Theoretical Implications of the Combined Solar Neutrino Observations

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蓖麻高产宜机收杂交组合评价

蓖麻高产宜机收杂交组合评价

收稿日期:2023-09-05基金项目:国家自然科学基金(31271759)作者简介:左金鹰(1998-),女,在读硕士生,研究方向为蓖麻分子育种,E-mail:*****************通信作者:殷学贵(1964—),男,博士,教授,研究方向为蓖麻种质资源、分子遗传育种和基因组学,E-mail:*****************蓖麻高产宜机收杂交组合评价左金鹰,陆建农,殷学贵,黄冠荣,张柳琴,林海虹,张星语,刘陆洲(广东海洋大学滨海农业学院,广东 湛江 524088)摘 要:【目的】对蓖麻杂交组合进行联合评价,为筛选高产、宜机收蓖麻品种提供理论参考。

【方法】联用灰色关联度分析、主成分分析和聚类分析对30个蓖麻杂交组合的产量性状、宜机收性状和光合性能3个方面进行综合评价。

【结果】在灰色关联度分析中,根据育种目标构建了理想品种;通过各组合与理想品种之间的加权关联度评选出N 19(0.768)、N 7(0.751)、N 11(0.727)、N 10(0.717)、N 6(0.713)和N 13(0.712)6个组合。

其中,前4个组合的加权关联度优于淄蓖5号(0.714),后2个组合的加权关联度与淄蓖5号接近;主成分分析结果将10个性状归纳为株型因子、产量决定因子和光合与分枝夹角因子3个主成分,累计贡献率达67.07%。

30个组合中,21个组合的综合得分均大于淄蓖5号(-0.699),且仅N 18(2.370)、N 4(1.848)、N 19(1.742)和N 11(1.019)4个组合的得分大于1,并以N 19最为突出,其得分远高于其他材料;聚类分析结果显示,在欧氏距离值为22处可将30个组合划分为4个类群,第Ⅳ类群成员(包括N 19、N 11和N 30)的整体表现与理想品种最为相似,但分枝夹角(59.10°)较大,仍需进一步改良。

【结论】综合3种评价结果,避免了多余材料入选和优良材料丢失,最终筛选出N 19和N 11 2个产量高、株型好和光合速率高的蓖麻杂交组合,它们的综合表现均优于淄蓖5号,为品种改良方向提供参考。

