest of researchers in the past three decades.In the early seventies,Kantz et al.[2]studied the morphology of injection molded iPP tensile bars by using optical microscopy and X-ray diffraction.The microscopic results revealed the presence of three distinct crystalline zones on the cross-section:a highly oriented non-spherulitic skin;a shear zone with molecular chains oriented essentially parallel to the injection direction;a spherulitic core with essentially no preferred orientation.The X-ray diffraction studies indicated that the skin layer contains biaxially oriented crystallites due to the biaxial extensionalflow at theflow front.A similar multilayered morphology was also reported by Menges et al.[3].Later on,Fujiyama et al.[4] investigated the skin–core morphology of injection molded iPP samples using X-ray Small and Wide Angle Scattering techniques,and suggested that the shear region contains shish–kebab structures.The same shish–kebab structure was observed by Wenig and Herzog in the shear region of their molded samples[5].A similar investigation was conducted by Titomanlio and co-workers[6],who analyzed the morphology distribution in injection moldings of iPP. They observed a skin–core morphology distribution with an isotropic spherulitic core,a skin layer characterized by afine crystalline structure and an intermediate layer appearing as a dark band in crossed polarized light,this layer being characterized by high crystallinity.Kalay and Bevis[7]pointed out that,although iPP crystallizes essentially in the a-form,a small amount of b-form can be found in the skin layer and in the shear region.The amount of b-form was found to increase by effect of high shear rates[8].A wide analysis on the effect of processing conditions on the morphology of injection molded iPP was conducted by Viana et al.[9]and,more recently, by Mendoza et al.[10].In particular,Mendoza et al. report that the highest level of crystallinity orientation is found inside the shear zone and that a high level of orientation was also found in the skin layer,with an orientation angle tilted toward the core.It is rather difficult to theoretically establish the relationship between the observed microstructure and processing conditions.Indeed,a model of the injection molding process able to predict morphology distribution in thefinal samples is not yet available,even if it would be of enormous strategic importance.This is mainly because a complete understanding of crystallization kinetics in processing conditions(high cooling rates and pressures,strong and complexflowfields)has not yet been reached.In this section,the most relevant aspects for process modeling and morphology development are identified. In particular,a successful path leading to a reliable description of morphology evolution during polymer processing should necessarily pass through:–a good description of morphology evolution under quiescent conditions(accounting all competing crystallization processes),including the range of cooling rates characteristic of processing operations (from1to10008C/s);R.Pantani et al./Prog.Polym.Sci.30(2005)1185–12221189–a description capturing the main features of melt morphology(orientation and stretch)evolution under processing conditions;–a good coupling of the two(quiescent crystallization and orientation)in order to capture the effect of crystallinity on viscosity and the effect offlow on crystallization kinetics.The points listed above outline the strategy to be followed in order to achieve the basic understanding for a satisfactory description of morphology evolution during all polymer processing operations.In the following,the state of art for each of those points will be analyzed in a dedicated section.1.1.1.Modeling of the injection molding processThefirst step in the prediction of the morphology distribution within injection moldings is obviously the thermo-mechanical simulation of the process.Much of the efforts in the past were focused on the prediction of pressure and temperature evolution during the process and on the prediction of the melt front advancement [11–15].The simulation of injection molding involves the simultaneous solution of the mass,energy and momentum balance equations.Thefluid is non-New-tonian(and viscoelastic)with all parameters dependent upon temperature,pressure,crystallinity,which are all function of pressibility cannot be neglected as theflow during the packing/holding step is determined by density changes due to temperature, pressure and crystallinity evolution.Indeed,apart from some attempts to introduce a full 3D approach[16–19],the analysis is currently still often restricted to the Hele–Shaw(or thinfilm) approximation,which is warranted by the fact that most injection molded parts have the characteristic of being thin.Furthermore,it is recognized that the viscoelastic behavior of the polymer only marginally influences theflow kinematics[20–22]thus the melt is normally considered as a non-Newtonian viscousfluid for the description of pressure and velocity gradients evolution.Some examples of adopting a viscoelastic constitutive equation in the momentum balance equations are found in the literature[23],but the improvements in accuracy do not justify a considerable extension of computational effort.It has to be mentioned that the analysis of some features of kinematics and temperature gradients affecting the description of morphology need a more accurate description with respect to the analysis of pressure distributions.Some aspects of the process which were often neglected and may have a critical importance are the description of the heat transfer at polymer–mold interface[24–26]and of the effect of mold deformation[24,27,28].Another aspect of particular interest to the develop-ment of morphology is the fountainflow[29–32], which is often neglected being restricted to a rather small region at theflow front and close to the mold walls.1.1.2.Modeling of the crystallization kineticsIt is obvious that the description of crystallization kinetics is necessary if thefinal morphology of the molded object wants to be described.Also,the development of a crystalline degree during the process influences the evolution of all material properties like density and,above all,viscosity(see below).Further-more,crystallization kinetics enters explicitly in the generation term of the energy balance,through the latent heat of crystallization[26,33].It is therefore clear that the crystallinity degree is not only a result of simulation but also(and above all)a phenomenon to be kept into account in each step of process modeling.In spite of its dramatic influence on the process,the efforts to simulate the injection molding of semi-crystalline polymers are crude in most of the commercial software for processing simulation and rather scarce in the fleur and Kamal[34],Papatanasiu[35], Titomanlio et al.[15],Han and Wang[36],Ito et al.[37],Manzione[38],Guo and Isayev[26],and Hieber [25]adopted the following equation(Kolmogoroff–Avrami–Evans,KAE)to predict the development of crystallinityd xd tZð1K xÞd d cd t(1)where x is the relative degree of crystallization;d c is the undisturbed volume fraction of the crystals(if no impingement would occur).A significant improvement in the prediction of crystallinity development was introduced by Titoman-lio and co-workers[39]who kept into account the possibility of the formation of different crystalline phases.This was done by assuming a parallel of several non-interacting kinetic processes competing for the available amorphous volume.The evolution of each phase can thus be described byd x id tZð1K xÞd d c id t(2)where the subscript i stands for a particular phase,x i is the relative degree of crystallization,x ZPix i and d c iR.Pantani et al./Prog.Polym.Sci.30(2005)1185–1222 1190is the expectancy of volume fraction of each phase if no impingement would occur.Eq.(2)assumes that,for each phase,the probability of the fraction increase of a single crystalline phase is simply the product of the rate of growth of the corresponding undisturbed volume fraction and of the amount of available amorphous fraction.By summing up the phase evolution equations of all phases(Eq.(2))over the index i,and solving the resulting differential equation,one simply obtainsxðtÞZ1K exp½K d cðtÞ (3)where d c Z Pid c i and Eq.(1)is recovered.It was shown by Coccorullo et al.[40]with reference to an iPP,that the description of the kinetic competition between phases is crucial to a reliable prediction of solidified structures:indeed,it is not possible to describe iPP crystallization kinetics in the range of cooling rates of interest for processing(i.e.up to several hundreds of8C/s)if the mesomorphic phase is neglected:in the cooling rate range10–1008C/s, spherulite crystals in the a-phase are overcome by the formation of the mesophase.Furthermore,it has been found that in some conditions(mainly at pressures higher than100MPa,and low cooling rates),the g-phase can also form[41].In spite of this,the presence of different crystalline phases is usually neglected in the literature,essentially because the range of cooling rates investigated for characterization falls in the DSC range (well lower than typical cooling rates of interest for the process)and only one crystalline phase is formed for iPP at low cooling rates.It has to be noticed that for iPP,which presents a T g well lower than ambient temperature,high values of crystallinity degree are always found in solids which passed through ambient temperature,and the cooling rate can only determine which crystalline phase forms, roughly a-phase at low cooling rates(below about 508C/s)and mesomorphic phase at higher cooling rates.The most widespread approach to the description of kinetic constant is the isokinetic approach introduced by Nakamura et al.According to this model,d c in Eq.(1)is calculated asd cðtÞZ ln2ðt0KðTðsÞÞd s2 435n(4)where K is the kinetic constant and n is the so-called Avrami index.When introduced as in Eq.(4),the reciprocal of the kinetic constant is a characteristic time for crystallization,namely the crystallization half-time, t05.If a polymer is cooled through the crystallization temperature,crystallization takes place at the tempera-ture at which crystallization half-time is of the order of characteristic cooling time t q defined ast q Z D T=q(5) where q is the cooling rate and D T is a temperature interval over which the crystallization kinetic constant changes of at least one order of magnitude.The temperature dependence of the kinetic constant is modeled using some analytical function which,in the simplest approach,is described by a Gaussian shaped curve:KðTÞZ K0exp K4ln2ðT K T maxÞ2D2(6)The following Hoffman–Lauritzen expression[42] is also commonly adopted:K½TðtÞ Z K0exp KUÃR$ðTðtÞK T NÞ!exp KKÃ$ðTðtÞC T mÞ2TðtÞ2$ðT m K TðtÞÞð7ÞBoth equations describe a bell shaped curve with a maximum which for Eq.(6)is located at T Z T max and for Eq.(7)lies at a temperature between T m(the melting temperature)and T N(which is classically assumed to be 308C below the glass transition temperature).Accord-ing to Eq.(7),the kinetic constant is exactly zero at T Z T m and at T Z T N,whereas Eq.(6)describes a reduction of several orders of magnitude when the temperature departs from T max of a value higher than2D.It is worth mentioning that only three parameters are needed for Eq.(6),whereas Eq.(7)needs the definition offive parameters.Some authors[43,44]couple the above equations with the so-called‘induction time’,which can be defined as the time the crystallization process starts, when the temperature is below the equilibrium melting temperature.It is normally described as[45]Dt indDtZðT0m K TÞat m(8)where t m,T0m and a are material constants.It should be mentioned that it has been found[46,47]that there is no need to explicitly incorporate an induction time when the modeling is based upon the KAE equation(Eq.(1)).1.1.3.Modeling of the morphology evolutionDespite of the fact that the approaches based on Eq.(4)do represent a significant step toward the descriptionR.Pantani et al./Prog.Polym.Sci.30(2005)1185–12221191of morphology,it has often been pointed out in the literature that the isokinetic approach on which Nakamura’s equation (Eq.(4))is based does not describe details of structure formation [48].For instance,the well-known experience that,with many polymers,the number of spherulites in the final solid sample increases strongly with increasing cooling rate,is indeed not taken into account by this approach.Furthermore,Eq.(4)describes an increase of crystal-linity (at constant temperature)depending only on the current value of crystallinity degree itself,whereas it is expected that the crystallization rate should depend also on the number of crystalline entities present in the material.These limits are overcome by considering the crystallization phenomenon as the consequence of nucleation and growth.Kolmogoroff’s model [49],which describes crystallinity evolution accounting of the number of nuclei per unit volume and spherulitic growth rate can then be applied.In this case,d c in Eq.(1)is described asd ðt ÞZ C m ðt 0d N ðs Þd s$ðt sG ðu Þd u 2435nd s (9)where C m is a shape factor (C 3Z 4/3p ,for spherical growth),G (T (t ))is the linear growth rate,and N (T (t ))is the nucleation density.The following Hoffman–Lauritzen expression is normally adopted for the growth rateG ½T ðt Þ Z G 0exp KUR $ðT ðt ÞK T N Þ!exp K K g $ðT ðt ÞC T m Þ2T ðt Þ2$ðT m K T ðt ÞÞð10ÞEqs.(7)and (10)have the same form,however the values of the constants are different.The nucleation mechanism can be either homo-geneous or heterogeneous.In the case of heterogeneous nucleation,two equations are reported in the literature,both describing the nucleation density as a function of temperature [37,50]:N ðT ðt ÞÞZ N 0exp ½j $ðT m K T ðt ÞÞ (11)N ðT ðt ÞÞZ N 0exp K 3$T mT ðt ÞðT m K T ðt ÞÞ(12)In the case of homogeneous nucleation,the nucleation rate rather than the nucleation density is function of temperature,and a Hoffman–Lauritzen expression isadoptedd N ðT ðt ÞÞd t Z N 0exp K C 1ðT ðt ÞK T N Þ!exp KC 2$ðT ðt ÞC T m ÞT ðt Þ$ðT m K T ðt ÞÞð13ÞConcentration of nucleating particles is usually quite significant in commercial polymers,and thus hetero-geneous nucleation becomes the dominant mechanism.When Kolmogoroff’s approach is followed,the number N a of active nuclei at the end of the crystal-lization process can be calculated as [48]N a ;final Zðt final 0d N ½T ðs Þd sð1K x ðs ÞÞd s (14)and the average dimension of crystalline structures can be attained by geometrical considerations.Pantani et al.[51]and Zuidema et al.[22]exploited this method to describe the distribution of crystallinity and the final average radius of the spherulites in injection moldings of polypropylene;in particular,they adopted the following equationR Z ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi3x a ;final 4p N a ;final 3s (15)A different approach is also present in the literature,somehow halfway between Nakamura’s and Kolmo-goroff’s models:the growth rate (G )and the kinetic constant (K )are described independently,and the number of active nuclei (and consequently the average dimensions of crystalline entities)can be obtained by coupling Eqs.(4)and (9)asN a ðT ÞZ 3ln 24p K ðT ÞG ðT Þ 3(16)where heterogeneous nucleation and spherical growth is assumed (Avrami’s index Z 3).Guo et al.[43]adopted this approach to describe the dimensions of spherulites in injection moldings of polypropylene.1.1.4.Modeling of the effect of crystallinity on rheology As mentioned above,crystallization has a dramatic influence on material viscosity.This phenomenon must obviously be taken into account and,indeed,the solidification of a semi-crystalline material is essen-tially caused by crystallization rather than by tempera-ture in normal processing conditions.Despite of the importance of the subject,the relevant literature on the effect of crystallinity on viscosity isR.Pantani et al./Prog.Polym.Sci.30(2005)1185–12221192rather scarce.This might be due to the difficulties in measuring simultaneously rheological properties and crystallinity evolution during the same tests.Apart from some attempts to obtain simultaneous measure-ments of crystallinity and viscosity by special setups [52,53],more often viscosity and crystallinity are measured during separate tests having the same thermal history,thus greatly simplifying the experimental approach.Nevertheless,very few works can be retrieved in the literature in which(shear or complex) viscosity can be somehow linked to a crystallinity development.This is the case of Winter and co-workers [54],Vleeshouwers and Meijer[55](crystallinity evolution can be drawn from Swartjes[56]),Boutahar et al.[57],Titomanlio et al.[15],Han and Wang[36], Floudas et al.[58],Wassner and Maier[59],Pantani et al.[60],Pogodina et al.[61],Acierno and Grizzuti[62].All the authors essentially agree that melt viscosity experiences an abrupt increase when crystallinity degree reaches a certain‘critical’value,x c[15]. However,little agreement is found in the literature on the value of this critical crystallinity degree:assuming that x c is reached when the viscosity increases of one order of magnitude with respect to the molten state,it is found in the literature that,for iPP,x c ranges from a value of a few percent[15,62,60,58]up to values of20–30%[58,61]or even higher than40%[59,54,57].Some studies are also reported on the secondary effects of relevant variables such as temperature or shear rate(or frequency)on the dependence of crystallinity on viscosity.As for the effect of temperature,Titomanlio[15]found for an iPP that the increase of viscosity for the same crystallinity degree was higher at lower temperatures,whereas Winter[63] reports the opposite trend for a thermoplastic elasto-meric polypropylene.As for the effect of shear rate,a general agreement is found in the literature that the increase of viscosity for the same crystallinity degree is lower at higher deformation rates[62,61,57].Essentially,the equations adopted to describe the effect of crystallinity on viscosity of polymers can be grouped into two main categories:–equations based on suspensions theories(for a review,see[64]or[65]);–empirical equations.Some of the equations adopted in the literature with regard to polymer processing are summarized in Table1.Apart from Eq.(17)adopted by Katayama and Yoon [66],all equations predict a sharp increase of viscosity on increasing crystallinity,sometimes reaching infinite (Eqs.(18)and(21)).All authors consider that the relevant variable is the volume occupied by crystalline entities(i.e.x),even if the dimensions of the crystals should reasonably have an effect.1.1.5.Modeling of the molecular orientationOne of the most challenging problems to present day polymer science regards the reliable prediction of molecular orientation during transformation processes. Indeed,although pressure and velocity distribution during injection molding can be satisfactorily described by viscous models,details of the viscoelastic nature of the polymer need to be accounted for in the descriptionTable1List of the most used equations to describe the effect of crystallinity on viscosityEquation Author Derivation Parameters h=h0Z1C a0x(17)Katayama[66]Suspensions a Z99h=h0Z1=ðx K x cÞa0(18)Ziabicki[67]Empirical x c Z0.1h=h0Z1C a1expðK a2=x a3Þ(19)Titomanlio[15],also adopted byGuo[68]and Hieber[25]Empiricalh=h0Z expða1x a2Þ(20)Shimizu[69],also adopted byZuidema[22]and Hieber[25]Empiricalh=h0Z1Cðx=a1Þa2=ð1Kðx=a1Þa2Þ(21)Tanner[70]Empirical,basedon suspensionsa1Z0.44for compact crystallitesa1Z0.68for spherical crystallitesh=h0Z expða1x C a2x2Þ(22)Han[36]Empiricalh=h0Z1C a1x C a2x2(23)Tanner[71]Empirical a1Z0.54,a2Z4,x!0.4h=h0Zð1K x=a0ÞK2(24)Metzner[65],also adopted byTanner[70]Suspensions a Z0.68for smooth spheresR.Pantani et al./Prog.Polym.Sci.30(2005)1185–12221193。