层状双金属氢氧化物微观结构与性质的理论研究进展

层状双金属氢氧化物微观结构与性质的理论研究进展

层状双金属氢氧化物微观结构与性质的理论研究进展倪哲明1,*胥倩1潘国祥1,2毛江洪1(1浙江工业大学化学工程与材料学院,催化新材料研究室,杭州310032;2湖州师范学院化学系,浙江湖州313000)摘要:总结了近年来理论计算方法在研究层状双金属氢氧化物(LDHs)结构与功能方面的应用现状.结合LDHs 材料的结构特点,归纳了量子力学、分子力学、几何建模及物理静电模型相结合对LDHs 材料进行结构模拟的思路,比较了各种方法在LDHs 结构模拟上的优势及存在的不足.量子力学方法能够精确获得水滑石材料的层板构成及作用机制、简单阴离子插层水滑石主客体间的超分子作用实质以及电子性质、反应机理等方面的信息.与量子力学相比较,分子力学方法可以快速得到插层水滑石材料的层间阴离子排布及取向、水合膨胀特性及宏观力学性质等.几何模型和物理静电模型能构建直观、形象的数学模型,大大简化了计算量,因此能计算接近实际LDHs 尺寸的体系,为推测LDHs 结构信息提供了可能性.随着理论方法和计算机硬件水平的发展,使得计算机模拟技术逐渐成为获得LDHs 材料微观结构参数、电子性质和动力学性质的一种有效手段.关键词:层状双金属氢氧化物;结构与性质的关系;理论研究进展中图分类号:O641Theoretical Processing in Understanding the Structures and Properties of Layered Double HydroxidesNI Zhe -Ming 1,*XU Qian 1PAN Guo -Xiang 1,2MAO Jiang -Hong 1(1Laboratory of Advanced Catalytic Materials,College of Chemical Engineering and Materials Science,Zhejiang University of Technology,Hangzhou 310032,P.R.China ;2Department of Chemistry,Huzhou Teachers College,Huzhou 313000,ZhejiangProvince,P.R.China )Abstract :We review the techniques,applications,characteristics,and insights gained from the use of theoretical calculations that were applied to the study of layer double hydroxides (LDHs)materials by using a series of typical case studies.The advantages and shortcomings of different theoretical calculation methods (quantum mechanics,molecular mechanics,geometric model,and electrostatic potential energy model)for the study of the properties of LDHs minerals are compared.Based on quantum mechanics calculations,we obtained information about template effects on the construction of layered double hydroxides,super molecular interactions in LDHs containing simple anions,electronic properties,and reaction pathways pared with quantum mechanics,molecular mechanics is quicker in obtaining information about the interlayer structure,arrangement,orientation,hydration,and the swelling trajectory as well as elastic constants etc of LDHs intercalated with various anions.The geometric model and electrostatic potential energy model offer a more intuitive and visual mathematical model of LDHs minerals.The calculations were done on the verge of full size LDHs,which may allow the prediction of the crystal structure.Along with the development of theoretical methods