22705900_阿尔金北缘新太古代TTG片麻岩的成因及其构造意义
苏必利尔克拉通( , )、波罗的地盾( , , ; , ; , ;梅 Henry et al 2000
Samsonov al 2012a 2013b Zhao et al 2015 Zong et al 2013
et al ,2005)、西格林兰克拉通(Polat et al ,2008)、华北克 华林等,1997,1998;王忠梅等,2013;张建新等,2011;赵
Key words TTG gneiss Zircon SHRIMP UPb dating Petrogenesis North Altyn Tagh Tarim Craton
摘 要 塔里木克拉通前寒武纪构造演化,特别是早前寒武纪构造演化一直是地质学家讨论的焦点。本文通过对阿尔金 北缘新太古代TTG 片麻岩进行详细的野外调查、岩相学观察、地球化学分析以及锆石SHRIMP UPb 定年来揭示该岩石的成因 以及探讨塔里木克拉通早前寒武纪构造演化。锆石SHRIMP UPb 定年结果显示阿尔金北缘TTG 片麻岩的形成年龄为2740 ± 19Ma,而后经历了新太古代(2494 ± 53Ma)混合岩化作用和古元古代(1962 ± 78Ma)麻粒岩相变质作用。阿尔金北缘英云闪 长质片麻岩显示低的MgO 含量(1 33% ~ 3 )和 ( 08% Mg# 37 ~ 52),具有高Sr(469 × 10 -6 ~ 764 × 10 -6 )含量、低Y(4 72 × 10 -6 ~ 13 5 × 10 -6)和Yb(0 37 × 10 -6 ~ 0 99 × 10 -6)含量的特点,它们的Sr / Y 比值可达到41 ~ 99。岩石的这些特征与基性 下地壳部分熔融形成的TTG 相同。并且,该新太古代TTG 片麻岩还具有正的εNd(t)值(0 2 ~ 3 6)、高的Nd 同位素初始值 (0 509088 ~ 0 509260)和古太古代两阶段模式年龄(3 62 ~ 3 70Ga)。因此,阿尔金北缘新太古代TTG 片麻岩可能来源于基 性下地壳部分熔融,并且岩浆源区有石榴石、角闪石和金红石的残留。综合前人的研究成果,对比相邻区域TTG 的形成时代, 变质事件的记录以及太古宙地壳增生差异都指示阿尔金北缘和敦煌库鲁塔格地区可能来源于不同的大陆块体。 关键词 TTG 片麻岩;锆石SHRIMP UPb 定年;岩石成因;阿尔金北缘;塔里木克拉通 中图法分类号 ; P588 121 P597 3
美国石油天然气测量标准(API):天然气样品收集与持有转移的指南说明书
COLLECTING AND HANDLING OF NATURAL GAS SAMPLES FOR CUSTODY TRANSFERChristopher L. Grant, Dr. Darin L. George, and Jacob L. ThorsonSouthwest Research InstituteINTRODUCTIONThe American Petroleum Institute (API) Manual of Petroleum Measurement Standards (MPMS) Chapter 14.1, Collecting and Handling of Natural Gas Samples for Custody Transfer, provides practical guidance for gas sampling in custody transfer applications. Though gas sampling should not be performed without fully reading the standard, this paper is designed to provide supplemental information, illustrative examples, and guidelines for how best to use API 14.1. Specific sections of the standard are highlighted and broadened with additional detail. Special emphasis is put on the accurate sampling of an unknown gas stream.THE IMPORTANCE OF THE HYDROCARBON DEW POINTIn natural gas sampling applications, it is important to be familiar with the hydrocarbon dew point (HDP) and to be aware of how it can affect your sample’s accuracy. This is different from the water dew point, which is another topic of concern, but will not be discussed in this paper. An example image of the HDP as viewed in a chilled mirror device is shown in Figure 1. The HDP is defined as the temperature for a given pressure at which hydrocarbon condensation begins (1). The HDP is often plotted on a temperature versus pressure chart as shown with the dashed blue line in Figure 2. To the right of the HDP curve and above the critical temperature, no liquids will be present. As the pressure-temperature state moves to the left of the HDP curve, liquids will condense, and a natural gas sample will contain gas and liquid phases simultaneously.Figure 1. Gas at the Hydrocarbon Dew Point in a Chilled Mirror DeviceIn the image above, faint droplets are visible on the mirror with an iridescent ring around the perimeter of the mirror. This indicates thatthe HDP has been reached (1).Note that the curve passes through or near common pipeline operating temperatures and pressures in a variety of locations. A common process that causes a gas to condense is known as the Joule-Thomson (J-T) effect and is caused by a gas cooling as its pressure drops. This process can be encountered in sampling systems if a gas sample flows through a restriction such as a partially open needle valve. If this is the case, the gas and equipment must be warmed enough to counteract the J-T cooling effect. Many of the guidelines outlined in API Chapter 14.1 are aimed at avoiding this transition during sampling.The HDP curve shown in Figure 2 below is an approximation, and the true HDP curve can be difficult to predict accurately for some pipeline gases. Because different components condense at different temperatures and rates, crossing the HDP curve will change the density, heating value, and many other properties of the remaining gas. Generally, heavy hydrocarbons condense before lighter components causing a drop in the measured heating value and density – two key measurements in custody transfer applications.Figure 2. Pressure vs Temperature Plot of a Hydrocarbon Dew Point Curve An example plot of a phase boundary curve for a typical natural gas mixture is shown. The blue line represents the HDP curve (2). Care must be taken in the handling of a sample after it is collected to avoid condensation and distortions in the sample properties. If a gas sample has changed phase within the sample cylinder, and the cylinder has not been opened, the condensation process may be reversed. This is accomplished by heating the sample cylinder above the predicted HDP for enough time to revaporize all of the condensation. The standard requires that the sample cylinder be held at 30°F above the HDP for at least two hours. This revaporization must be conducted before any liquid or gas has been removed from the sample cylinder, or the gas sampled by the GC and that remaining in the cylinder will both be distorted.As an example of the effects of condensation, consider a mix of 1,500 Btu/scf gas with the components shown in Table 1. This gas is rich but is well within the range of natural gases found upstream of processing stations. If this gas were at 75 psia, the HDP would be roughly 91°F. A drop of 50°F below the hydrocarbon dew point would cause condensation and would cause the remaining gas to have a heating value 70 Btu/scf lower than the sampled gas stream. This would coincide with only a 3% drop in vapor fraction. If this occurred in a 300 cc cylinder at 75 psia, the condensed liquid would be less than 1/1,000 of a pound, a small enough amount to easily avoid detection (2). If this condensation were to occur in a crevice or other difficult to clean area, it could contaminate a later sample and increase its measured heating value (3).Table 1. Composition of an Example Gas Mixture with a Heating Value of 1,500 Btu/scfPercentComponent MoleMethane 64.107Ethane 10.330Propane 7.128Iso-butane 2.174Normal butane 6.386Iso-pentane 1.874Normal pentane 2.307Normal hexane 0.538Normal heptane 0.187Normal octane 0.086Normal nonane 0.023Normal decane 0.016Nitrogen 3.939Carbon dioxide 0.906Total 100.001GUIDELINES FOR INITIAL SAMPLING OF A GAS STREAM OF UNKNOWN HYDROCARBON DEW POINT AND COMPOSITIONSampling an unknown gas stream for custody transfer poses unique risks. Without knowledge of the gas stream composition, samples may be collected improperly, and J-T cooling or exposure to ambient temperatures can drop the sample temperature below its HDP. A gas stream below its HDP can lose heavy hydrocarbons through condensation, and the liquids can be trapped in the sample connections or in the cylinder itself. This can lead to several issues:∙ A sample analysis that indicates a lower (or higher) energy content than the actual gas stream, leading to lower (or higher) custody transfer revenue.∙Pipeline natural gas that violates custody transfer tariffs, but is not recognized as being in violation.∙Equipment problems such as damaged turbines, flooding of burners, and poor combustion.In short, sampling an unknown gas stream requires care and attention to avoid potentially significant costs to the operator and/or the end user of the natural gas.Measuring HDPs before SamplingWhen faced with sampling an unknown gas stream, the preferred technique is to measure the HDP and keep the temperature of the sample (and the sampling equipment) above the HDP. HDP measurement can be done manually using chilled mirror devices or automatically with a variety of automated analyzers.Manual HDP measurement has been standardized in Annex G of the seventh edition of API Chapter 14.1 (1). The annex references the ASTM D1142 standard for measuring water dew points using a chilled mirror device (8). The annex expands on this standard by providing guidelines for measuring the HDP of natural gas mixtures using the same device. The procedures were developed using a combination of practical industry knowledge and applied research. Notably, the annex provides uncertainty values for HDP measurements made with chilled mirrors (5).Annex G also illustrates different types and amounts of condensation that an operator could see within a chilled mirror device during normal use and while diagnosing problems. A few of these illustrations are shown in Figure 3. It should be noted that manual measurement, though standardized, is still subjective, since different operators can obtain different results on the same gas stream.Figure 3. Example Images of Condensation Observed on a Chilled Mirror Device Clockwise from the top left, these images show hydrocarbon condensation, water condensation, glycol contamination, and alcoholcondensation (5).Automated HDP measurement devices can vary greatly in operating methods. Examples include optical detection of condensate on a chilled mirror, spectroscopic analysis of a gas stream and correlation to HDP, and gas chromatographic analysis and equation of state HDP calculation. Automated HDP measurement devices are objective and are often more repeatable than manual measurements. However, they can suffer from measurement interference and other sources of bias.Sampling Without Direct HDP MeasurementsWhen the HDP is impractical to measure, gas samples can be taken, but the samples should be checked to confirm that the gas in the pipeline is above its HDP. API Chapter 14.1 describes various approaches to collecting samples when the HDP is unknown. Most of these approaches require the use of an equation of state (EOS) to predict the HDP from an analysis of the sample. From most to least preferred, the recommended sampling methods are listed below.1.Take a constant pressure spot sample at or above the flowing gas temperature, perform an extended analysis, andcalculate the HDP temperature using the analysis and an EOS.e a pressure-reducing sampling method, perform an extended analysis, and calculate the HDP temperature using anEOS.e historical information, including past analyses and dew point measurements from a similar source.4.Take a spot sample at line pressure, heat the sample gas to at least 30ºF above the flowing temperature at the time ofthe sample, perform an extended analysis, and calculate the HDP temperature using an EOS.If the HDP temperature calculated from one of these samples is above the flowing temperature, the sample is suspect and cannot be considered representative of the gas stream. Direct measurement of the HDP is recommended before any further gas samples are taken.USE OF EQUATIONS OF STATE (EOS)As noted above, EOSs may be used with sample analyses to predict the HDP of a gas stream. Several EOSs are used by the natural gas industry to predict the properties of natural gases with a given composition at a known pressure. The Peng-Robinson (P-R) EOS and Soave-Redlich-Kwong (SRK) EOS are two EOSs commonly used by the natural gas industry to predict the HDP of natural gases. These have been found to predict the HDP well for leaner gases, but often under-predict the HDP for richer gases, particularly at higher pressures. This is illustrated in Figure 4, where both EOSs are compared to experimental data for a representative production gas with a heating value of 1,325 Btu/scf.A more recent EOS, developed at Ruhr-Universität Bochum (the University of Bochum) in Germany, is known as GERG-2008(10). This equation uses a thermodynamic property known as the Helmholtz free energy to predict various properties of gas mixtures, including HDPs and phase boundaries. Limited tests of this equation have shown better agreement with existing HDP data than the P-R and SRK EOSs at higher pressures and for richer gases, as shown in Figure 4.Figure 4. Predicted versus Experimental Hydrocarbon Dew PointThe above plot compares experimentally measured hydrocarbon dew points to the P-R EOS (black line), the SRK EOS (pink line), and the GERG-2008 EOS (green line). This demonstrates the tendency of the P-R and SRK EOSs to under-predict the HDP of rich gases, such asproduction gases, at higher pressures.Heavy Hydrocarbon “Lumping” ModelsOne persistent challenge in the use of EOSs to predict HDPs (and other natural gas properties) is the need for data on hydrocarbons heavier than hexane. Often, these components are not measured individually by a field GC, but are reported as a combined total, or a “C6+ fraction.” These hydrocarbons comprise a small portion of common natural gas mixtures but have a significant impact on the mixture’s density, heating value, and HDP. Therefore, various models have been developed for characterizing these components.Research has shown that currently there is no single characterization method that works best for predicting the HDP of all gas streams (5). The research did show that treating the C6+ fraction as normal hexane did not accurately predict the HDP and could cause the HDP to be under-predicted by as much as 70°F. Many field GCs use the GPA 60/30/10 method of characterizing the C6+ fraction (60% n-hexane, 30% n-heptane, and 10% n-octane). This approach, and similar standard fraction distributions, can accurately characterize the density, heating value, and many other properties of many natural gas streams. However, these same distributions generally predict the HDP of typical gas streams only to within ±25°F (5). There are other characterization models available, but questions remain about how well they work when used with different EOS to predict HDPs (9). Where possible, a periodic extended analysis of a gas stream to at least C9 is recommended for accurate HDP predictions.Differences between Calculated and Measured HDPsUsers should be aware of the differences between HDPs predicted by an EOS and measured HDPs. An EOS predicts the temperature at which the first few heavy hydrocarbon molecules in the gas stream theoretically condense out to form liquid. A device used to measure the HDP will register the temperature at which the smallest amount of condensate can be detected. In the case of a Bureau of Mines chilled mirror device, the HDP will depend on the skill and eyesight of the operator.Both HDPs predicted by EOS and HDP measurements are subject to biases. For HDPs calculated from a sample analysis, these can include biases in the sampling procedure, biases in the sample analysis, and biases in the EOS and its parameters. HDP measurement biases are commonly related to the detection method, but may also be related to the method of transporting the sample to the instrument.Measured HDP temperatures tend to be a few tenths to a few degrees Fahrenheit less than a calculated HDP, since an instrument requires more than a few molecules to detect condensation. In general, as the gas composition becomes richer, the differences between measured and calculated HDPs tend to decrease, because more heavy hydrocarbons will condense out from a richer gas as the temperature falls below the HDP.EQUIPMENT HEATING REQUIREMENTSTo avoid sample condensation and the errors discussed above, API Chapter 14.1 requires that sampling equipment be kept at least 30°F above the predicted HDP. It does allow operators to use a lower margin if the difference between experimental and predicted hydrocarbon dew points has been shown to be less than 30°F for the gas of interest. This requirement is separate from the heating requirements imposed by Joule-Thomson cooling. The requirement covers all equipment that comes in contact with the gas sample, and is intended as a safety margin to ensure that the gas stays above its HDP as it travels to the sample cylinder. API Chapter 14.1 also gives guidance on how to properly heat or insulate sampling equipment to consistently keep it at the required temperature.SAMPLE PROBE LENGTH AND LOCATIONBesides precautions to avoid sample condensation, the length and location of the sample probe should also be examined. As natural gas production has increased, flow rates through existing pipelines have correspondingly increased. As a consequence, industry has witnessed large diameter pipelines flowing gas at higher pressures and velocities than ever before. This combination of longer probes required by larger diameter pipelines and higher velocities has increased the fatigue loading on probes as they begin to resonate. If not accounted for by the probe designer, fatigue loading can cause probes to fail catastrophically and to be swept downstream into other equipment.API Chapter 14.1 gives equations and other guidance for selecting sample probes appropriately to avoid these failures. For example, in Table 2, the maximum length for probes is recommended based on common probe diameters (see Figure 5). API Chapter 14.1 gives several other guidelines for probe installation.∙Probes should be mounted vertically at the top of a straight run of pipe.∙If the gas is not near its HDP, the probe may be placed at any axial location in a meter run that doesn’t interfere with the performance of the primary metering element (1).∙If the gas is at or near its HDP, the probe should be at least five nominal diameters downstream from any major disturbances. This is designed to avoid ingesting liquid droplets that could be condensed out of the gas or swept into the gas in the wake of the disturbance. Some of the major disturbances listed are orifice plates, elbows, tees, and flow conditioners (1).ProbeODProbe LengthFigure 5. Two Example Sample ProbesSample probes are shown with beveled (left) and straight-cut (right) ends. Straight-cut probes are preferred over beveled probes (1).Recommended values for the labeled dimensions are shown in Table 2.Table 2. Maximum Probe Length Recommendations for Common Probe DiametersProbe Outer Diameter (in) Recommended Max ProbeLength (in).250 2.00.375 3.25.500 4.25.750 6.50SAMPLING METHODSAPI 14.1 references GPA Standard 2166 (6) regarding spot sampling methods, and the reader is referred to that standard for details of the various methods. One change of note to the GPA standard that may not yet be commonly used is related to the fill-and-empty method of sampling. In this method, a length of tube must be installed downstream of the sample cylinder with a flow restriction at the end of the tube. This flow restriction forces the pressure drop to occur at the orifice instead of inside of the sample cylinder and reduces the risk of condensation inside the cylinder itself.The previous edition of GPA 2166 required that this flow restriction be a drilled plug. The standard now allows for other flow restrictions and specifically discusses the use of devices with a flow coefficient (Cv) between 0.09 and 0.53. One device specifically mentioned that can meet this specification is a partially open needle valve, although any device is allowed as long as it meets the requirements for thermal isolation and throttling.GUIDELINES FOR LABORATORY ANALYSISTo help ensure that natural gas samples are both properly collected and analyzed, API Chapter 14.1 gives guidance on laboratory sample analysis, with specific guidance to the preparation of gas chromatograph (GC) calibration standards. For example, it requires that laboratories meet the GPA operational requirements laid out in GPA Standard 2198 (7). API Chapter 14.1 also requires that GC calibration standards be prepared according to GPA 2198 and calls out specific requirements from that standard. It requires that gases must be gravimetrically prepared; that is, each component must be weighed as it is added to the mixture. It requires that those measurements be traceable back to NIST or an equivalent standards body.API Chapter 14.1 also requires that each component of a given GC calibration mixture be screened for impurities and that any impurities be accounted for in the final composition. It also calls out the required accuracy of the composition as shown in Table 3. This guideline requires that the accuracy of each component’s concentration fall within the specified ranges based on the nominal concentration.Table 3. Required Blending AccuracyThe table below illustrates the required accuracy for GC calibration standards. These guide the required accuracy for each componentbased on what percent of the total composition it comprises (7).Percent AccuracyPercent Concentration(mole %)0 to 0.099% 5%0.10 to 9.999% 2%10.0% to 100% 1%AUTO-IGNITIONAPI Chapter 14.1 Section 16 reflects industry concerns regarding auto-ignition of natural gas in sample containers. There is a theoretical possibility of auto-ignition if a sample cylinder is not properly purged and filled. Specifically, if a sample cylinder is stored at a low pressure and then is rapidly pressurized with gas, a shockwave could occur within the cylinder. This shockwave would compress the gas at its forefront and correspondingly heat it. If this heating brought the gas above its auto-ignition temperature and the cylinder had also contained oxygen before the rapid filling process, a combustion process could occur. This process would require an inlet valve with a large flow area that was opened very quickly, as with a large quarter turn valve. API Chapter 14.1 notes that API is not aware of this actually occurring in the field, but the process is possible in theory (1).CHECKLIST FOR INSPECTING FIELD SAMPLING LOCATIONS AND PROCEDURESThe seventh edition of API Chapter 14.1 includes a checklist (Annex H) for inspecting field sites where natural gas is sampled, the sampling methods used, and the procedures used to analyze samples in the lab. The checklist is recommended for use by field personnel, company auditors, and training instructors to ensure that API Chapter 14.1 guidelines are followed and that natural gas samples are collected according to API Chapter 14.1 requirements. In 2017, the Bureau of Land Management (BLM) referenced API Chapter 14.1, Annex H in its regulations for the measurement of natural gas produced on federal lands, and this checklist will be used by BLM inspectors as well.CONCLUSIONAPI 14.1 serves the natural gas industry as the standard for best practices in the collection and handling of gas samples in custody transfer. In support, this paper has expanded on several important sections of the standard, providing background information, examples, and guidelines.REFERENCES1.API Manual of Petroleum Measurement Standards, Chapter 14 – Natural Gas Fluids Measurement, Section 1 – Collectingand Handling of Natural Gas Samples for Custody Transfer, Seventh Edition, American Petroleum Institute, WashingtonD.C., May 2016.2.George, D. L. and Kelner E., Lessons Learned from the API MPMS, Chapter 14.1 Gas Sampling Research Project,Proceedings of the 2014 American School of Gas Measurement Technology, Houston, TX,.3.Metering Research Facility Program: Natural Gas Sample Collection and Handling-Phase I, Behring, K.A. III and Kelner,E., GRI Topical Report No. GRI-99/0194, Gas Technology Institute, Des Plaines, Illinois, August 1999.4.Metering Research Facility Program: Natural Gas Sample Collection and Handling-Phase V, George, D. L., Burkey, R.C., and Morrow, T. B., GRI Topical Report No. GRI-05/0134, Gas Technology Institute, Des Plaines, Illinois, March 2005.5.Metering Research Facility Program: Natural Gas Sample Collection and Handling-Phase IV, George, D. L., Barajas, A.M., Kelner, E., and Nored, M., GRI Topical Report No. GRI-03/0049, Gas Technology Institute, Des Plaines, Illinois, January 2005.6.GPA Standard 2166, Obtaining Natural Gas Samples for Analysis by Gas Chromatography, Gas Processors Association,Tulsa, Oklahoma, 2005 (reaffirmed 2017).7.GPA Standard 2198, Selection, Preparation, Validation, Care and Storage of Natural Gas and Natural Gas LiquidsReference Standard Blends, Gas Processors Association, Tulsa, Oklahoma, 2016.8.ASTM Standard D1142, Standard Test Method for Water Vapor Content of Gaseous Fuels by Measurement of Dew PointTemperature, ASTM International, West Conshohocken, PA, 1995 (reaffirmed 2012).ughton, A., Use of the GERG-2008 Equation of State for Hydrocarbon Dew Point Calculation, Proceedings of the 2015American Gas Association Operations Conference, Grapevine, TX.10.Kunz, O., Klimeck, R., Wagner, W., and Jaeschke, M., The GERG-2004 Wide-Range Equation of State for Natural Gasesand Other Mixtures, GERG TM- 15, 2007.11.Metering Research Facility Program: Natural Gas Sample Collection and Handling-Phase II, Kelner, E., Britton, C. L.,Behring, K.A. III and Sparks, C. R., GRI Topical Report No. GRI-01/0069, Gas Technology Institute, Des Plaines, Illinois, January 2003.12.Metering Research Facility Program: Natural Gas Sample Collection and Handling-Phase III, Kelner, E., Sparks, C. R.,and Behring, K.A. III, GRI Topical Report No. GRI-01/0070, Gas Technology Institute, Des Plaines, Illinois, August 2002.13.GPA Standard 2172, Calculation of Gross Heating Value, Relative Density, Compressibility and Theoretical HydrocarbonLiquid Content for Natural Gas Mixtures for Custody Transfer, Third Edition, Gas Processors Association, Tulsa, Oklahoma, 2014.14.Title 43, Code of Federal Regulations, Part 3170, Onshore Oil and Gas Production, Subpart 3175, Measurement of Gas,November 17, 2016.。
Cheng Hao,2009,Lithos
Transitional time of oceanic to continental subduction in the Dabie orogen:Constraints from U –Pb,Lu –Hf,Sm –Nd and Ar –Ar multichronometric datingHao Cheng a ,b ,⁎,Robert L.King c ,Eizo Nakamura b ,Jeffrey D.Vervoort c ,Yong-Fei Zheng d ,Tsutomu Ota b ,Yuan-Bao Wu e ,Katsura Kobayashi b ,Zu-Yi Zhou aaState Key Laboratory of Marine Geology,Tongji University,Shanghai 200092,ChinabInstitute for Study of the Earth's Interior,Okayama University at Misasa,Tottori 682-0193,Japan cSchool of Earth and Environmental Sciences,Washington State University,Pullman,Washington 99164,USA dCAS Key Laboratory of Crust-Mantle Materials and Environments,School of Earth and Space Sciences,University of Science and Technology of China,Hefei 230026,China eState Key Laboratory of Geological Processes and Mineral Resources,Faculty of Earth Sciences,China University of Geosciences,Wuhan 430074,Chinaa b s t r a c ta r t i c l e i n f o Article history:Received 22August 2008Accepted 9January 2009Available online 8February 2009Keywords:Continental subduction Dabie EclogiteGeochronologyOceanic subduction Tectonic transitionWe investigated the oceanic-type Xiongdian high-pressure eclogites in the western part of the Dabie orogen with combined U –Pb,Lu –Hf,Sm –Nd and Ar –Ar geochronology.Three groups of weighted-mean 206Pb/238U ages at 315±5,373±4and 422±7Ma are largely consistent with previous dates.In contrast,Lu –Hf and Sm –Nd isochron dates yield identical ages of 268.9±6.9and 271.3±5.3Ma.Phengite and amphibole Ar –Ar total fusion analyses give Neoproterozoic apparent ages,which are geologically meaningless due to the presence of excess 40Ar.Plagioclase inclusions in zircon cores suggest that the Silurian ages likely represent protolith ages,whereas the Carboniferous ages correspond to prograde metamorphism,based on the compositions of garnet inclusions.Despite weakly-preserved prograde major-and trace element zoning in garnet,a combined textural and compositional study reveals that the consistent Lu –Hf and Sm –Nd ages of ca.270Ma record a later event of garnet growth and thus mark the termination of high-pressure eclogite –facies metamorphism.The new U –Pb,Lu –Hf and Sm –Nd ages suggest a model of continuous processes from oceanic to continental subduction,pointing to the onset of prograde metamorphism prior to ca.315Ma for the subduction of oceanic crust,while the peak eclogite –facies metamorphic episode is constrained to between ca.315and 270Ma.Thus,the initiation of continental subduction is not earlier than ca.270Ma.©2009Elsevier B.V.All rights reserved.1.IntroductionSubduction zones are essential to the dynamic evolution of the earth's surface due to plate tectonics.Subduction of oceanic and continental crust eventually leads to closure of backarc basins and arc-continent and continent-continent collisions (O'Brien,2001;Ernst,2005;Zheng et al.,2008),forming various types of high-pressure (HP)and ultrahigh-pressure (UHP)metamorphic rocks.Subduction of oceanic lithosphere causes a complex continuum of diagenetic and metamorphic reactions;many kilometres of oceanic lithosphere are ultimately consumed prior to the subsequent continental slab subduction and collision.Subducted continental slabs that detach from the oceanic lithosphere that was dragging them into the mantle are expected to rapidly rise to Moho depths because of their positive buoyancy.Thus,studying subducted oceanic crust in subduction zones can provide clues to the incorporation rate of supercrustal materialinto the mantle and can shed light on the initiation of successive continental subduction.Determining a geochronological framework for determining the sequence and duration of oceanic to continental subduction and HP and UHP metamorphism plays an essential role in this respect.Zircon has long been recognized as a promising geochronometer of the U –Pb decay system because of its refractory nature,commonly preserved growth zones and mineral inclusions within a single grain.Recent developments in analytical techniques allow us to unravel a wealth of information contained in zircons with respect to their growth history and thus the prograde and retrograde metamorphic evolution of the host rock (Gebauer,1996;Wu et al.,2006;Zheng et al.,2007).The Lu –Hf garnet technique has been applied to constrain the prograde and high-temperature histories of metamorphic belts (e.g.,Duchêne et al.,1997;Blichert-Toft and Frei,2001;Anczkiewicz et al.,2004,2007;Lagos et al.,2007;Kylander-Clark et al.,2007;Cheng et al.,2008a )because of its high closure temperature (Dodson,1973;Scherer et al.,2000)and the fact that garnet strongly partitions Lu over Hf,resulting in a high parent/daughter ratio (Otamendi et al.,2002).Combined with Sm –Nd age determination,the Lu –Hf garnet geochronometer can potentially be used to estimate the duration ofLithos 110(2009)327–342⁎Corresponding author.State Key Laboratory of Marine Geology,Tongji University,Shanghai 200092,China.Tel.:+862165982358;fax:+862165984906.E-mail address:chenghao@ (H.Cheng).0024-4937/$–see front matter ©2009Elsevier B.V.All rights reserved.doi:10.1016/j.lithos.2009.01.013Contents lists available at ScienceDirectLithosj ou r n a l h o m e pa g e :ww w.e l s ev i e r.c o m/l o c a t e /l i t h o sFig.1.Simpli fied geologic map of the Huwan mélange area (b)in southern Dabie orogen (a),modi fied after Ye et al.(1993)and Liu et al.(2004b),showing the sample localities for the Xiongdian eclogite.References:asterisk,this study;[1],Ratschbacher et al.(2006);[2],Jahn et al.(2005);[3],Liu et al.(2004a);[4],Eide et al.(1994);[5],Webb et al.(1999);[6],Xu et al.(2000);[7],Ye et al.(1993);[8],Sun et al.(2002);[9],Jian et al.(1997);[10],Jian et al.(2000);[11],Gao et al.(2002);[12],Li et al.(2001);[13],Wu et al.(2008).amp —amphibole;brs —barroisite;phen —phengite;zrn —zircon.328H.Cheng et al./Lithos 110(2009)327–342garnet growth,which either reflects early prograde metamorphism (Lapen et al.,2003),exhumation(Cheng et al.,2009)or a particular garnet growth stage(Skora et al.,2006).Dating the exhumation of high-pressure(HP)and ultra-high-pressure(UHP)metamorphic rocks by conventional step-heating Ar–Ar technique was largely hampered and discredited due to the presence of excess/inherited argon(Li et al.,1994;Kelley,2002).However,the Ar–Ar geochron-ometer remains irreplaceable in constraining the exhumation of HP/ UHP metamorphic rocks because of its intermediate closure tempera-ture.Nevertheless,timing must be integrated with textures and petrology in order to quantify the dynamics of geological processes, whichever geochronological method is used.During the past two decades,considerable progress has been made in constraining the prograde metamorphism and exhumation of HP/ UHP metamorphism of the Dabie–Sulu orogen by a variety of geochronological methods,indicating a Triassic collision between the South China and North China Blocks(e.g.,Eide et al.,1994;Ames et al., 1996;Rowley et al.,1997;Hacker et al.,1998;Li et al.,2000,2004; Zheng et al.,2004).The initiation of continental subduction is pinned to ca.245Ma(Hacker et al.,2006;Liu et al.,2006a;Wu et al.,2006; Cheng et al.,2008a),but the exact time is poorly constrained.On the other hand,thefingerprints of early continental subduction may not be preserved in continental-type metamorphic rocks due to the succes-sive high-temperature prograde and retrograde overprints.Alterna-tively,the timing of initiation of continental subduction subsequent to the termination of oceanic subduction may be registered in the HP/ UHP eclogites,whose protoliths are of oceanic origin.Currently,the only outcropping candidate is the Xiongdian HP eclogite in the western part of the Dabie orogen(Li et al.,2001;Fu et al.,2002).However,U–Pb zircon ages ranging from216±4to449±14Ma have been obtained for the Xiongdian eclogite(Jian et al.,1997;Sun et al.,2002;Gao et al., 2002);the geological significance of this age spread is controversial. Efforts to clarify the geochronological evolution of the Xiongdian eclogite were hampered by a much older Sm–Nd garnet-whole-rock isochron of533±13Ma(Ye et al.,1993)and the fact that further Sm–Nd and Rb–Sr analyses failed to produce mineral isochrons(Li et al., 2001;Jahn et al.,2005),although oxygen isotopic equilibrium was largely attained(Jahn et al.,2005).Here,we present a combined U–Pb,Lu–Hf,Sm–Nd,Ar–Ar and oxygen multi-isotopic and mineral chemical study of the Xiongdian eclogite.The differences in these systems,in conjunction with chemical profiles in garnet porphyroblasts and zircons,provide a window into the time-scales of the oceanic subduction and sub-sequent exhumation.2.Geochronological background and sample descriptionsThe Qinling–Dabie–Sulu orogen in east-central China marks the junction between the North and South China Blocks(Cong,1996; Zheng et al.,2005).The western part of the Dabie orogen,usually termed the West Dabie and sometimes the Hong'an terrane,is separated from the Tongbaishan in the west by the Dawu Fault and from the East Dabie by the Shangma fault in the east(Fig.1a).It contains a progressive sequence of metamorphic zones characterized by increasing metamorphic grade,from transitional blueschist–greenschist in the south,through epidote–amphibolite and quartz eclogite,to coesite eclogite in the north(e.g.,Zhou et al.,1993;Hacker et al.,1998;Liu et al.,2004b,2006b).The Xiongdian eclogites crop out in the northwestern corner of the West Dabie,in the Xiongdian mélange within the Huwan mélange after the definition of Ratschba-cher et al.(2006),in analogy to the terms of the Sujiahe mélange(Jian et al.,1997)and Huwan shear zone(Sun et al.,2002).The Huwan mélange consists of eclogite,gabbro,amphibolite,marble,and quartzite.The eclogitic metamorphic peak for the Xiongdian eclogite is estimated at600–730°C,1.4–1.9GPa(Fu et al.,2002),550–570°C,∼2.1GPa(Liu et al.,2004b)and540–600°C,∼2.0GPa(Ratschbacher et al.,2006),followed by retrogression at530–685°C and∼0.6GPa (Fu et al.,2002).Except for the Xiongdian eclogite,consistent Triassic metamorphic ages have been obtained for other eclogites across the West Dabie (Webb et al.,1999;Sun et al.,2002;Liu et al.,2004a;Wu et al.,2008). This indicates that West Dabie is largely a coherent part of an HP–UHP belt elsewhere in the Dabie–Sulu orogenic belt.Geochronological debate is limited to the Xiongdian eclogite(Fig.1b).U–Pb zircon ages ranging from ca.216to ca.449Ma have been obtained for the Xiongdian eclogite.Jian et al.(1997)reported ca.400,ca.373and 301±0.6Ma ages by ID–TIMS method.Weighted-mean SHRIMP ages range from335±2to424±5Ma(Jian et al.,2000).The Silurian U–Pb zircon ages were interpreted as the age of the protolith,while the Carboniferous ages mark high-pressure metamorphism(Jian et al., 1997,2000).Weighted-mean206Pb/238U SHRIMP U–Pb zircons ages of 433±9,367±10and398±5Ma were interpreted as the protolith age,while323±7and312±5Ma likely date the high-pressure metamorphism(Sun et al.,2002).A Triassic age of216±4Ma together with449±14and307±14Ma weighted-mean206Pb/238U SHRIMP U–Pb zircon ages appear to argue for the involvement of the Triassic subduction in the Xiongdian eclogite(Gao et al.,2002).A garnet-whole-rock Sm–Nd isochron of533±13Ma(Ye et al.,1993)was interpreted to reflect the high-pressure metamorphism age.Several Table1Chemical compositions of the Xiongdian eclogite from the western Dabie.Sample number DB17DB18(Major oxides in%)SiO254.5452.45 TiO20.370.43 Al2O314.6212.35 Fe2O38.7710.15 MnO0.150.16 MgO 6.669.91 CaO10.3510.26 Na2O 2.88 2.65 K2O0.600.28 P2O50.060.05 Cr2O3⁎6601118 NiO⁎137247 L.O.I0.87 1.28 Total99.95100.11 (Trace elements in ppm)Li27.627.0 Be0.560.47 Rb9.7813.8 Sr178130Y12.612.7 Cs0.89 3.67 Ba86552.4 La 2.21 1.77 Ce 5.97 5.12 Pr0.880.80 Nd 4.35 4.10 Sm 1.25 1.26 Eu0.470.39 Gd 1.53 1.52 Tb0.280.29 Dy 1.83 1.91 Ho0.410.42 Er 1.14 1.19 Tm0.190.19 Yb 1.31 1.34 Lu0.200.20 Pb 6.44 1.85 Th0.050.07 U0.110.06 Zr28.828.2 Nb 1.19 1.77 Hf0.870.88 Ta0.050.08⁎In ppm.329H.Cheng et al./Lithos110(2009)327–342Sm –Nd and Rb –Sr analyses failed to produces isochrons (Li et al.,2001;Jahn et al.,2005),which was believed to be due to unequilibrated isotopic systems despite the fact that oxygen isotopic equilibrium was largely attained (Jahn et al.,2005).Phengite 40Ar/39Ar ages of ca.430–350Ma have been explained as the retrograde metamorphic age (Xu et al.,2000).The 310±3Ma phengite 40Ar/39Ar age (Webb et al.,1999)is likely geologically meaningless due to the concave-upward age spectrum,indicating the presence of excess argon.Collectively,existing geochronology provides an apparently con flicting picture for the Xiongdian eclogites.The timing of the oceanic crust subduction and exhumation essentially remains to be resolved.The two eclogites examined in this study were selected based on their mineral assemblages,inclusion types and geological context (Fig.1).The one (DB17)from the east bank of the river to the east of Xiongdian village is a coarse-grained and strongly foliated banded eclogite,composed mainly of garnet,omphacite and phengite.A second (DB18)eclogite was sampled about 50m to the north of DB17and is strongly foliated with a similar mineralogy assemblage but smaller garnet grains.3.MethodsSample preparation,mineral separation and chemical procedures for isotope analysis,instrumentation and standard reference materials used to determine whole rock and bulk mineral compositions,in situ major and trace element analyses (Institute for Study of the Earth's Interior,Okayama University at Misasa,Japan),zircon U –Pb isotope and trace element analyses (China University of Geosciences in Wuhan),Lu –Hf and Sm –Nd isotope analyses (Washington State University),Ar –Ar isotope analyses (Guangzhou Institute of Geo-chemistry,Chinese Academy of Sciences)and oxygen isotope analyses (University of Science and Technology of China)are described in the Appendix .4.Results4.1.Bulk chemical compositionThe Xiongdian eclogites are mainly of basaltic composition,but they show a wide range of major and trace element abundances.Despite the high SiO 2(52–58%)and low TiO 2(0.32–0.43%)contents,Fig.2.Whole rock chemical analysis data.(a)Chondrite-normalized REE distribution patterns of the Xiongdian eclogites.