and computer techniques,computational simulation method has become an effective adjust to experimental techniques for obtaining the microscopic structures,electronic and dynamic properties of LDHs minerals.Key Words :Layered double hydroxide;Structure -property relationship;Theoretical processing[Review]物理化学学报(Wuli Huaxue Xuebao )Acta Phys.-Chim.Sin .,2009,25(4):792-805Received:November 9,2008;Revised:January 16,2009;Published on Web:February 23,2009.*Corresponding author.Email:jchx@;Tel:+86571-88320373.浙江省自然科学基金(Y406069)资助项目鬁Editorial office of Acta Physico -Chimica SinicaApril792No.4倪哲明等:层状双金属氢氧化物微观结构与性质的理论研究进展层状双金属氢氧化物(layer double hydroxides,简称LDHs)是一类重要的新型无机功能材料,可作为制备无机-无机、无机-有机纳米复合材料的母体[1].因其具有特殊的层状结构及物理化学性质,在催化[2-5]、离子交换和吸附[6-8]、医药[9-13]等诸多领域具有广阔的应用前景.目前,粉末X射线衍射(XRD)、红外(IR)、热重差热分析(TG-DTA)、核磁共振(NMR)、X射线光电子能谱技术(XPS)、透射电镜(TEM)、中子衍射等实验手段已被应用于LDHs微观结构研究中,并取得了一些重要的结构数据[14-17].比如,LDHs微观结构研究中最为重要的XRD表征技术,能够得到合成材料是否具有层状构型,以及层间距、层板中金属离子的平均间距等重要结构参数[14].将插层阴离子的尺寸与层间距大小相关联,能推测阴离子在层间大致的排布情况(比如单层垂直、双层垂直交替、倾斜交替等)[14].IR、TG-DTA、NMR、中子衍射技术可作为辅助手段来佐证XRD推测所得LDHs微观结构的正确性[15-17].然而,对于复杂阴离子插层LDHs体系,其层间阴离子的排布形态确认仍存在困难,层间结构水分子的排布信息,从实验手段进行表征更是无法得知的.LDHs单晶合成非常有限(迄今为止只合成了2、3个LDHs单晶[1,18]),因而要从实验角度精确探求LDHs微观结构还存在相当大的困难.同时,要探求LDHs层板内部金属离子与羟基之间、主体层板与客体阴离子及水分子之间的超分子作用实质,从实验角度也是很难解决的.近年来,理论模拟计算作为获得LDHs材料微观结构信息和动力学性质的一种有效手段,为LDHs材料的分子设计提供了理论指导.本文总结了近年来理论计算方法在LDHs材料结构与功能方面的研究进展.结合LDHs 材料的结构特点,归纳了量子力学、分子力学、几何建模及物理静电模型相结合对LDHs材料进行结构模拟的思路,比较了各种方法在LDHs结构模拟上的优势及存在的不足.1层状LDHs材料微观结构与功能的关系LDHs是一类具有主体氢氧化物层板、客体阴离子柱撑的无机功能材料,其结构与水镁石结构类似[19,20].LDHs由水滑石(Mg6Al2(OH)16CO3·4H2O)经层板金属阳离子与层间阴离子调变而形成,其结构如图1所示,组成通式为[M II1-x M III x(OH)2]x+(A n-)x/n·m H2O,其中M II和M III分别代表二价和三价金属离子;x 是摩尔比n(M3+)/(n(M2+)+n(M3+));A n-是层间阴离子;m为层间结构水分子数目.LDHs独特的层状构型和结构的可调变性决定了其功能的多样性和应用的广泛性,研究LDHs材料微观结构与功能间的关系,必须对材料的精细结构取得足够的了解.LDHs材料的功能特性按照其微观和亚微观结构(三级结构:主体氢氧化物的层板、层间客体阴离子、结构水分子)进行划分,大致可分为以下三个方面:(1)层板有序结构主要由金属离子与羟基通过配位键形成,主体层板金属离子具有同晶可取代性.LDHs层状材料经合适温度焙烧,能够形成具有高表面积、高分散性、酸碱性可调的复合氧化物.焙烧产物中某些过渡金属经还原,便可形成性能优良的纳米金属负载型催化剂.由于LDHs层板金属离子具有可调变性(如Mg2+、Zn2+、Co2+、Ni2+、Cu2+和Al3+、Fe3+、Cr3+等),所以LDHs的焙烧/还原衍生物在催化、吸附等领域得到广泛应用.(2)层间客体阴离子具有可组装性.LDHs具有客体阴离子可插层性,主体层板与层间客体阴离子间存在着静电和氢键等分子间作用力,很多功能性阴离子能通过这些分子间相互作用而被引入LDHs 层间,形成一类新型LDHs基复合材料.比如:(a)杂多、同多酸阴离子、金属配离子;(b)羧酸、磺酸类有机阴离子;(c)布洛芬、萘普生等医药分子及草甘膦等农药分子;(d)氨基酸、DNA、核苷酸、ATP、酶等生物分子.