(b)Primitive-mantle-normalized spidergrams of the Xiongdianeclogites.Fig.3.Backscattered-electron images and rim-to-rim major-element compositional zoning pro files of representative garnets in the matrix and as inclusions in zircon.Amp —amphibole;Ap —apatite;Cal —calcite;Cpx —clinopyroxene;Zo —zoisite;Phen —phengite;Omp —omphacite;Qtz —quartz;Zrn —zircon.330H.Cheng et al./Lithos 110(2009)327–342they have MgO=5.1–9.9%,Cr=430–1118ppm,Ni=88–247ppm (Table 1;Li et al.,2001;Fu et al.,2002;Jahn et al.,2005).In contrast to existing LREE-enriched chondritic REE patterns,our samples have rather flat REE patterns around ten times more chondritic abundances with small,both negative and positive Eu anomalies (Fig.2a).Rubidium is depleted and Sr displays enrichment with respect to Ce.Both negative and no Nb anomalies relative to La were observed (Fig.2b).The N-MORB-normalized value of Th is around 0.5,lower than previous reported values of up to 25(Li et al.,2001).4.2.Petrography and mineral compositionThe Xiongdian eclogites occur as thin layers intercalated with dolomite –plagioclase gneiss and phengite –quartz schist (Fu et al.,2002),mainly consisting of garnet,omphacite,epidote (clinozoisite),phengite and minor amphibole,quartz and kyanite (Fig.3).Zircons were observed both as inclusions in garnet porphyroblasts and in the matrix.The samples have similar mineral assemblages,but differ in modal compositions.Omphacite (X Jd =0.46–0.48)is unzoned.Phengite has 3.30–3.32Si apfu and ∼0.4wt.%TiO 2.Garnets range in size from 0.5to 5mm in diameter,either as porphyroblasts or as coalesced polycrystals,mostly with idioblastic shapes with inclusions of quartz,calcite,apatite and omphacite (Fig.3).Garnet is largely homogeneous (Prp 24–25Alm 49–50Grs 24–25Sps 1.5–1.9),but shows a slightly Mn-enriched core (Fig.3d;Table 2).HREEs in large garnet porphyroblasts,such as Yb and Lu,display weak but continuous decreases in concentration from core to rim (Fig.4a),mimicking the MnO zoning pattern,which could be explained by their high af finity for garnet and likely arises from an overall Rayleigh distillation process during early garnet growth (Hollister,1966;Otamendi et al.,2002).However,the limited variation in MREE concentrations,such as Sm and Nd,in garnet with respect to the weak zoning in HREE (Fig.4a)might be explained by growth in an environment where MREEs are not limited and continuously supplied by the breakdown of other phases.Hafnium has a fairly flat pro file (Table 3),re flecting its incompatible character in garnet and absence of Hf-competing reactions involved in garnet growth.Two distinct domains can be de fined in the large garnet porphyroblasts based on the chemical zoning and the abundance of inclusions.These zones are an inclusion-rich core with richer Mn and HREE and an inclusion-free rim with poorer Mn and HREE (Fig.3d).The inclusion-free rim for individual garnet has a rather similar width of 200–250μm (Fig.3).Although concentrations of Nd (0.22–0.41ppm)and Sm (0.33–0.48ppm)vary within single garnet grains,the Sm/Nd ratios (0.8–2.2)are consistentTable 2Representative major-element data of the garnets,omphacites,phengites,amphiboles and zoisites.(wt.%)Grt Omp RimCore Inclusions-in-zircon Rim Core SiO 238.6838.6438.6638.5338.6538.6637.8637.7555.9356.1256.1356.20TiO 20.050.060.050.050.050.050.050.080.120.110.110.11Al 2O 321.9221.9422.0721.9921.9921.8421.6821.8611.2611.2211.3311.26FeO ⁎22.9823.0523.0623.1623.0523.1124.4224.33 4.25 4.23 4.32 4.27MnO 0.680.720.790.880.750.680.990.930.030.020.030.02MgO 6.37 6.38 6.28 6.31 6.36 6.35 4.23 4.748.158.027.968.13CaO 9.108.949.028.929.038.9910.579.5013.2213.3613.3213.34Na 2O 0.030.030.030.030.030.030.020.01 6.65 6.41 6.39 6.42K 2O 0.000.000.000.000.000.000.000.000.000.000.000.00Total 99.8099.7799.9699.8799.9199.7199.8299.2199.6099.6099.7099.87O.N.12121212121212126666Si 2.986 2.984 2.981 2.975 2.980 2.988 2.958 2.962 1.996 2.010 2.010 2.007Al 1.994 1.997 2.006 2.001 1.999 1.990 1.997 2.0210.4740.4730.4780.474Ti 0.0030.0030.0030.0030.0030.0030.0030.0050.0030.0030.0030.003Fe 2+ 1.486 1.491 1.489 1.499 1.489 1.496 1.596 1.5990.1270.1270.1290.128Mn 0.0440.0470.0520.0580.0490.0440.0660.0620.0010.0010.0010.001Mg 0.7330.7350.7220.7260.7310.7320.4930.5540.4340.4280.4250.433Ca 0.7530.7400.7450.7380.7460.7440.8850.7980.5060.5130.5110.511Na 0.0040.0050.0050.0050.0050.0050.0030.0020.4600.4450.4430.445K0.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.000Phn Amp Zo RimCore Rim Core Mantle Core SiO 248.8649.0949.3349.0147.0847.0746.7246.7539.0538.9239.0239.02TiO 20.400.410.410.400.220.220.220.220.130.130.130.12Al 2O 329.0328.6829.0129.1912.6612.8112.5812.6228.5528.2128.7328.62FeO ⁎ 1.99 1.99 2.00 1.9711.6011.4811.4611.36 6.01 6.01 6.03 6.07MnO 0.000.000.000.010.100.090.090.090.050.050.060.05MgO 2.79 2.77 2.78 2.8012.2012.4712.4412.300.070.060.070.07CaO 0.010.010.010.019.9710.0910.0710.1024.1023.8624.1324.14Na 2O 0.930.920.920.91 2.79 2.77 2.82 2.830.000.000.000.00K 2O 10.009.919.819.780.480.470.470.470.000.000.000.00Total 94.0293.7894.2894.0997.0997.4996.8896.7697.9697.2498.1698.09O.N.111111112323232312.512.512.512.5Si 3.302 3.323 3.318 3.304 6.831 6.800 6.799 6.809 3.008 3.019 3.000 3.003Al 2.313 2.288 2.300 2.319 2.164 2.182 2.158 2.167 2.592 2.579 2.603 2.596Ti 0.0200.0210.0210.0200.0240.0240.0240.0240.0070.0070.0070.007Fe 2+0.1120.1130.1130.111 1.407 1.387 1.394 1.3830.3870.3900.3880.390Mn 0.0000.0000.0000.0000.0120.0120.0120.0120.0040.0040.0040.004Mg 0.2820.2800.2790.282 2.639 2.686 2.699 2.6700.0070.0070.0070.008Ca 0.0010.0010.0010.001 1.550 1.562 1.570 1.577 1.989 1.983 1.988 1.990Na 0.1220.1210.1200.1190.7840.7770.7950.7980.0000.0000.0000.000K0.8620.8550.8420.8410.0890.0870.0880.0880.0000.0000.0000.000⁎Total iron;concentrations reported as wt.%.331H.Cheng et al./Lithos 110(2009)327–342with those obtained by ID-MC-ICPMS (1.9–2.4)within error (Fig.5a),indicating that the Nd isotopic analyses in this study are essentially unaffected by MREE-rich inclusions,likely due to ef ficient mineral picking and/or concentrated H 2SO 4pre-leaching.The consistent Hf concentrations of 0.10–0.13ppm within single grains with those (0.11–0.13ppm)by ID-MC-ICPMS indicates the Hf-rich phases were essentially removed during digestion (Fig.5b).The overall Lu concentration slightly skews towards the garnet rim because of the weak zoning pattern and the spherical geometry effect,i.e.,the outershells dominate the volume of Lu (Cheng et al.,2008a ).The 0.90–0.93ppm Lu contents by ID-MC-ICPMS apparently resemble those of the garnet rim,which could be readily explained by the spherical geometry effect.However,we interpret this with caution because individual garnet porphyroblasts could have different zoning patterns and the individual Lu pro file might not be representative of the population of garnet grains,although the chemical zoning center (nucleation site)coincides with the geometric center (Fig.3d),suggesting asymmetric garnet growth.In addition,biased mineral hand-picking should be considered (Cheng et al.,2008a,b ).Moreover,since the thin-section preparation method for this study cannot ensure that the real center of the garnet was exposed,the observed zoning here likely only represents a minimum zoning of particular garnet porphyroblasts.4.3.Estimation of P –T conditionsMetamorphic peak P –T conditions of 2.2GPa and 620°C for the DB17Xiongdian eclogite (Fig.6)are evaluated on the basis of recent cali-brations of the assemblage garnet+omphacite+phengite+kyanite+quartz,according to the dataset of Holland and Powell (1998).Higher P –T values of 2.4GPa and 650°C are calculated with the calibrations of Krogh Ravna and Terry (2004).While a temperature of 620±29°C is estimated by quartz –garnet O isotope thermometer (Zheng,1993),Ti-in-zircon thermometer (Watson et al.,2006;Ferry and Watson,2007)gives similar value of 695±22°C.Zr-in-rutile thermometer (Watson et al.,2006;Ferry and Watson,2007)yields a lower value of 634–652°C and a similar temperature of 683–701°C (Fig.6)when using the pressure-dependent calibration of Tomkins et al.(2007)at 2.2GPa.Calibration 1uses updated versions of the thermodynamic dataset and activity models in the programs THERMOCALC3.26and AX (Holland,Powell,1998;latest updated dataset;Powell et al.,1998)by using an avPT calculation in the simpli fied model system NCKFMASH with excess SiO 2and H 2O.Calibration 2uses thermobarometry based on the database of Holland and Powell (1998)and activity models for garnet (Ganguly et al.,1996),clinopyroxene (Holland and Powell,1990)and phengite (Holland and Powell,1998).Analyses of garnet,omphacite and phengite (Table 2)were processed according to the two calibrations.Calibration 3uses mineral O isotope compositions (Table 4)to estimate temperature based on the quartz –garnet O isotope thermometer (Zheng,1993).Calibrations 4and 5use Ti contents in zircon by LA-ICPMS and Zr concentration of rutile by SIMS (Table 5)to temperature estimations based on the Ti-in-zircon and Zr-in-rutile thermometers,respectively (Watson et al.,2006;Ferry and Watson,2007;Tomkins et al.,2007).The assemblage of garnet –omphacite –kyanite –phengite –quartz is representative of metamorphic peak conditions of theXiongdianFig.4.Chondrite-normalized REE patterns (Sun and McDonough,1989)of zircons,garnets and omphacite from Xiongdian eclogite (a)and REE distribution patterns between zircon and garnet (b).The equilibrium D REE(Zrn/Grt)values of Rubatto (2002),Whitehouse and Platt (2003)and Rubatto and Hermann (2007)are presented for comparison.Table 3SIMS Sm,Nd,Hf and Lu concentration pro files of the garnets in Figs.4and 5.(ppm)RimCore Cpx Li 0.93 1.140.880.840.890.980.750.520.990.580.690.870.670.7522.1Sr 0.100.130.120.120.100.100.100.120.110.120.130.100.110.1033.5Y 45.646.846.647.346.447.148.350.052.053.553.155.354.657.80.92Hf 0.110.130.120.120.110.110.120.120.120.100.110.100.100.100.41La 0.010.020.020.010.000.000.010.010.010.010.010.010.020.010.02Ce 0.040.050.050.060.050.040.040.040.050.030.040.040.050.030.12Pr 0.010.020.030.020.020.020.020.020.020.020.030.020.020.020.03Nd 0.390.330.280.380.350.270.220.280.340.310.270.410.280.260.36Sm 0.450.360.380.440.470.410.480.450.450.410.340.330.420.410.31Eu 0.270.270.270.280.300.240.280.280.250.300.290.240.250.220.22Gd 1.85 1.96 1.75 1.80 1.85 1.78 1.85 1.84 1.93 1.82 1.57 1.92 1.69 1.530.65Dy 5.68 5.86 5.58 6.18 5.87 5.84 5.79 6.19 6.46 6.40 5.50 6.91 6.09 6.400.26Er 3.74 4.13 4.04 4.25 4.23 4.16 3.76 4.15 4.65 4.99 4.53 4.98 4.63 5.200.06Yb 4.10 4.18 4.01 3.86 4.23 4.11 4.49 4.34 4.97 5.19 5.19 5.65 5.10 5.690.12Lu0.900.910.880.840.840.891.131.151.281.261.261.331.321.420.01332H.Cheng et al./Lithos 110(2009)327–342eclogite.A partly-calibrated thermobarometer is de fined by the three reactions of 3Celadonite +1Pyrope +2Grossular =3Muscovite +6Diopside,2Kyanite+3Diopside =1Pyrope +1Grossular +2Quartz,and 3Celadonite +4Kyanite=3Muscovite +1Pyrope +4Quartz.An intersection point of 2.2GPa and 620°C is de fined and therefore independent of commonly-used Fe –Mg exchange thermometers.This offers an advantage with regards to garnet –clinopyroxene,which is prone to retrograde reactions and problems stemming from ferric iron estimation of omphacite (Li et al.,2005).Results are plotted according to the calibrations mentioned above.The three reactions and intersection points are shown according to programs of calibrations 1–5in Fig.6.4.4.Oxygen isotopic dataThe O isotope compositions of minerals for the two eclogites are presented in Table 4.When paired with quartz for isotope geothermo-metry,garnet,omphacite,phengite,kyanite,zoisite and amphibole yield temperatures of 620±29,563±35,567±43,508±31,404±28and 685±39°C for eclogite DB17,respectively.Because these temperatures are concordant with rates of O diffusion and thus closure temperatures in the mineral assemblage garnet +omphacite +kyanite+phengite+quartz (Zheng and Fu,1998),representative of metamorphic peak conditions,a continuous resetting of O isotopes in the different mineral-pair systems is evident during cooling (Giletti,1986;Eiler et al.,1993;Chen et al.,2007).Quartz –garnet pairs from eclogite DB17give temperatures of 620±29°C,which are consistent with those calibrated by the THERMOCALCmethod,indicating that O isotope equilibrium was achieved and preserved during eclogite –facies recrystallization (Fig.7a).This is also evidenced by the apparent equilibrium fractionation between garnet and omphacite (Fig.7b).In contrast,equilibrium fractionation was not attained between garnets and omphacites in eclogite DB18.The calculated quartz –amphibole pair temperature of 685±39°C is distinctly higher than the 508±31°C from the quartz –zoisite pair.Because oxygen diffusion in amphibole is faster than in zoisite and kyanite (Zheng and Fu,1998),amphibole exchanges oxygen isotopes with water faster than zoisite during retrogression.Consequently,the O isotope temperature increases for the quartz –amphibole pair,whereas the quartz –zoisite temperature decreases relative to the formation temperature.In this regard,the retrograde metamorphism of amphibolite –facies should take place at a temperature between ∼685and ∼508°C.On the other hand,the low quartz –kyanite pair temperature (404±28°C)could be interpreted as a result of in fluence by retrogressive metamorphism without a clear geologicalmeaning.Fig.5.Sm/Nd versus Nd and Lu/Hf versus Hf plots for garnet and whole rock.ID:data obtained by the isotope dilution method using MC-ICPMS.IMS:data obtained by ion microprobe.bombWR —whole rock by bomb-digestion,savWR —whole rock by Savillex-digestion.Error bars for both IMS and ID methods are signi ficantly smaller than thesymbols.Fig.6.Peak P –T estimates of the Xiongdian eclogite.Reactions of py +2gr +3cel =6di +3mu;3di+2ky =py+gr +2q;and 3cel +4ky =py +3mu +4q and intersection points are plotted according to the calibrations of Holland and Powell (1998,latest updated dataset)in solid lines and Krogh Ravna and Terry (2004)in dashed lines.Coesite quartz equilibrium is also shown (Holland and Powell,1998).Abbreviations:alm —almandine,gr —grossular,py —pyrope,cel —celadonite,mu —muscovite,di —diopside,jd —jadeite,coe —coesite.Temperatures estimated by quartz –garnet oxygen isotope thermometry (Zheng,1993),Ti-in-zircon and Zr-in-rutile thermometries (Watson et al.,2006;Tomkins et al.,2007)are also shown.Table 4Oxygen isotope data of minerals for the Xiongdian eclogite.Sample number Mineral δ18O (‰)Pair Δ18O (‰)T 1(°C)T 2(°C)DB17Quartz 12.86,12.66Phengite 10.26,10.14Qtz –Phn 2.57567±43Garnet 8.83,8.85Qtz –Grt 3.93620±29605±22Omphacite 9.64,9.56Qtz –Omp 3.17563±35574±28Zoisite 9.31,9.43Qtz –Zo 3.40508±31494±21Amphibole 9.83,9.60Qtz –Amp 3.06685±39Kyanite 9.36,–Qtz –Ky3.41404±28WR 9.85,9.91DB18Garnet 9.74,9.59Omphacite 8.58,8.48Omp –Grt −1.14WR10.15,9.99T 1and T 2were calculated based on the theoretical calibrations of Zheng (1993)and Matthews (1994),respectively,with omphacite (Jd 45Di 55).Uncertainty on the temperature is derived from error propagation of the average reproducibility of ±15‰for δ18O (‰)values in the fractionation equations.333H.Cheng et al./Lithos 110(2009)327–342。
Entropy changes in the clustering of galaxies in a
Vol.3, No.1, 65-68 (2011)doi:10.4236/ns.2011.31009Natural ScienceEntropy changes in the clustering of galaxies in an expanding universeNaseer Iqbal1,2*, Mohammad Shafi Khan1, Tabasum Masood11Department of Physics, University of Kashmir, Srinagar, India; *Corresponding Author:2Interuniversity Centre for Astronomy and Astrophysics, Pune, India.Received 19 October 2010; revised 23 November 2010; accepted 26 November 2010.ABSTRACTIn the present work the approach-thermody- namics and statistical mechanics of gravitating systems is applied to study the entropy change in gravitational clustering of galaxies in an ex-panding universe. We derive analytically the expressions for gravitational entropy in terms of temperature T and average density n of the par-ticles (galaxies) in the given phase space cell. It is found that during the initial stage of cluster-ing of galaxies, the entropy decreases and fi-nally seems to be increasing when the system attains virial equilibrium. The entropy changes are studied for different range of measuring correlation parameter b. We attempt to provide a clearer account of this phenomena. The entropy results for a system consisting of extended mass (non-point mass) particles show a similar behaviour with that of point mass particles clustering gravitationally in an expanding uni-verse.Keywords:Gravitational Clustering; Thermodynamics; Entropy; Cosmology1. INTRODUCTIONGalaxy groups and clusters are the largest known gravitationally bound objects to have arisen thus far in the process of cosmic structure formation [1]. They form the densest part of the large scale structure of the uni-verse. In models for the gravitational formation of struc-ture with cold dark matter, the smallest structures col-lapse first and eventually build the largest structures; clusters of galaxies are then formed relatively. The clus-ters themselves are often associated with larger groups called super-clusters. Clusters of galaxies are the most recent and most massive objects to have arisen in the hiearchical structure formation of the universe and the study of clusters tells one about the way galaxies form and evolve. The average density n and the temperature T of a gravitating system discuss some thermal history of cluster formation. For a better larger understanding of this thermal history it is important to study the entropy change resulting during the clustering phenomena be-cause the entropy is the quantity most directly changed by increasing or decreasing thermal energy of intraclus-ter gas. The purpose of the present paper is to show how entropy of the universe changes with time in a system of galaxies clustering under the influence of gravitational interaction.Entropy is a measure of how disorganised a system is. It forms an important part of second law of thermody-namics [2,3]. The concept of entropy is generally not well understood. For erupting stars, colloiding galaxies, collapsing black holes - the cosmos is a surprisingly or-derly place. Supermassive black holes, dark matter and stars are some of the contributors to the overall entropy of the universe. The microscopic explanation of entropy has been challenged both from the experimental and theoretical point of view [11,12]. Entropy is a mathe-matical formula. Standard calculations have shown that the entropy of our universe is dominated by black holes, whose entropy is of the order of their area in planck units [13]. An analysis by Chas Egan of the Australian National University in Canberra indicates that the col-lective entropy of all the supermassive black holes at the centers of galaxies is about 100 times higher than previ-ously calculated. Statistical entropy is logrithmic of the number of microstates consistent with the observed macroscopic properties of a system hence a measure of uncertainty about its precise state. Statistical mechanics explains entropy as the amount of uncertainty which remains about a system after its observable macroscopic properties have been taken into account. For a given set of macroscopic quantities like temperature and volume, the entropy is a function of the probability that the sys-tem is in various quantumn states. The more states avail-able to the system with higher probability, the greater theAll Rights Reserved.N. Iqbal et al. / Natural Science 3 (2011) 65-6866 disorder and thus greater the entropy [2]. In real experi-ments, it is quite difficult to measure the entropy of a system. The technique for doing so is based on the thermodynamic definition of entropy. We discuss the applicability of statistical mechanics and thermodynam-ics for gravitating systems and explain in what sense the entropy change S – S 0 shows a changing behaviour with respect to the measuring correlation parameter b = 0 – 1.2. THERMODYNAMIC DESCRIPTION OF GALAXY CLUSTERSA system of many point particles which interacts by Newtonian gravity is always unstable. The basic insta-bilities which may occur involve the overall contraction (or expansion) of the system, and the formation of clus-ters within the system. The rates and forms of these in-stabilities are governed by the distribution of kinetic and potential energy and the momentum among the particles. For example, a finite spherical system which approxi-mately satisfies the viral theorem, contracts slowlycompared to the crossing time ~ ()12G ρ- due to the evaporation of high energy particles [3] and the lack of equipartition among particles of different masses [4]. We consider here a thermodynamic description for the sys-tem (universe). The universe is considered to be an infi-nite gas in which each gas molecule is treated to be agalaxy. The gravitational force is a binary interaction and as a result a number of particles cluster together. We use the same approximation of binary interaction for our universe (system) consisting of large number of galaxies clustering together under the influence of gravitational force. It is important to mention here that the characteri-zation of this clustering is a problem of current interest. The physical validity of the application of thermody-namics in the clustering of galaxies and galaxy clusters has been discussed on the basis of N-body computer simulation results [5]. Equations of state for internal energy U and pressure P are of the form [6]:(3122NTU =-)b (1) (1NTP V=-)b (2) b defines the measuring correlation parameter and is dimensionless, given by [8]()202,23W nb Gm n T r K Tτξ∞=-=⎰,rdr (3)W is the potential energy and K the kinetic energy ofthe particles in a system. n N V = is the average num-ber density of the system of particles each of mass m, T is the temperature, V the volume, G is the universalgravitational constant. (),,n T r ξ is the two particle correlation function and r is the inter-particle distance. An overall study of (),n T r ξ has already been dis-cussed by [7]. For an ideal gas behaviour b = 0 and for non-ideal gas system b varies between 0 and 1. Previ-ously some workers [7,8] have derived b in the form of:331nT b nT ββ--=+ (4) Eq.4 indicates that b has a specific dependence on the combination 3nT -.3. ENTROPY CALCULATIONSThermodynamics and statistical mechanics have been found to be equal tools in describing entropy of a system. Thermodynamic entropy is a non-conserved state func-tion that is of great importance in science. Historically the concept of entropy evolved in order to explain why some processes are spontaneous and others are not; sys-tems tend to progress in the direction of increasing en-tropy [9]. Following statistical mechanics and the work carried out by [10], the grand canonical partition func-tion is given by()3213212,1!N N N N mkT Z T V V nT N πβ--⎛⎫⎡=+ ⎪⎣Λ⎝⎭⎤⎦(5)where N! is due to the distinguishability of particles. Λrepresents the volume of a phase space cell. N is the number of paricles (galaxies) with point mass approxi-mation. The Helmholtz free energy is given by:ln N A T Z =- (6)Thermodynamic description of entropy can be calcu-lated as:,N VA S T ∂⎛⎫=- ⎪∂⎝⎭ (7)The use of Eq.5 and Eq.6 in Eq.7 gives()3120ln ln 13S S n T b b -⎛⎫-=-- ⎪ ⎪⎝⎭- (8) where S 0 is an arbitary constant. From Eq.4 we write()31bn b T β-=- (9)Using Eq.9, Eq.8 becomes as3203ln S S b bT ⎡⎤-=-+⎢⎣⎦⎥ (10)Again from Eq.4All Rights Reserved.N. Iqbal et al. / Natural Science 3 (2011) 65-68 6767()13221n b T b β-⎡⎤=⎢⎣⎦⎥ (11)with the help of Eq.11, Eq.10 becomes as()011ln ln 1322S S n b b b ⎡-=-+-+⎡⎤⎣⎦⎢⎥⎣⎦⎤ (12) This is the expression for entropy of a system consist-ing of point mass particles, but actually galaxies have extended structures, therefore the point mass concept is only an approximation. For extended mass structures we make use of softening parameter ε whose value is taken between 0.01 and 0.05 (in the units of total radius). Following the same procedure, Eq.8 becomes as()320ln ln 13N S S N T N b Nb V εε⎡⎤-=---⎢⎥⎣⎦(13)For extended structures of galaxies, Eq.4 gets modi-fied to()()331nT R b nT R εβαεβαε--=+ (14)where α is a constant, R is the radius of a cell in a phase space in which number of particles (galaxies) is N and volume is V . The relation between b and b ε is given by: ()11b b b εαα=+- (15) b ε represents the correlation energy for extended mass particles clustering gravitationally in an expanding uni-verse. The above Eq.10 and Eq.12 take the form respec-tively as;()()3203ln 111bT b S S b b ααα⎡⎤⎢⎥-=-+⎢⎥+-+-⎢⎥⎣⎦1 (16) ()()()120113ln ln 2111b b b S S n b b ααα⎡⎤-⎡⎤⎢⎥⎣⎦-=-++⎢⎥+-+-⎢⎥⎣⎦1 (17)where2R R εεεα⎛⎫⎛⎫=⎪ ⎪⎝⎭⎝⎭(18)If ε = 0, α = 1 the entropy equations for extended mass galaxies are exactly same with that of a system of point mass galaxies approximation. Eq.10, Eq.12, Eq.16and Eq.17 are used here to study the entropy changes inthe cosmological many body problem. Various entropy change results S – S 0 for both the point mass approxima-tion and of extended mass approximation of particles (galaxies) are shown in (Figures 1and2). The resultshave been calculated analytically for different values ofFigure 1. (Color online) Comparison of isothermal entropy changes for non-point and point mass particles (galaxies) for an infinite gravitating system as a function of average relative temperature T and the parameter b . For non-point mass ε = 0.03 and R = 0.06 (left panel), ε = 0.04 and R = 0.04 (right panel).All Rights Reserved.N. Iqbal et al. / Natural Science 3 (2011) 65-68 68Figure 2. (Color online) Comparison of equi-density entropy changes for non-point and point mass particles (galaxies) for an infinite gravitating system as a function of average relative density n and the parameter b. For non-point mass ε= 0.03 and R = 0.04.R (cell size) corresponding to different values of soften-ing parameter ε. We study the variations of entropy changes S – S0with the changing parameter b for differ-ent values of n and T. Some graphical variations for S – S0with b for different values of n = 0, 1, 100 and aver-age temperature T = 1, 10 and 100 and by fixing value of cell size R = 0.04 and 0.06 are shown. The graphical analysis can be repeated for different values of R and by fixing values of εfor different sets like 0.04 and 0.05. From both the figures shown in 1 and 2, the dashed line represents variation for point mass particles and the solid line represents variation for extended (non-point mass) particles (galaxies) clustering together. It has been ob-served that the nature of the variation remains more or less same except with some minor difference.4. RESULTSThe formula for entropy calculated in this paper has provided a convenient way to study the entropy changes in gravitational galaxy clusters in an expanding universe. Gravity changes things that we have witnessed in this research. Clustering of galaxies in an expanding universe, which is like that of a self gravitating gas increases the gases volume which increases the entropy, but it also increases the potential energy and thus decreases the kinetic energy as particles must work against the attrac-tive gravitational field. So we expect expanding gases to cool down, and therefore there is a probability that the entropy has to decrease which gets confirmed from our theoretical calculations as shown in Figures 1 and 2. Entropy has remained an important contributor to our understanding in cosmology. Everything from gravita-tional clustering to supernova are contributors to entropy budget of the universe. A new calculation and study of entropy results given by Eqs.10, 12, 16 and 17 shows that the entropy of the universe decreases first with the clustering rate of the particles and then gradually in-creases as the system attains viral equilibrium. The gravitational entropy in this paper furthermore suggests that the universe is different than scientists had thought.5. ACKNOWLEDGEMENTSWe are thankful to Interuniversity centre for Astronomy and Astro-physics Pune India for providing a warm hospitality and facilities during the course of this work.REFERENCES[1]Voit, G.M. (2005) Tracing cosmic evolution with clus-ters of galaxies. Reviews of Modern Physics, 77, 207- 248.[2]Rief, F. (1965)Fundamentals of statistical and thermalphysics. McGraw-Hill, Tokyo.[3]Spitzer, L. and Saslaw, W.C. (1966) On the evolution ofgalactic nuclei. Astrophysical Journal, 143, 400-420.doi:10.1086/148523[4]Saslaw, W.C. and De Youngs, D.S. (1971) On the equi-partition in galactic nuclei and gravitating systems. As-trophysical Journal, 170, 423-429.doi:10.1086/151229[5]Itoh, M., Inagaki, S. and Saslaw, W.C. (1993) Gravita-tional clustering of galaxies. Astrophysical Journal, 403,476-496.doi:10.1086/172219[6]Hill, T.L. (1956) Statistical mechanics: Principles andstatistical applications. McGraw-Hill, New York.[7]Iqbal, N., Ahmad, F. and Khan, M.S. (2006) Gravita-tional clustering of galaxies in an expanding universe.Journal of Astronomy and Astrophysics, 27, 373-379.doi:10.1007/BF02709363[8]Saslaw, W.C. and Hamilton, A.J.S. (1984) Thermody-namics and galaxy clustering. Astrophysical Journal, 276, 13-25.doi:10.1086/161589[9]Mcquarrie, D.A. and Simon, J.D. (1997) Physical chem-istry: A molecular approach. University Science Books,Sausalito.[10]Ahmad, F, Saslaw, W.C. and Bhat, N.I. (2002) Statisticalmechanics of cosmological many body problem. Astro-physical Journal, 571, 576-584.doi:10.1086/340095[11]Freud, P.G. (1970) Physics: A Contemporary Perspective.Taylor and Francis Group.[12]Khinchin, A.I. (1949) Mathamatical Foundation of statis-tical mechanics. Dover Publications, New York.[13]Frampton, P., Stephen, D.H., Kephar, T.W. and Reeb, D.(2009) Classical Quantum Gravity. 26, 145005.doi:10.1088/0264-9381/26/14/145005All Rights Reserved.。
半径约束最小二乘圆拟合方法及其误差分析_刘珂
第17卷第5期2006年5月光电子#激光Journal of O p toelectronics#LaserV o l.17N o.5M ay2006半径约束最小二乘圆拟合方法及其误差分析*y刘珂**,周富强,张广军(北京航空航天大学仪器科学与光电工程学院,北京100083)摘要:针对基于线结构光视觉检测类圆工件三维测量中的光条圆弧特征数据所占整圆比例偏小,提出了基于半径约束最小二乘圆拟合方法。
详细地分析了样本特征数据噪声对圆心定位精度的影响,并进行了仿真实验。
实验结果表明,在光条圆弧特征数据所占整圆比例偏小的条件下,半径约束最小二乘圆拟合方法可以有效地提高圆中心定位精度。
关键词:最小二乘法;半径约束;圆拟合;线结构光;误差分析中图分类号:T P391文献标识码:A文章编号:1005-0086(2006)05-0604-04Radius C onstraint Leas-t square Circle Fitting Method and Error AnalysisLIU Ke**,ZH OU Fu-qiang,ZH ANG Guang-jun(School of Instrument Science&O pt oelectr onics Eng ineer ing,Beijing U niv ersity of A ero nautics and A s-t ronautics,Beijing100083,China)Abstract:In the process of3-D measurement of the workpiece in shape of arc with struc-tu red light vision sensor,feature data of the stru ctu red light arc is inadequ ate compared with the whole circle,which results in the location of the circle centre bein g of low prec-i sion.Leas-t squares method based on radius constraint is proposed in the paper to solve the problem.Influence of the noise in sample data the on the locating of circle centre is ana-lyzed in detail,and simulated experimen ts are implem ented.Results of experiments show that under the circumstan ces that featu re data of the structured light arc is inadequate com-pared with the whole circle,the method proposed above can improve the accuracy of circle fitting efficiently.Key words:leas-t squares m ethod;radius constrai ned;li ne structured li ght;anal ysis of error1引言各种零部件定位圆孔几何中心的定位精度对零部件的成功安装以及物体的整体定位,有着重要的意义。
数学英文论文
070451 Controlling chaos based on an adaptive nonlinear compensatingmechanism*Corresponding author,Xu Shu ,email:123456789@Abstract The control problems of chaotic systems are investigated in the presence of parametric u ncertainty and persistent external distu rbances based on nonlinear control theory. B y designing a nonlinear compensating mechanism, the system deterministic nonlinearity, parametric uncertainty and disturbance effect can be compensated effectively. The renowned chaotic Lorenz system subject to parametric variations and external disturbances is studied as an illustrative example. From Lyapu nov stability theory, sufficient conditions for the choice of control parameters are derived to guarantee chaos control. Several groups of experiments are carried out, including parameter change experiments, set-point change experiments and disturbance experiments. Simulation results indicate that the chaotic motion can be regulated not only to stead y states but also to any desired periodic orbits with great immunity to parametric variations and external distu rbances.Keywords: chaotic system, nonlinear compensating mechanism, Lorenz chaotic systemPACC: 05451. IntroductionChaotic motion, as the peculiar behavior in deterministic systems, may be undesirable in many cases, so suppressing such a phenomenon has been intensively studied in recent years. Generally speaking chaos suppression and chaos synchronization[1-4 ]are two active research fields in chaos control and are both crucial in application of chaos. In the following letters we only deal with the problem of chaos suppression and will not discuss the chaos synchronization problem.Since the early 1990s, the small time-dependent parameter perturbation was introduced by Ott,Grebogi, and Y orke to eliminate chaos,[5]many effective control methods have been reported in various scientific literatures.[1-4,6-36,38-44,46] There are two lines in these methods. One is to introduce parameter perturbations to an accessible system parameter, [5-6,8-13] the other is to introduce an additive external force to the original uncontrolled chaotic system. [14-37,39-43,47] Along the first line, when system parameters are not accessible or can not be changed easily, or the environment perturbations are not avoided, these methods fail. Recently, using additive external force to achieve chaos suppression purpose is in the ascendant. Referring to the second line of the approaches, various techniques and methods have been proposed to achieve chaos elimination, to mention only a few:(ⅰ) linear state feedback controlIn Ref.[14] a conventional feedback controller was designed to drive the chaotic Duffing equation to one of its inherent multiperiodic orbits.Recently a linear feedback control law based upon the Lyapunov–Krasovskii (LK) method was developed for the suppression of chaotic oscillations.[15]A linear state feedback controller was designed to solve the chaos control problem of a class of new chaotic system in Ref.[16].(ⅱ) structure variation control [12-16]Since Y u X proposed structure variation method for controlling chaos of Lorenz system,[17]some improved sliding-mode control strategies were*Project supported by the National Natural Science Foundation of C hina (Grant No 50376029). †Corresponding au thor. E-mail:zibotll@introduced in chaos control. In Ref.[18] the author used a newly developed sliding mode controller with a time-varying manifold dynamic to compensate the external excitation in chaotic systems. In Ref.[19] the design schemes of integration fuzzy sliding-mode control were addressed, in which the reaching law was proposed by a set of linguistic rules. A radial basis function sliding mode controller was introduced in Ref.[20] for chaos control.(ⅲ) nonlinear geometric controlNonlinear geometric control theory was introduced for chaos control in Ref.[22], in which a Lorenz system model slightly different from the original Lorenz system was studied considering only the Prandtl number variation and process noise. In Ref.[23] the state space exact linearization method was also used to stabilize the equilibrium of the Lorenz system with a controllable Rayleigh number. (ⅳ)intelligence control[24-27 ]An intelligent control method based on RBF neural network was proposed for chaos control in Ref.[24]. Liu H, Liu D and Ren H P suggested in Ref.[25] to use Least-Square Support V ector Machines to drive the chaotic system to desirable points. A switching static output-feedback fuzzy-model-based controller was studied in Ref.[27], which was capable of handling chaos.Other methods are also attentively studied such as entrainment and migration control, impulsive control method, optimal control method, stochastic control method, robust control method, adaptive control method, backstepping design method and so on. A detailed survey of recent publications on control of chaos can be referenced in Refs.[28-34] and the references therein.Among most of the existing control strategies, it is considered essentially to know the model parameters for the derivation of a controller and the control goal is often to stabilize the embedded unstable period orbits of chaotic systems or to control the system to its equilibrium points. In case of controlling the system to its equilibrium point, one general approach is to linearize the system in the given equilibrium point, then design a controller with local stability, which limits the use of the control scheme. Based on Machine Learning methods, such as neural network method[24]or support vector machine method,[25]the control performance often depends largely on the training samples, and sometimes better generalization capability can not be guaranteed.Chaos, as the special phenomenon of deterministic nonlinear system, nonlinearity is the essence. So if a nonlinear real-time compensator can eliminate the effect of the system nonlinearities, chaotic motion is expected to be suppressed. Consequently the chaotic system can be controlled to a desired state. Under the guidance of nonlinear control theory, the objective of this paper is to design a control system to drive the chaotic systems not only to steady states but also to periodic trajectories. In the next section the controller architecture is introduced. In section 3, a Lorenz system considering parametric uncertainties and external disturbances is studied as an illustrative example. Two control schemes are designed for the studied chaotic system. By constructing appropriate L yapunov functions, after rigorous analysis from L yapunov stability theory sufficient conditions for the choice of control parameters are deduced for each scheme. Then in section 4 we present the numerical simulation results to illustrate the effectiveness of the design techniques. Finally some conclusions are provided to close the text.2. Controller architectureSystem differential equation is only an approximate description of the actual plant due to various uncertainties and disturbances. Without loss of generality let us consider a nonlinear continuous dynamic system, which appears strange attractors under certain parameter conditions. With the relative degree r n(n is the dimension of the system), it can be directly described or transformed to the following normal form:121(,,)((,,)1)(,,,)(,,)r r r z z z z za z v wb z v u u d z v u u vc z v θθθθθθθθ-=⎧⎪⎪⎪=⎪=+∆+⎨⎪ ++∆-+⎪⎪ =+∆+⎪=+∆⎩ (1) 1y z =where θ is the parameter vector, θ∆ denotes parameter uncertainty, and w stands for the external disturbance, such that w M ≤with Mbeingpositive.In Eq.(1)1(,,)T r z z z = can be called external state variable vector,1(,,)T r n v v v += called internal state variable vector. As we can see from Eq.(1)(,,,,)(,,)((,,)1)d z v w u a z v w b z v uθθθθθθ+∆=+∆+ ++∆- (2)includes system nonlinearities, uncertainties, external disturbances and so on.According to the chaotic system (1), the following assumptions are introduced in order to establish the results concerned to the controller design (see more details in Ref.