这些分子/离子与LDHs组装后,能应用于催化、PVC改性剂、药物缓释、无机/生物复合材料、紫外阻隔材料、油田化工品、环境修复等领域.(3)层间水合膨胀及剥离特性.实验证明层间水分子具有稳定LDHs结构的作用,层间水分子与层板及阴离子间主要以氢键作用相结合,并能在一定温度下可逆脱除/吸收,所以在湿度调节方面得图1LDHs材料的结构示意图Fig.1Scheme of microstructure for LDHs793Acta Phys.-Chim.Sin.,2009Vol.25到应用.其他有机中性分子通过克服主客体间超分子作用力被引入LDHs层间,能使LDHs材料层间距膨胀乃至剥离,形成纳米LDHs层片,应用于LDHs/高分子复合材料的合成中.根据Lehn对超分子化学的阐述[21],LDHs主体层板形成、层板中M2+(M3+)-OH-(H2O)作用机制、层板与层间阴离子及水分子间相互作用都可纳入超分子化学研究范畴.从超分子化学角度,使用实验表征与理论模拟计算方法研究LDHs层板内部金属离子与羟基之间、层板与客体阴离子及水分子之间的相互作用,可取得LDHs材料结构调变与其功能间的关系.LDHs超分子结构与功能的基础性研究工作的进展,将有助于LDHs功能的强化以及应用领域的拓展.2理论方法研究LDHs材料的结构与性质近年来,理论模拟计算作为有效的研究方法在LDHs材料的微观结构、力学、热学、电磁学等性能的研究中卓有成效.其中,计算机模拟研究根据模拟尺度、理论依据、研究性质的不同,可分为量子力学(quantum mechanics,QM)和分子力学方法(molecular mechanics,MM)两大类,它被认为是本世纪以来除理论分析和实验观察之外的第三种科学研究手段,称之为“计算机实验”[22].2.1量子力学方法量子力学方法主要包括:从头算法(ab initio method)、分子轨道半经验计算法(semi-empirical molecular orbital method)和密度泛函理论(density functional theory,DFT)[22,23].它以分子中电子的非定域化(delocalization)为基础,电子的行为以其波函数表示.根据海森堡(Heisenberg)的测不准原理,量子力学仅能计算区间内电子出现的概率,其概率正比于波函数绝对值的平方.通过求解由核和电子组成的多电子体系的薛定谔方程,从而获得LDHs材料结构与功能方面的信息[22-24].它建立在原子核与核外电子作用基础上,计算精度高.量子力学方法适用于简单的分子或电子数量较少的体系,能够精确计算分子的性质、结构、构象、偶极矩、电离能、电子亲和力、电子密度等,以及了解分子间相互作用的电子性质.2.1.1从头算法从头算法利用变分原理(variation principle),将系统电子的波函数展开为原子轨道波函数的组合,而原子轨道的波函数又为一些特定的数学函数(如高斯函数)的组合[22,23].这种方法虽然精确,却甚为缓慢,所能计算的系统亦极为有限,通常不超过100个原子.目前,该方法主要应用于LDHs材料精确结构参数[25]、金属离子同晶取代对层板结构的影响[26]、酸碱性等物化性质的影响[26]、催化反应机理、催化剂活性[26]以及电子相关性质(态密度、能带结构)[26]方面的计算.Masini等[25]运用ab initio Car-Parrinello模拟了水镁石(brucite)表面的羟基化和脱羟基作用反应,在获得水镁石(0001),(1100)和(1000)晶面结构特性的同时,通过比较水镁石表面和内部的脱羟基反应所需的能量,指出水镁石分解生成MgO和H2O的反应首先在材料表面发生.Trave等[26]计算了含有不同层板阳离子和层间阴离子的LDHs体系的晶格参数、自由度等结构信息,探讨了层板Al3+的排列方式和Mg/Al摩尔比两个参数对Mg/Al-LDHs结构的影响,当R(M II/M III 摩尔比)约为3时,体系的结合能最低,而层间通道高度最大,建立了结构参数与化学组成和结合能之间的关系.另一方面,通过对态密度等电子性质的研究,发现层间阴离子的性质对化合物的电子性质有很大的影响.与LDHs-Cl体系相比,LDHs-OH体系最高占据轨道(HOMO)-最低空轨道(LUMO)间的禁带宽度较小,且层间的LUMO轨道主要由层间的阴离子提供(如图2),导致了LDHs-OH具有更强的接受电子的能力,所以LDHs-OH较LDHs-Cl在羟醛缩合碱催化反应中具有更高的碱催化活性.李蕾等[27]在制备表征磺基水杨酸、4-羟基-3-甲氧基肉桂酸和2-羟基-4-甲氧基二苯甲酮-5-磺酸等紫外吸收剂插层锌铝水滑石的基础上,运用(a)(b)图2(a)LDHs-Cl和(b)LDHs-OH的HOMO和LUMO轨道分布图[26]Fig.2Spatial distributions of the HOMO and LUMO for(a)LDHs-Cl and(b)LDHs-OH [26]794No.4倪哲明等:层状双金属氢氧化物微观结构与性质的理论研究进展Gaussian98[28]软件中的ab initio分子轨道法(HF/6-31G)计算了LDHs层间有机紫外吸收剂的分子结构和电荷分布,提出了合理的客体阴离子在主体层间的排列方式,并分析了其结构与光化学行为的关系.