[38]).Assumption 1 The relative degree r of the chaotic system is finite and known.Assumption 2 The output variable y and its time derivatives i y up to order 1r -are measurable. Assumption 3 The zero dynamics of the systemis asymptotically stable, i.e.,(0,,)v c v θθ=+∆ is asymptotically stable.Assumption 4 The sign of function(,,)b z v θθ+∆is known such that it is always positive or negative.Since maybe not all the state vector is measurable, also (,,)a z v θθ+∆and (,,)b z v θθ+∆are not known, a controller with integral action is introduced to compensate theinfluenceof (,,,,)d z v w u θθ+∆. Namely,01121ˆr r u h z h z h z d------ (3) where110121112100ˆr i i i r r r r i i ii r i i d k z k k k z kz k uξξξ-+=----++-==⎧=+⎪⎪⎨⎪=----⎪⎩∑∑∑ (4)ˆdis the estimation to (,,,,)d z v w u θθ+∆. The controller parameters include ,0,,1i h i r =- and ,0,,1i k i r =- . Here011[,,,]Tr H h h h -= is Hurwitz vector, such that alleigenvalues of the polynomial121210()rr r P s s h sh s h s h --=+++++ (5)have negative real parts. The suitable positive constants ,0,,1i h i r =- can be chosen according to the expected dynamic characteristic. In most cases they are determined according to different designed requirements.Define 1((,,))r k sign b z v θμ-=, here μstands for a suitable positive constant, and the other parameters ,0,,2i k i r =- can be selected arbitrarily. After011[,,,]Tr H h h h -= is decided, we can tune ,0,,1i k i r =- toachievesatisfyingstaticperformances.Remark 1 In this section, we consider a n-dimensional nonlinear continuous dynamic system with strange attractors. By proper coordinate transformation, it can be represented to a normal form. Then a control system with a nonlinear compensator can be designed easily. In particular, the control parameters can be divided into two parts, which correspond to the dynamic characteristic and the static performance respectively (The theoretic analysis and more details about the controller can be referenced to Ref.[38]).3. Illustrative example-the Lorenz systemThe Lorenz system captures many of the features of chaotic dynamics, and many control methods have been tested on it.[17,20,22-23,27,30,32-35,42] However most of the existing methods is model-based and has not considered the influence ofpersistent external disturbances.The uncontrolled original Lorenz system can be described by112121132231233()()()()x P P x P P x w x R R x x x x w xx x b b x w =-+∆++∆+⎧⎪=+∆--+⎨⎪=-+∆+⎩ (6) where P and R are related to the Prendtl number and Rayleigh number respectively, and b is a geometric factor. P ∆, R ∆and b ∆denote the parametric variations respectively. The state variables, 1x ,2x and 3x represent measures of fluid velocity and the spatial temperature distribution in the fluid layer under gravity , and ,1,2,3i w i =represent external disturbance. In Lorenz system the desired response state variable is 1x . It is desired that 1x is regulated to 1r x , where 1r x is a given constant. In this section we consider two control schemes for system (6).3.1 Control schemes for Lorenz chaotic system3.1.1 Control scheme 1The control is acting at the right-side of the firstequation (1x), thus the controlled Lorenz system without disturbance can be depicted as1122113231231x Px Px u xRx x x x x x x bx y x =-++⎧⎪=--⎨⎪=-⎩= (7) By simple computation we know system (7) has relative degree 1 (i.e., the lowest ordertime-derivative of the output y which is directly related to the control u is 1), and can be rewritten as1122113231231z Pz Pv u vRz z v v v z v bv y z =-++⎧⎪=--⎨⎪=-⎩= (8) According to section 2, the following control strategy is introduced:01ˆu h z d=-- (9) 0120010ˆ-d k z k k z k uξξξ⎧=+⎪⎨=--⎪⎩ (10) Theorem 1 Under Assumptions 1 toAssumptions 4 there exists a constant value *0μ>, such that if *μμ>, then the closed-loop system (8), (9) and (10) is asymptotically stable.Proof Define 12d Pz Pv =-+, Eq.(8) can be easily rewritten as1211323123z d u v Rz z v v vz v bv =+⎧⎪=--⎨⎪=-⎩ (11) Substituting Eq.(9) into Eq.(11) yields101211323123ˆz h z d dv R z z v v v z v bv ⎧=-+-⎪=--⎨⎪=-⎩ (12) Computing the time derivative of d and ˆdand considering Eq.(12) yields12011132ˆ()()dPz Pv P h z d d P Rz z v v =-+ =--+- +-- (13) 0120010000100ˆ-()()ˆ=()d k z k k z k u k d u k d k z k d d k dξξξ=+ =--++ =-- - = (14)Defining ˆdd d =- , we have 011320ˆ()()dd d P h P R z P z v P v P k d=- =+- --+ (15) Then, we can obtain the following closed-loop system101211323123011320()()z h z dvRz z v v v z v bv d Ph PR z Pz v Pv P k d⎧=-+⎪=--⎪⎨=-⎪⎪=+---+⎩ (16) To stabilize the closed-loop system (16), a L yapunovfunction is defined by21()2V ςς=(17)where, ςdenotes state vector ()123,,,Tz v v d, isthe Euclidean norm. i.e.,22221231()()2V z v v dς=+++ (18) We define the following compact domain, which is constituted by all the points internal to the superball with radius .(){}2222123123,,,2U z v v d zv v dM +++≤(19)By taking the time derivative of ()V ςand replacing the system expressions, we have11223322*********01213()()(1)V z z v v v v dd h z v bv k P d R z v P R P h z d P v d P z v d ς=+++ =----++ +++-- (20) For any ()123,,,z v v d U ∈, we have: 222201230120123()()(1)V h z v b v k P dR z v PR Ph z d P v d d ς≤----+ ++++ ++ (21)Namely,12300()(1)22020V z v v dPR Ph R h R P ς⎡⎤≤- ⎣⎦++ - 0 - - 1 - 2⨯00123(1)()2Tb PR Ph P k P z v v d ⎡⎤⎢⎥⎢⎥⎢⎥⎢⎥⎢⎥⎢⎥0 ⎢⎥2⎢⎥++⎢⎥- - - +⎢⎥⎣22⎦⎡⎤⨯ ⎣⎦(22) So if the above symmetrical parameter matrix in Eq.(22) is positive definite, then V is negative and definite, which implies that system (16) is asymptotically stable based on L yapunov stability theory.By defining the principal minor determinants of symmetrical matrix in Eq.(22) as ,1,2,3,4i D i =, from the well-known Sylvester theorem it is straightforward to get the following inequations:100D h => (23)22004RD h =-> (24)23004R b D bh =-> (25)240302001()(1)(2)821[2(1)]08P M D k P D b PR Ph PR D Pb Ph R PR Ph =+-+++--+++>(26)After 0h is determined by solving Inequalities (23) to (25), undoubtedly, the Inequalities (26) can serve effectively as the constraints for the choice of 0k , i.e.20200031(1)(2)821[2(1)]8P M b PR Ph PR D Pb Ph R PR Ph k P D ++++ ++++>- (27)Here,20200*31(1)(2)821[2(1)]8P M b PR Ph PR D Pb Ph R PR Ph P D μ++++ ++++=-.Then the proof of the theorem 1 is completed. 3.1.2 Control scheme 2Adding the control signal on the secondequation (2x ), the system under control can be derived as112211323123x P x P x x R x x x x u xx x bx =-+⎧⎪=--+⎨⎪=-⎩ (28) From Eq.(28), for a target constant 11()r x t x =,then 1()0xt = , by solving the above differential equation, we get 21r r x x =. Moreover whent →∞,3r x converges to 12r x b . Since 1x and 2x havethe same equilibrium, then the measured state can also be chosen as 2x .To determine u , consider the coordinate transform:122133z x v x v x=⎧⎪=⎨⎪=⎩ and reformulate Eq.(28) into the following normal form:1223121231231zRv v v z u vPz Pv v z v bv y z =--+⎧⎪=-⎨⎪=-⎩= (29) thus the controller can be derived, which has the same expression as scheme 1.Theorem 2 Under Assumptions 1, 2, 3 and 4, there exists a constant value *0μ>, such that if *μμ>, then the closed-loop system (9), (10) and (29) is asymptotically stable.Proof In order to get compact analysis, Eq.(29) can be rewritten as12123123z d u v P z P v vz v bv =+⎧⎪=-⎨⎪=-⎩ (30) where 2231d Rv v v z =--Substituting Eq.(9) into Eq.(30),we obtain:1012123123ˆz h z d dv P z P v v z v bv ⎧=-+-⎪=-⎨⎪=-⎩ (31) Giving the following definition:ˆdd d =- (32) then we can get22323112123212301()()()()dRv v v v v z R Pz Pv Pz Pv v v z v bv h z d =--- =--- ----+ (33) 012001000ˆ-()d k z k k z k u k d u k dξξ=+ =--++ = (34) 121232123010ˆ()()()(1)dd d R Pz Pv Pz Pv v v z v bv h z k d=- =--- --+-+ (35)Thus the closed-loop system can be represented as the following compact form:1012123123121232123010()()()(1)zh z d v Pz Pv v z v bv d R Pz Pv Pz Pv v v z v bv h z k d⎧=-+⎪⎪=-⎪=-⎨⎪=---⎪⎪ --+-+⎩(36) The following quadratic L yapunov function is chosen:21()2V ςς=(37)where, ςdenotes state vector ()123,,,Tz v v d , is the Euclidean norm. i.e.,22221231()()2V z v v dς=+++ (38) We can also define the following compact domain, which is constituted by all the points internalto the super ball with radius .(){}2222123123,,,2U z v v d zv v dM =+++≤ (39)Differentiating V with respect to t and using Eq.(36) yields112233222201230011212322321312()(1)(1)()V z z v v v v dd h z P v bv k dP R h z d P z v z v v P b v v d P v d P z v d z v d ς=+++ =----+ +++++ ++--- (40)Similarly, for any ()123,,,z v v d U ∈, we have: 2222012300112133231()(1)(1)(2V h z P v b v k dPR h z d P z v v P b d P v d d M z dς≤----+ +++++ ++++ + (41)i.e.,12300()(12)22V z v v dPR M h P h P Pς⎡⎤≤- ⎣⎦+++ - -2 - 0 ⨯ 001230(12)(1)2TP b PR M h P k z v v d ⎡⎤⎢⎥⎢⎥⎢⎥ - ⎢⎥⎢⎥⎢⎥ ⎢⎥22⎢⎥⎢⎥ +++ - - -+⎢⎥⎣22⎦⎡⎤⨯ ⎣⎦(42) For brevity, Let1001(12)[(222)82(23)]P PR M h b PR P h M P b α=++++++ ++(43) 2201[(231)(13)]8P M P b b PR h α=+-+++ (44)230201(2)[2(12)8(2)(4)]PM P b P P PR M h P b Ph P α=++ +++ ++- (45)Based on Sylvester theorem the following inequations are obtained:100D h => (46)22004PD h P =-> (47)3202PMD bD =-> (48)403123(1)0D k D ααα=+---> (49)where,1,2,3,4i D i =are the principal minordeterminants of the symmetrical matrix in Eq.(42).*0k μ>*12331D αααμ++=- (50)The theorem 2 is then proved.Remark 2 In this section we give two control schemes for controlling chaos in Lorenz system. For each scheme the control depends on the observed variable only, and two control parameters are neededto be tuned, viz. 0h and 0k . According to L yapunov stability theory, after 0h is fixed, the sufficient condition for the choice of parameter 0k is also obtained.4. Simulation resultsChoosing 10P =,28R =, and 8/3b =, the uncontrolled Lorenz system exhibits chaotic behavior, as plotted in Fig.1. In simulation let the initial values of the state of thesystembe 123(0)10,(0)10,(0)10x x x ===.x1x 2x1x 3Fig.1. C haotic trajectories of Lorenz system (a) projected on12x x -plane, (b) projected on 13x x -plane4.1 Simulation results of control the trajectory to steady stateIn this section only the simulation results of control scheme 2 are depicted. The simulation results of control scheme 1 will be given in Appendix. For the first five seconds the control input is not active, at5t s =, control signal is input and the systemtrajectory is steered to set point2121(,,)(8.5,8.5,27.1)T Tr r r x x x b =, as can be seen inFig.2(a). The time history of the L yapunov function is illustrated in Fig.2(b).t/sx 1,x 2,x 3t/sL y a p u n o v f u n c t i o n VFig.2. (a) State responses under control, (b) Time history of the Lyapunov functionA. Simulation results in the presence ofparameters ’ changeAt 9t s =, system parameters are abruptly changed to 15P =,35R =, and 12/3b =. Accordingly the new equilibrium is changedto 2121(,,)(8.5,8.5,18.1)T Tr r r x x x b =. Obviously, aftervery short transient duration, system state converges to the new point, as shown in Fig.3(a). Fig.4(a) represents the evolution in time of the L yapunov function.B. Simulation results in the presence of set pointchangeAt 9t s =, the target is abruptly changedto 2121(,,)(12,12,54)T Tr r r x x x b =, then the responsesof the system state are shown in Fig.3(b). In Fig.4(b) the time history of the L yapunov function is expressed.t/sx 1,x 2,x 3t/sx 1,x 2,x 3Fig.3. State responses (a) in the presence of parameter variations, (b) in the presence of set point changet/sL y a p u n o v f u n c t i o n Vt/sL y a p u n o v f u n c t i o n VFig.4. Time history of the Lyapunov fu nction (a) in the presence of parameter variations, (b) in the presence of set point changeC. Simulation results in the presence ofdisturbanceIn Eq.(5)external periodic disturbance3cos(5),1,2,3i w t i π==is considered. The time responses of the system states are given in Fig.5. After control the steady-state phase plane trajectory describes a limit cycle, as shown in Fig.6.t/sx 1,x 2,x 3Fig.5. State responses in the presence of periodic disturbancex1x 3Fig.6. The state space trajectory at [10,12]t ∈in the presence ofperiodic disturbanceD. Simulation results in the presence of randomnoiseUnder the influence of random noise,112121132231233xPx Px x Rx x x x u xx x bx εδεδεδ=-++⎧⎪=--++⎨⎪=-+⎩ (51) where ,1,2,3i i δ= are normally distributed withmean value 0 and variance 0.5, and 5ε=. The results of the numerical simulation are depicted in Fig.7,which show that the steady responses are hardly affected by the perturbations.t/sx 1,x 2,x 3t/se 1,e 2,e 3Fig.7. Time responses in the presence of random noise (a) state responses, (b) state tracking error responses4.2 Simulation results of control the trajectory to periodic orbitIf the reference signal is periodic, then the system output will also track this signal. Figs.8(a) to (d) show time responses of 1()x t and the tracking trajectories for 3-Period and 4-period respectively.t/sx 1x1x 2t/sx 1x1x 2Fig.8. State responses and the tracking periodic orbits (a)&( b)3-period, (c)&(d) 4-periodRemark 3 The two controllers designed above solved the chaos control problems of Lorenz chaoticsystem, and the controller design method can also beextended to solve the chaos suppression problems of the whole Lorenz system family, namely the unified chaotic system.[44-46] The detail design process and close-loop system analysis can reference to the author ’s another paper.[47] In Ref.[47] according to different positions the scalar control input added,three controllers are designed to reject the chaotic behaviors of the unified chaotic system. Taking the first state 1x as the system output, by transforming system equation into the normal form firstly, the relative degree r (3r ≤) of the controlled systems i s known. Then we can design the controller with the expression as Eq.(3) and Eq.(4). Three effective adaptive nonlinear compensating mechanisms are derived to compensate the chaotic system nonlinearities and external disturbances. According toL yapunov stability theory sufficient conditions for the choice of control parameters are deduced so that designers can tune the design parameters in an explicit way to obtain the required closed loop behavior. By numeric simulation, it has been shown that the designed three controllers can successfully regulate the chaotic motion of the whole family of the system to a given point or make the output state to track a given bounded signal with great robustness.5. ConclusionsIn this letter we introduce a promising tool to design control system for chaotic system subject to persistent disturbances, whose entire dynamics is assumed unknown and the state variables are not completely measurable. By integral action the nonlinearities, including system structure nonlinearity, various disturbances, are compensated successfully. It can handle, therefore, a large class of chaotic systems, which satisfy four assumptions. Taking chaotic Lorenz system as an example, it has been shown that the designed control scheme is robust in the sense that the unmeasured states, parameter uncertainties and external disturbance effects are all compensated and chaos suppression is achieved. Some advantages of this control strategy can be summarized as follows: (1) It is not limited to stabilizing the embeddedperiodic orbits and can be any desired set points and multiperiodic orbits even when the desired trajectories are not located on the embedded orbits of the chaotic system.(2) The existence of parameter uncertainty andexternal disturbance are allowed. The controller can be designed according to the nominal system.(3) The dynamic characteristics of the controlledsystems are approximately linear and the transient responses can be regulated by the designer through controllerparameters ,0,,1i h i r =- .(4) From L yapunov stability theory sufficientconditions for the choice of control parameters can be derived easily.(5) The error converging speed is very fast evenwhen the initial state is far from the target one without waiting for the actual state to reach the neighborhood of the target state.AppendixSimulation results of control scheme 1.t/sx 1,x 2,x 3t/sL y a p u n o v f u n c t i o n VFig.A1. (a) State responses u nder control, (b) Time history of the Lyapunov functiont/sx 1,x 2,x 3t/sx 1,x 2,x 3Fig.A2. State responses (a) in the presence of parameter variations, (b) in the presence of set point changet/sL y a p u n o v f u n c t i o n Vt/sL y a p u n o v f u n c t i o n VFig.A3. Time history of the L yapu nov fu nction (a) in the presence of parameter variations, (b) in the presence of set point changet/sx 1,x 2,x 3Fig.A4. State responses in the presence of periodic disturbanceresponsest/sx 1,x 2,x 3Fig.A5. State responses in the presence of rand om noiset/sx 1x1x 2Fig.A6. State response and the tracking periodic orbits (4-period)References[1] Lü J H, Zhou T S, Zhang S C 2002 C haos Solitons Fractals 14 529[2] Yoshihiko Nagai, Hua X D, Lai Y C 2002 C haos Solitons Fractals 14 643[3] Li R H, Xu W , Li S 2007 C hin.phys.16 1591 [4]Xiao Y Z, Xu W 2007 C hin.phys.16 1597[5] Ott E ,Greb ogi C and Yorke J A 1990 Phys.Rev .Lett. 64 1196 [6]Yoshihiko Nagai, Hua X D, Lai Y C 1996 Phys.Rev.E 54 1190 [7] K.Pyragas, 1992 Phys. Lett. A 170 421 [8] Lima,R and Pettini,M 1990 Phys.Rev.A 41 726[9] Zhou Y F, Tse C K, Qiu S S and Chen J N 2005 C hin.phys. 14 0061[10] G .Cicog na, L.Fronzoni 1993 Phys.Rew .E 30 709 [11] Rakasekar,S. 1993 Pramana-J.Phys.41 295 [12] Gong L H 2005 Acta Phys.Sin.54 3502 (in C hinese) [13] Chen L,Wang D S 2007 Acta Phys.Sin.56 0091 (in C hinese) [14] C hen G R and Dong X N 1993 IEEE Trans.on Circuits andSystem-Ⅰ:Fundamental Theory and Applications 40 9 [15] J.L. Kuang, P.A. Meehan, A.Y.T. Leung 2006 C haos SolitonsFractals 27 1408[16] Li R H, Xu W, Li S 2006 Acta Phys.Sin.55 0598 (in C hinese) [17] Yu X 1996 Int.J.of Systems Science 27 355[18] Hsun-Heng Tsai, C hyu n-C hau Fuh and Chiang-Nan Chang2002 C haos,Solitons Fractals 14 627[19] Her-Terng Yau and C hieh-Li C hen 2006 C hao ,SolitonsFractal 30 709[20] Guo H J, Liu J H, 2004 Acta Phys.Sin.53 4080 (in C hinese) [21] Yu D C, Wu A G , Yang C P 2005 Chin.phys.14 0914 [22] C hyu n-C hau Fuh and Pi-Cheng Tu ng 1995 Phys.Rev .Lett.752952[23] Chen L Q, Liu Y Z 1998 Applied Math.Mech. 19 63[24] Liu D, R en H P, Kong Z Q 2003 Acta Phys.Sin.52 0531 (inChinese)[25] Liu H, Liu D and Ren H P 2005 Acta Phys.Sin.54 4019 (inChinese)[26] C hang W , Park JB, Joo YH, C hen GR 2002 Inform Sci 151227[27] Gao X, Liu X W 2007 Acta Phys.Sin. 56 0084 (in C hinese) [28] Chen S H, Liu J, Lu J 2002 C hin.phys.10 233 [29] Lu J H, Zhang S. 2001 Phys. Lett. A 286 145[30] Liu J, Chen S H, Xie J. 2003 C haos Solitons Fractals 15 643 [31] Wang J, Wang J, Li H Y 2005 C haos Solitons Fractals 251057[32] Wu X Q, Lu JA, C hi K. Tse, Wang J J, Liu J 2007 ChaoSolitons Fractals 31 631[33] A.L.Fradkov , R .J.Evans, 2002 Preprints of 15th IF AC W orldCongress on Automatic Control 143[34] Zhang H G 2003 C ontrol theory of chaotic systems (Shenyang:Northeastern University) P38 (in C hinese)[35] Yu-Chu Tian, Moses O.Tadé, David Levy 2002Phys.Lett.A.296 87[36] Jose A R , Gilberto E P, Hector P, 2003 Phys. Lett. A 316 196 [37] Liao X X, Yu P 2006 Chaos Solitons Fractals 29 91[38] Tornambe A, V aligi P.A 1994 Measurement, and C ontrol 116293[39] Andrew Y.T.Leung, Liu Z R 2004 Int.J.Bifurc.C haos 14 2955 [40] Qu Z L, Hu,G .,Yang,G J, Qin,G R 1995 Phys.Rev .Lett.74 1736 [41] Y ang J Z, Qu Z L, Hu G 1996 Phys.Rev.E.53 4402[42] Shyi-Kae Yang, C hieh-Li Chen, Her-Terng Yau 2002 C haosSolitons Fractals 13 767。
On the plane-wave cubic vertex
arXiv:hep-th/0402185v4 27 Sep 2005
On the plane-wave cubic vertex
James Lucietti ♭ , Sakura Sch¨ afer-Nameki ♯ and Aninda Sinha ♭
Abstract The exact bosonic Neumann matrices of the cubic vertex in plane-wave light-cone string field theory are derived using the contour integration techniques developed in our earlier paper. This simplifies the original derivation of the vertex. In particular, the Neumann matrices are written in terms of µ-deformed Gamma-functions, thus casting them into a form that elegantly generalizes the well-known flat-space solution. The asymptotics of the µ-deformed Gamma-functions allow one to determine the large-µ behaviour of the Neumann matrices including exponential corrections. We provide an explicit expression for the first exponential correction and make a conjecture for the subsequent exponential correction terms.
A self-consistent mechanics of composite materials
A SELF-CONSISTENT MECHANICS OF COMPOSITE MATERIALS
Ry R. HILL lhzpartrncnt of Applied Nuthenlutics and Theoretical Physics, University of Cambridge
difference in viewpoint, the entire analysis is found to remain strurturally close
to that for a crystal aggregate (as given in 011.cit. 1965a, §$ 3 and 4).
SUMMARY
THE WACROSCOP~C elastic nloduli of two-phase composites arc tstimated by a method that takes
account of the inhomogeneity of stress and strain in a way similar to the Hershey-Kriiner theory of crystalline aggregates. The phases may be arbitrarily neolotropic and in any concentrations, but are required to have the character of 8 matrix and cffcctivcly ellipsoidal inclusions. IMailed results arc given for an isotropic dispersion of sphcrcs.
均衡完全三部图K3(n)的线性3-荫度
均衡完全三部图K3(n)的线性3-荫度王苒群;左连翠【摘要】考虑均衡完全三部图K3(n)的线性3-荫度.利用路分解的方法给出了K3(n)的线性3-荫度la3 (K3(n))当n≡1,2,3(mod 4)时的比较紧的上界,利用线性k-荫度的基本理论分别得到了它们的下界,进而得到了特殊情况下均衡完全三部图K3(n)的线性3-荫度的确切值.【期刊名称】《天津师范大学学报(自然科学版)》【年(卷),期】2012(032)002【总页数】8页(P10-17)【关键词】线性k-森林;线性k-荫度;均衡完全三部图【作者】王苒群;左连翠【作者单位】天津师范大学数学科学学院,天津300387;天津师范大学数学科学学院,天津300387【正文语种】中文【中图分类】O157.5本研究所涉及的图都是简单图,即它们是有限的、无向的、无自环并且没有重边的图.图的一个独立集是顶点集的一个子集合,其中的顶点是两两不相邻的[1].称图G是一个m-部图,如果它的顶点集合V (G )可以划分为m个独立集,而这些独立集称为m-部图G的分裂集.一个完全m-部图G首先是一个m-部图,并且边uv∈Ε(G)的充要条件是u和v属于不同的分裂集.当m≥2时,将完全m-部图记为Κn1,n2,…,nm,其中n1,n2,…,nm分别是它的分裂集的基数.若n1=n2=…=nm=n,则称此完全m-部图为均衡完全m-部图,记为Κm(n).当m =3时,这样的图就称为均衡完全3-部图,记作Κn,n,n 或Κ3(n).图G的一个分解就是将这个图分成一系列的子图,使得图G的每条边恰出现在其中的一个子图中.如果图G有一个分解G1,G2,…,Gd,就称G1,G2,…,Gd 分解了图G,或称G能分解为G1,G2,…,Gd.线性k-森林是每一个连通分支均为长度不超过k的路的图.一个图G的线性k-荫度是将图G的边集合分解成的线性k-森林的最少数目,用lak(G)表示.图的线性k-荫度的概念首先由Habib等[2]提出.它是边着色的一种很自然的推广.很显然,一个线性1-森林是由一个匹配导出的,并且图G的线性1-荫度等于它的边色数(或称色指数),即la1(G)=χ′(G).而且,一个图G的线性k -荫度lak(G)也是一般线性荫度la(G)(或者la∞(G))的一个加细,一般的线性荫度是图G的边集合能分解成的线性森林(每个连通分支都是路的图)的最少数目,此时每个分支都是没有长度限制的路.1982年,Habib等提出了下述猜想,估计出了lak(G)的一个上界.目前为止,已有的相关结果都是支持此猜想的,尤其是对于结构特殊的图,如树[2,4,5]、立方图[6-8]、正则图[9-10]、可平面图[11]、均衡完全2-部图[12-13]和完全图[6,12,14,15]等,此猜想都是成立的,但对于一般图,此猜想尚未得到证明.假设H是连通图.图G的一个支撑子图F称为一个H-因子,如果F的每个连通分支都与H同构.如果图G可以表示为边不相交的H-因子的一个并,那么这个并就称为G的一个H-因子分解.进而,称一个图G的一个1-因子是G的一个支撑1-正则子图.若一个正则图G能分解为若干个1-因子,则称其为G的一个1-因子分解.如果一个图有一个1-因子分解,那么称这个图是可1-因子化的.设Ρλ为一条有λ个顶点的路.由Ρk-因子分解和线性(k-1)-荫度的概念可知,如果图G有一个Ρk-因子分解,那么lak-1(G)=而这就是G能分解成的Ρ 因子的个数.Yen等得到下述结论:k-【相关文献】[1] BONDY J A.Graph Theory with Applications[M].New York:MacMillan Press,1976.[2] HABIB M,PEROCHE k-arboricitélinéaire des arbres[J].Discrete Math,1983,17:307-317.[3] HABIB M,PEROCHE B.Some problems about linear arboricity[J].Discrete Math,1982,41:219-220.[4] CHANG G J.Algorithmic aspects of linear k-arboricity[J].Taiwanese J Math,1999,3:73-81.[5] CHANG G J,CHEN B L,FU H L,et al.Linear k-arboricities on trees[J].Discrete Appl Math,2000,103:281-287.[6] BERMOND J C,FIUQUET J L,HABIB M,et al.On linear k-arboricity[J].Discrete Math,1984,52:123-132.[7] JACKSON B,WORMALD N C.On the linear k-arboricity of cubic graphs[J].Discrete Math,1996,162:293-297.[8] THOMASSEN C.Two-coloring the edges of a cubic graph such that each monochromatic component is a path of length at most 5[J].Journal of Combinatorial Theory,1999,75:100-109.[9] ALDRED R E L,WORMALD N C.More on the liear k-arboricity of regular graphs [J].Austral J Combin,1998,18:97-104.[10]ALON N,TEAGUE V J,WORMALD N C.Linear arboricity and linear k-arboricity of regular graphs[J].Graphs Combin,2001,17:11-16.[11]LIH K W,TONG L D,WANG W F.The linear 2-arboricity of planar graphs[J].Graphs Combin,2003,19:241-248.[12]CHEN B L,HUANG K C.On the linear k-arboricity of Knand Kn,n[J].Discrete Math,2002,254:51-61.[13]FU H L,HUANG K C.The linear 2-arboricity of complete bipartite graphs[J].Ars Combin,1994,38:309-318.[14]CHEN B L,FU H L,HUANG K C.Decomposing graphs into forests of paths with size less than three[J].Austral J Combin,1991,3:55-73.[15]YEN C H,FU H L.Linear 2-arboricity of the complete graph[J].Taiwanese J Math,2010,14:273-286.[16]FU H L,HUANG K C,YEN C H.The linear 3-arboricity of Knand Kn,n[J].Discrete Math,2008,308:3816-3823.[17]YEN C H,FU H L.Linear 3-arboricity of the balanced complete multipartite graph [J].Appl Math,2007,50:33-46.。
科技英语写作(06)
RADIO PHYSICS LIANG YU
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RADIO PHYSICS LIANG YU
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There is a 1-in-17 chance of drawing two successive hearts (红桃) in this manner. The varieties of nonferrous (有色的) metals are nearly four times what they were. There are races (种,属) between animals large and small. Leprosy does not affect most animals the way it does humans. Aiken’s machine was limited in speed by its use of relays rather than electronic devices. Familiar to all with but the slightest exposure to scientific literature, this model shows the atom as a miniature solar system. The absence of atmosphere in space will allow the space telescope to show scientists light sources as far as 14-billion light years away, some seven times farther out than those visible to the biggest ground-based optical telescope. RADIO PHYSICS LIANG YU
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On oriented arc-coloringof subcubic graphsAlexandre PinlouAlexandre.Pinlou@labri.frLaBRI,Universit´e Bordeaux I,351,Cours de la Lib´e ration,33405Talence,FranceJanuary 17,20061IntroductionWe consider finite simple oriented graphs ,that is digraphs with no opposite arcs.For an oriented graph G ,we denote by V (G )its set of vertices and by A (G )its set of arcs.In [2],Courcelle introduced the notion of vertex-coloring of oriented graphs as follows:an ori-ented k-vertex-coloring of an oriented graph G is a mapping ϕfrom V (G )to a set of k colors such that (i )ϕ(u )=ϕ(v )whenever −→uv is an arc in G ,and (ii )ϕ(u )=ϕ(x )whenever −→uv and −→wx are two arcs in G with ϕ(v )=ϕ(w ).The oriented chromatic number of an oriented graph G ,denoted by χo (G ),is defined as the smallest k such that G admits an oriented k -vertex-coloring.Let H and H ′be two oriented graphs.A homomorphism from H to H ′is a mapping ϕfrom V (H )to V (H ′)that preserves the arcs:−−−−−→ϕ(u )ϕ(v )∈A (H ′)whenever −→uv ∈A (H ).An oriented k -vertex-coloring of G can be equivalently defined as a homomorphism ϕfrom G to H ,where H is an oriented graph of order k .The existence of such a homomorphism from G to H is denoted by G →H .The graph H will be called color-graph and its vertices will be called colors ,and we will say that G isH -colorable.The oriented chromatic number can be then equivalently defined as the smallest order of an oriented graph H such that G →H .Oriented vertex-colorings have been studied by several authors in the last past years (see e.g.[1,3,5]or [7]for an overview).One can define oriented arc-colorings of oriented graphs in a natural way by saying that,as in the undirected case,an oriented arc-coloring of an oriented graph G is an oriented vertex-coloring of the line digraph LD (G )of G (Recall that LD (G )is given by V (LD (G ))=A (G )and −→ab ∈A (LD (G ))whenever a =−→uv and b =−→vw).We will say that an oriented graph G is H-arc-colorable if there exists a homomorphism ϕfrom LD (G )to H and ϕis then an H-arc-coloring or simply an arc-coloring of G .Therefore,an oriented arc-coloring ϕof G must satisfy (i )ϕ(−→uv )=ϕ(−→vw )whenever −→uv and −→vw are two consecutive arcs in G ,and (ii )ϕ(−→vw )=ϕ(−→xy )whenever −→uv ,−→vw ,−→xy ,−→yz ∈A (G )with ϕ(−→uv )=ϕ(−→yz ).The oriented chromatic index of G ,denoted by χ′o (G ),is defined as the smallest order of an orientedgraph H such that LD (G )→H .The notion of oriented chromatic index can be extended to undirected graphs as follows.The oriented chromatic index χ′o (G )of an undirected graph G is the maximum of the oriented chromatic indexes taken over all the orientations of G (an orientation of an undirected graph G is obtained by giving one of the two possible orientations to every edge of G ).In this paper,we are interested in oriented arc-coloring of subcubic graphs,that is graphs with maximum degree at most 3.Oriented vertex-coloring of subcubic graphs has been first studied in [4]where it was proved that every oriented subcubic graph admits an oriented 16-vertex-coloring.In 1996,Sopena and Vignal improved this result:Theorem 1[6]Every oriented subcubic graph admits an oriented 11-vertex-coloring.It is not difficult to see that every oriented graph having an oriented k -vertex-coloring admits a k -arc-coloring (from a k -vertex-coloring f ,we obtain a k -arc-coloring g by setting g (−→uv )=f (u )for every arc −→uv ).Therefore,every oriented subcubic graph admits an oriented 11-arc-coloring.We improve this bound and prove the followingTheorem 2Every oriented subcubic graph admits a 7-arc-coloring.More precisely,we shall show that every oriented subcubic graph admits a homomorphism to QR 7,a tournament on 7vertices described in section 3.Note that Sopena conjectured that every oriented connected subcubic graph admits an oriented 7-vertex-coloring [4].This paper is organised as follows.In the next section,we introduce the main definitions and notation.In section 3,we described the tournament QR 7and give some properties of this graph.Finally,Section 4is dedicated to the proof of Theorem 2.2Definitions and notationIn the rest of the paper,oriented graphs will be simply called graphs .For a graph G and a vertex v of G ,we denote by d −G (v )the indegree of v ,by d +G (v )its outdegree and by d G (v )its degree.A vertex of degree k (resp.at most k ,at least k )will be called a k -vertex (resp.≤k -vertex,≥k -vertex).A sourcevertex (or simply a source )is a vertex v with d −(v )=0and a sink vertex (or simply a sink )is a vertex v with d +(v )=0.A source (resp.sink)of degree k will be called a k -source (resp.a k -sink).We denote by N +G (v ),N −G (v )and N G (v )respectively the set of successors of v ,the set of predeces-sors of v and the set of neighbors of v in G .The maximum degree and minimum degree of a graph G are respectively denoted by ∆(G )and δ(G ).We denote by −→uv the arc from u to v or simply uv whenever its orientation is not relevant (therefore uv =−→uv or uv =−→vu ).For a graph G and a vertex v of V (G ),we denote by G \v the graph obtained from G by removing v together with the set of its incident arcs;similarly,for an arc a of A (G ),G \a denotes the graph obtained from G by removing a .These two notions are extended to sets in a standard way:for a set of vertices V ′,G \V ′denotes the graph obtained from G by successively removing all vertices of V ′and their incident arcs,and for a set of arcs A ′,G \A ′denotes the graph obtained from G by removing all arcs of A ′.The drawing conventions for a configuration are the following:a vertex whose neighbors are totally specified will be black (i.e.vertex of fixed degree),whereas a vertex whose neighbors are partially specified will be white.Moreover,an edge will represent an arc with any of its two possible orientations.3Some properties of the tournament QR 7For a prime p ≡3(mod 4),the Paley tournament QR p is defined as the oriented graph whose vertices are the integers modulo p and such that −→uv is an arc if and only if v −u is a non-zero quadratic residue of p .For instance,let us consider the tournament QR 7with V (QR 7)={0,1,...,6}and −→uv ∈A (QR 7)whenever v −u ≡r (mod 7)for r ∈{1,2,4}.This graph has the two following useful properties [1]:(P 1)Every vertex of QR 7has three successors and three predecessors.(P 2)For every two distinct vertices u and v ,there exists four vertices w 1,w 2,w 3and w 4such that:•−−→uw 1∈A (QR 7)and −→vw 1∈A (QR 7);•−−→uw 2∈A (QR 7)and −→w 2v ∈A (QR 7);•−−→w 3u ∈A (QR 7)and −→w 3v ∈A (QR 7);•−−→w 4u ∈A (QR 7)and −→vw 4∈A (QR 7).4Proof of Theorem 2Let G be an oriented subcubic graph and C be a cycle in G (C is a subgraph of G ).A vertex u of C is a transitive vertex of C if d +C (u )=d −C (u )=1(therefore 2≤d G (u )≤3).A cycle C in G is a special cycle if and only if:(1)every non-transitive vertex of C is a 2-source or a 2-sink in G ;(2)C has either exactly 1transitive vertex or exactly 2transitive vertices,and in this case,bothtransitive vertices have the same orientation on C .s′3Figure1:Two special cyclesFigure1shows two special cycles;thefirst one has exactly1transitive vertex while the second has exactly2transitive vertices oriented in the same direction.Vertices s i,s′j and t k are respectively the sinks,sources,and transitive vertices of the special cycles.Remark3Every2-source(resp.2-sink)in a special cycle C is necessarily adjacent to a2-sink(resp. 2-source).This directly follows from the fact that C does not contain two transitive vertices oriented in opposite direction.We shall denote by SS G(C)the set of2-sources and2-sinks of the cycle C inG.′2223 Figure2:Graphs with a special cycleRemark4Note that a special cycle may only be connected to the rest of the graph by its transitive vertices(see Figure2for an example).A QR7-arc-coloring f of an oriented subcubic graph G is good if and only if:•for every2-source u,|C+f(u)|=1,•for every2-sink v,|C−f(v)|=1.Note that if a subcubic graph G admits a good QR7-arc-coloring,then for every2-vertex v of G, |C+f(v)|≤1and|C−f(v)|≤1.Wefirst prove the following:Theorem5Every oriented subcubic graph with no special cycle admits a good QR7-arc-coloring.We define a partial order≺on the set of all graphs.Let n2(G)be the number of≥2-vertices of G. For any two graphs G1and G2,G1≺G2if and only if at least one of the following conditions holds:•G1is a proper subgraph of G2;•n2(G1)<n2(G2).Note that this partial order is well-defined,since if G1is a proper subgraph of G2,then n2(G1)≤n2(G2).The partial order≺is thus a partial linear extension of the subgraph poset.In the rest of this section,let H a be counter-example to Theorem5which is minimal with respect to≺.We shall show in the following lemmas that H does not contain some configurations.In all the proofs which follow,we shall proceed similarly.We suppose that H contains some con-figurations and,for each of them,we consider a reduction H′of H with no special cycle such that H′≺H.Therefore,due to the minimality of H,there exists a good QR7-arc-coloring f of H′.The coloring f is a partial good QR7-arc-coloring of H,that is an arc-coloring of some subset S of A(H) and we show how to extend it to a good QR7-arc-coloring of H.This proves that H cannot contain such configurations.We will extensively use the following proposition:Proposition6Let −→G be an oriented graph which admits a good QR7-arc-coloring.Let←−G be thegraph obtained from −→G by giving to every arc its opposite direction.Then,←−G admits a good QR7-arc-coloring.Proof:Let f be a good QR7-arc-coloring of −→G.Consider the coloring f′:V(QR7)→A(←−G)definedby f′(−→uv)=6−f(−→vu).It is easy to see that for every arc−→uv∈A(QR7),we have−→xy∈A(QR7)for x=6−v and y=6−u. Moreover,the two incident arcs to a2-source(or a2-sink)will get the same color by f′since they got the same color by f.2 Therefore,when considering oriented good QR7-arc-coloring of an oriented graph G,we may assume that one arc in G has a given orientation.The following remark will be extensively used in the following lemmas:Remark7Let G be a graph with no special cycle and A⊆A(G)be an arc set.If the graph G′=G\A contains a special cycle C,then at least one of the vertices incident to A is a2-source or a2-sink in G′and belongs to V(C),since otherwise C would be a special cycle in G.Lemma 8The graph H is connected.Proof :Suppose that H =H 1⊎H 2(disjoint union).We have H 1≺H and H 2≺H .The graphs H 1and H 2contain no special cycle and then,by minimality of H ,H 1and H 2admits good QR 7-arc-colorings f 1and f 2respectively that can easily be extended to a good QR 7-arc-coloring f =f 1∪f 2of H .2Lemma 9The graph H contains no 3-source and no 3-sink.Proof :By Proposition 6,we just have to consider the 3-source case.Let u be a 3-source in H and H ′be the graph obtained from H by splitting u into three 1-vertices u 1,u 2,u 3.We have H ′≺H since n 2(H ′)=n 2(H )−1.Any good QR 7-arc-coloring of H ′is clearly a good QR 7-arc-coloring of H .2Lemma 10The graph H contains no 1-vertex.Proof :Let u 1be a 1-vertex in H ,v be its neighbor and N H (v )={u i ,1≤i ≤d H (v )}.By Proposition 6,we may assume −→u 1v ∈A (H ).We consider three subcases.1.d H (v )=1.By Lemma 8,H =−→u 1v and obviously,H admits a good QR 7-arc-coloring.2.d H (v )=2.Let H ′=H \u 1;we have H ′≺H and H ′contains no special cycle by remark 7.By minimality of H ,H ′admits a good QR 7-arc-coloring f that can easily be extended to H :if v is a 2-sink,we set f (−→u 1v )=f (−→u 2v );otherwise,we have three available colors for f (−→u 1v )by Property (P 1)3.d H (v )=3.Let H ′=H \u 1;we have H ′≺H .If H ′contains no special cycle then,by minimality of H ,H ′admits a good QR 7-arc-coloring f such that |C +f (v )|≤1.The coloring f can then be extended to H since we have three available colors to set f (−→u 1v )by property (P 1).If H ′contains a special cycle C ,v ∈C and v is a 2-source in H ′by Remark 7and Lemma9.We may assume w.l.o.g.that u 2is a 2-sink by Remark 3.Let N H (u 2)={v ,x }and H ′′=H \{−→vu 2,−→u 1v }.We have H ′′≺H and H ′′contains no special cycle by Remark 7.By minimality of H ,H ′′admits a good QR 7-arc-coloring f that can be extended to H :we set f (−→vu 2)=f (−→xu 2),and we have at least one available color for f (−→u 1v )by Property (P 2).2Recall that a bridge in a graph G is an edge whose removal increases the number of components of G.Lemma 11The graph H contains no bridge.Proof :Suppose that H contains a bridge uv .Let H \uv =H 1⊎H 2.For i =1,2,consider H ′i =H i +uv .By Lemma 10,uv is not a dangling arc in H .Moreover H ′i ≺H for i =1,2.Clearly,the graphs H ′1and H ′2have no special cycle and therefore,by minimality of H ,they admit good QR 7-arc-colorings f 1and f 2respectively.By cyclically permuting the colors of f 2if necessary,we may assume that f 1(uv )=f 2(uv ).The mapping f =f 1∪f 2is then clearly a good QR 7-arc-coloring of H .24(a)(b)Figure3:Configurations of Lemma14Lemma12The graph H contains no2-sink adjacent to a2-source.Proof:Suppose that H contains a2-sink v adjacent to a2-source w.Let N(v)={u,w}and N(w)= {v,x}.Since H contains no special cycle,u and x are distinct vertices and−→xu/∈A(H).Let H′be the graph obtained from H\{v,w}by adding−→ux(if it did not already belong to A(H)). We have H′≺H since n2(H′)≤n2(H)−2.Since the vertices u and x are neither3-sources nor3-sinks in H by Lemma9,they are neither2-sources nor2-sinks in H′and therefore,by Remark7,H′contains no special cycle.Hence,by minimality of H,H′admits a good QR7-arc-coloring f′that can be extended to H by setting f(−→uv)=f(−→wv)=f(−→wx)=f(−→ux).2Lemma13Every2-source(resp.2-sink)of H is adjacent to a vertex v with d+(v)=2(resp.d−(v)= 2).Proof:Suppose that H contains a2-source u adjacent to two vertices v and w such that d+(v)=2 and d+(w)=2(by Proposition6,it is enough to consider this case).Let H′=H\u;by hypothesisand by Lemmas9and12,the vertices v and w are such that d+H′(v)=d−H′(v)=d+H′(w)=d−H′(w)=1.Therefore,the graph H′contains no special cycle by Remark7.By minimality of H,H′admits a good QR7-arc-coloring f that can be extended to H in such a way that f(−→uu1)=f(−→uu2)thanks to Property(P2).2Recall that we denote by SS G(C)the set of2-sources and2-sinks of the cycle C in G.Lemma14Let u be a vertex of H and H′=H\u.Then H′does not contain a special cycle C with |N H(u)∩SS H′(C)|=1.Proof:Let v1∈N(u)and w.l.o.g.,suppose that H′=H\u contains a special cycle C such that N H(u)∩SS H′(C)={v1};by Remark7,v1is a2-source or a2-sink in H′and by Proposition6we may assume w.l.o.g.that v1is a2-source.By Remark3,v1is adjacent to a2-sink v2.By Lemma12,the only pair of adjacent2-source and 2-sink in H′is v1,v2.Therefore,we have3≤|C|≤4.Let V(C)={v1,v2,v3,v4}and v3=v4if|C|=3. Moreover v3and v4are necessarily two transitives vertices of C.Furthermore,we have−→yv3∈A(H)by Lemma13and−→uv1∈A(H)by Lemma9.Then,we have only two possible configurations,depicted in Figure3.v1v2.This graph contains no special cycle by •If|C|=3(see Figure3(a)),consider H′1=H\−−→Remark7and we have H′1≺H.By minimality of H,H′1admits a good QR7-arc-coloring fv3v2)thanks tov1v2)=f(−−→that can be extended to H:wefirst erase f(−−→v1v3);then,we can set f(−−→v1v3)by Property(P2)since f(−→Property(P2)and then we have one avalaible color for f(−−→uv1)= v3v2).f(−−→•If|C|=4(see Figure3(b)),consider the graph H′2=H\v2.We have H′2≺H.–If H′2contains no special cycle,by minimality of H,H′2admits a good QR7-arc-coloringv1v2)thanks to Property(P2)v3v2)=f(−−→f that can be extended to H in such a way that f(−−→v4v3)=f(−→yv3).since f(−−→–Suppose now that H′2contains a special cycle C′.By Remark7,v3belong to C′and byRemark3,y is a2-sink.By Lemma12,the only pair of adjacent2-source and2-sinkin H′is v3,y,and therefore|C′|is a special cycle of length3or4.Supposefirst that{u,v1,v4,v3,y}⊆V(C′);we thus have u=y,that is a contradiction since by hypothesisN H(u)∩SS H′(C)={v1}={v1,v3}.zv4∈A(H).If|C′|=3,we have y=z and in Therefore V(C′)={y,v3,v4,z},and then−→uv1that is forbidden by Lemma11.Therefore, this case,the graph H contains a bridge−→we have|C′|=4and z is a transitive vertex of C′.Consider in this case the graph H′3=H\v4.This graph contains no special cycle since thevertices v1and v3are two transitive2-vertices oriented in opposite directions.We haveH′3≺H and therefore,by minimality of H,there exists a good QR7-arc-coloring f of H′3such that C−f(v1)={c1},C−f(v2)={c2}and C+f(y)=C−f(z)={c3}.The mapping f canv4v3)=c4/∈{c1,c3}thanks to Property(P1).be extended to H as follows:we can set f(−−→v1v4)since c1=c4and one Then,by Property(P2),we have one avalaible color for f(−−→avalaible color for f(−→zv4)since c3=c4.2 Lemma15The graph H does not contain two adjacent2-vertices.Proof:Suppose that H contains two adjacent2-vertices v and w.Let N(v)={u,w}and N(w)={v,x} and H′=H\v.By Lemma Remark7and14,H contains no special cycle.We have H′≺H and by minimality of H,H′admits a good QR7-arc-coloring f.We shall consider two cases depending on the orientation of the arcs incident to v and w(by Proposition6,we may assume that−→uv∈A(H)).1.v is a2-sink and w is a transitive vertex.By Lemma12,u is not a2-source in H.We have|C−(u)|≤1and then,we can set f(−→uv)=fwv)thanks to Property(P2).f(−→2.v and w are transitive vertices.(u)|≤1.Thanks to Property(P1),we By the previous case,u is not a2-source.We have|C−fcan set f(−→uv)=f(−→vw)by Property(P2)since wx)andfinally,we have one available color for f(−→wx).f(−→uv)=f(−→22u(a)u 2(b)u 2(c)2u(d)u 2(e)u 12(f)Figure 4:Configurations of Lemma 16Lemma 16The graph H contains no 2-vertex.Proof :Suppose that H contains a 2-vertex u and let N (u )={u 1,u 2}.The vertices u 1and u 2are 3-vertices by Lemma 15.By Proposition 6,we may assume w.l.o.g.that −→uu 1∈A (H ).Let H ′1=H \u ;we have H ′1≺H .If H ′1contains no special cycle,then by minimality of H ,H ′1admits a good QR 7-arc-coloring f of H ′1that can be extended to H as follows.If u is a 2-source ,we can set f (−→uu 1)=f (−→uu 2)thanks to Property (P 2)since |C +f (u 1)|≤1and |C +f (u 2)|≤1.If u is a transitive vertex,we can set f (−→uu 1)/∈C −f (u 2)thanks to Property (P 1)and then we have one available color for f (−→u 2u )by Property (P 2).Suppose now that H ′1contains a special cycle C .By Lemma 14,u 1and u 2belongs to C and at least one of them is a 2-source or a 2-sink.Suppose first that u 1is a 2-source in H ′1and u 2is neither a 2-source nor a 2-sink in H ′1.Then,since H contains no adjacent 2-vertices by Lemma 15,we have only three possible configurations depictedin Figures 4(a),4(b)and 4(c).Clearly,the configuration of Figure 4(a)admits a good QR 7-arc-coloring.The white vertex of the configuration of Figure 4(b)is a 3-vertex by Lemma 15,but in this case,the graph contains a bridge,that is forbidden by Lemma 11.The white vertex of the configuration of Figure 4(c)is of degree two by Lemma 11and this configuration clearly admits a good QR 7-arc-coloring.Therefore,u 1and u 2are either 2-sources or 2-sinks in H ′1.In this case,since H contains no adjacent 2-vertices by Lemma 15,we have only three possible configurations depicted in Figure 4(d),4(e)and 4(f).•Figure 4(d):by Lemma 9,we have −→u 2u ,−→uu 1∈A (H ).Consider the graph H ′2=H \−−→u 1u 2;H ′2contains no special cycle.Since H ′2≺H ,by minimality of H ,H ′2admits a good QR 7-arc-coloring f that can be extended to H thanks to Property (P 2)since f (−→u 2u )=f (−→uu 1).•Figure 4(e):by Lemma 9,we have −→u 2u ,−→uu 1∈A (H ).By Lemma 15,u 4is a 3-vertex.Ifd −(u 4)=2,this configuration is forbidden by Lemma 13.If d +(u 4)=2,this configuration is also forbidden by Lemma 13.•Figure4(f):by Lemma9,we have−→uu1,−→uu2∈A(H).Therefore,by Lemma13,d−(u4)=2. Consider H′4=H\−−→u1u3;clearly,H′4contains no special cycle.By minimality of H,H′4admits a good QR7-arc-coloring that can be extended to H as follows.Wefirst erase f(−−→u2u4)and f(−−→u4u3);then,thanks to Property(P2),we can set f(−−→u1u3)=f(−−→u4u3).Finally,since f(−→uu2)= f(u4u3),we can extend f to a good QR7-arc-coloring of H thanks to Property(P2).2 3u(a)u3(b)u3(c)3u(d)Figure5:Configurations of Lemma17Lemma17The graph H contains no3-vertex.Proof:By Lemmas10and16,H is a3-regular graph.Let u be a vertex of H with neighbors u1,u2 and u3.By Lemma9,u is neither a3-source nor a3-sink and therefore,by Proposition6,we may assume w.l.o.g.that d+(u)≥d−(u).Let−→u1u,−→uu2,−→uu3∈A(H).If H′1=H\u contains no special cycle,by minimality of H,H′1admits a good QR7-arc-coloring f that can be extended to H as follows.We can set f(−→u1u)/∈C+f(u2)∪C+f(u3)thanks to Property(P1). Then,thanks to Property(P2),we can extend f to a good QR7-arc-coloring of H.Suppose now that H′1contains a special cycle C.The graph H′1contains three2-vertices.Since a special cycle consists in k pairs of2-sources and2-sinks,C contains only one pair of adjacent2-source and2-sink(w.l.o.g.u1and u2respectively).Therefore,we have only four possible configurations depicted in Figure5.Clearly,the configuration of Figure5(a)admits a good QR7-arc-coloring.The white vertex of the configuration of Figure5(c)is a2-vertex by Lemma11and it is easy to check that there exits a good QR7-arc-coloring of this graph.Consider now the configurations of Figures5(b)and5(d)and let H′2=H\−−→u1u2.We have H′2≺H and clearly,H′2contains no special cycle.Therefore,by minimality of H,H′2admits a good QR7-arc-coloing f that can be extended to H thanks to Property(P2)since for any orientation of H,C−f(u1)∩C+f(u2)=/0.2 Proof of Theorem2:By Lemmas10,16and17,a minimal counter-example to Theorem5does not exist.We now say that a QR7-arc-coloring f of an oriented subcubic graph G is quasi-good if and only if for every2-source u,|C+f(u)|=1.Note that if a subcubic graph admits a quasi-good QR7-arc-coloring f,we have|C+f(v)|≤1for every≤2-vertex v of G.We shall then prove Theorem2by showing that every subcubic graph admits a quasi-good QR7-arc-coloring.Let H be a minimal counter-example to Theorem2.If H contains no special cycle,by Theorem5,H admits a good QR7-arc-coloring which is a quasi-good QR7-arc-coloring.Suppose now that H contains at least one special cycle.By definition,a special cycle contains at least one2-source.We inductively define a sequence of graphs H0,H1,...,H n for n≥0,and a sequence of vertices u0,u1,...,u n−1such that:•H0=H;•H i contains a special cycle,and thus a2-source u i for0≤i<n;•H i+1=H i\u i for0≤i<n;•H n has no special cycle.By Theorem5,H n admits a good QR7-arc-coloring,and therefore a quasi-good QR7-arc-coloring. Suppose that H i+1admits a quasi-good QR7-arc-coloring f i+1for1≤i<n;we claim that we can extend f i+1to a quasi-good QR7-arc-coloring f i of H i as follows.To see that,let v i and w i be the twoneighbors of u i which are≤2-vertices in H i+1.Therefore,we have|C+fi+1(v i)|≤1and|C+fi+1(w i)|≤1and thanks to Property(P2),we can set f i(−→u i v i)=f i(−−→u i w i).Therefore,any quasi-good QR7-arc-coloring of H n can be extended to H0=H,that is a contradic-tion.A minimal counter-example to Theorem2does not exist,that completes the proof.2wzFigure6:Cubic graph G withχ′o(G)=6Currently,we cannot provide an oriented subcubic graph with oriented chromatic index7.How-ever,the oriented cubic graph G depicted in Figure6has oriented chromatic index6.Suppose we want to color G withfive colors1,2,3,4,5.Necessarily the colors of−→vw,−→xy and−→zu are pairwise distinct and we may assume w.l.o.g.that f(−→vw)=1,f(−→xy)=2and f(−→zu)=3.Clearly,each of the colors4and5will appear at most once on−→uv,−→wx and−→yz.Therefore,w.l.o.g.we may assume that f(−→yz)=1,which implies w.l.o.g.that we must set f(−→ux)=4.Thus,we must set f(−→yv)=5,and then we have no remaining color to color f(−→wz).Therefore,we have the following:Proposition18Let C be the class of subcubic graphs.Then6≤χ′o(C)≤7.References[1]O.V.Borodin,A.V.Kostochka,J.Neˇs etˇr il,A.Raspaud,and E.Sopena.On the maximum averagedegree and the oriented chromatic number of a graph.Discrete Math.,206:77–89,1999.[2]B.Courcelle.The monadic second order-logic of graphs VI:on several representations of graphsby relationnal stuctures.Discrete Appl.Math.,54:117–149,1994.[3]A.V.Kostochka,E.Sopena,and X.Zhu.Acyclic and oriented chromatic numbers of graphs.J.Graph Theory,24:331–340,1997.[4]E.Sopena.The chromatic number of oriented graphs.J.Graph Theory,25:191–205,1997.[5]E.Sopena.Oriented graph coloring.Discrete Math.,229(1-3):359–369,2001.[6]E.Sopena and L.Vignal.A note on the chromatic number of graphs with maximum degree three.Technical Report1125-96,LaBRI,Universit´e Bordeaux1,1996.[7]D.R.Wood.Acyclic,star and oriented colourings of graph subdivisions.Discrete Mathematicsand Theoretical Computer Science,7(1):37–50,2005.。