结果表明,层板间的限域空间有利于主客体间的静电和氢键相互作用,插层产物的紫外吸收范围和能力显著增强,是一类具有潜在应用价值的无机-有机超分子复合结构的紫外吸收材料.2.1.2分子轨道半经验方法分子轨道半经验方法在从头算法的基础上,多引用了一些实验值为参数,求解Hartree-Fock-Roothaan 方程,以取代计算真正的积分项[22,23].采用此方法计算LDHs材料时,相关的结构参数如键长、键角等,往往不是通过几何优化获得,而是来源于实验文献.目前常用的分子轨道半经验方法有休克尔方法(EHMO),全略微分重叠(CNDO),间略微分重叠(INDO),改进的间略微分重叠(MINDO),忽略双原子微分重叠(MNDO),以及在忽略双原子微分重叠(MNDO)基础上发展起来的AM1方法和PM3方法等[22,23].与从头算法相比,利用半经验分子轨道方法可计算较大的分子,但需以大量的实验数据为基础.Pu等[29,30]采用MNDO/d、PM3法优化了不同尺寸水滑石层板结构,优化所得的晶体团簇模型呈六边形结构,且层板的Mg/Al摩尔比为可变参数,但当层板直径变得比较大时,Mg/Al摩尔比的极限值为3.在插层反应过程中,层板的边缘较容易吸附阳离子,而层板中心则易接受阴离子.在此基础上,他们采用B3PW91方法在Lanl2dz基组水平上进一步研究了Mg/Al摩尔比为3的水滑石层板结构[31],通过将结构参数和模拟得到的XRD图谱分别与实验观测结果相比较,确定了水滑石层板符合空间群R3m(166),沿第三维方向有序堆积.李蕾等[32]采用以含原子对排斥的EHMO法ASED(atom superposition and electron delocalization) -MO法为基础的结构自动优化EHTOPT程序,优化计算了Mg6Al2(OH)16X·H2O主体层板与不同简单客体阴离子稳定结构的能量变化、成键状况及电荷转移情况,揭示了LDHs层板与层间阴离子间存在静电吸引、氢键等非共价键弱相互作用.其中氢键作用为主,且强弱与阴离子电荷分布、空间排布方式密切相关,层间阴离子电荷分布对层板酸碱性变化也有影响.2.1.3密度泛函理论密度泛函理论是一种研究多电子体系电子结构的量子力学方法,即为非常精确的量子计算方法.在Kohn-Sham DFT的框架中,最难处理的多体问题(由于处在一个外部静电势中的电子相互作用而产生的)被简化成了一个没有相互作用的电子在有效势场中运动的问题[23].密度泛函理论是目前多种领域中电子结构计算的领先方法,但是用它来恰当地描述分子间相互作用,特别是范德华力(van der Waals),或者计算半导体的能隙还存在一定的困难.目前该方法主要被应用于研究LDHs材料层板金属离子同晶取代对层板结构的影响[31]、层板内部金属离子与羟基之间配位作用[33]、简单阴离子插层LDHs材料的微观结构性质和主客体间超分子作用实质[34-36]、成键规律、热稳定性、酸碱性等物化性质、离子交换性能、催化性能[32-37]、反应机理[38,39]等相关领域的研究.Wei等[33]采用混合密度泛函B3LYP方法对构建LDHs时产生的模板效应进行了研究.根据计算所得的结构畸变角θ的不同,可将层板金属离子分为三类(如图3):类型I(canonical structure,θ:0°-1°),类型II(slightly distorted structure,θ:1°-10°)和类型III(heavily distorted structure,θ>10°).计算了与LDHs 结构相关的键长、O—M—O键弯曲角、键能、价电图3[M(H2O)6]n+的三种几何优化结构[33]Fig.3Three types of optimized structures of the[M(H2O)6]n +[33]795Acta Phys.-Chim.Sin.,2009Vol.25子构型、配位场以及Jahn-Teller效应和自然键轨道(NBO).指出同晶取代Mg2+进入LDHs层板的金属阳离子,其与氧原子形成的八面体六配位的畸变角较离子半径对LDHs的层板结构有着更大的影响,且影响程度为类型I>类型II>类型III.倪哲明等[34,35]建立了LDHs与卤素阴离子(F-、Cl-)的单层簇模型,运用Gaussian03[40]程序,采用混合密度泛函B3LYP方法,在6-31G(d)基组水平上进行结构优化和频率分析,然后分别用6-31G(d)和6-311++G(d,p)计算主客体相互作用能,分析了LDHs 主体层板与卤素阴离子的超分子作用(静电作用和氢键作用),并对F-、Cl-超分子作用的强弱进行了比较.然后又建立了LDHs与CO2-3、H2O的双层簇模型,采用B3LYP/6-31G(d)//B3LYP/3-21G方法计算类水滑石(LDHs-CO3-n H2O)的结构与能量,探讨了主客体间的超分子作用,并对LDHs层间存在的三种不同类型氢键的强度进行了比较.在此基础上,还构建LDHs-Cl-n H2O周期性模型(如图4),采用了CASTEP[41]优化计算其微观结构,从结构参数、Mulliken电荷布居、态密度(DOS)、能量等角度研究层间Cl-和不同数目水分子的分布形态以及与LDHs层间的超分子作用[36].随着水分子数的增加,层间距逐渐增大后趋于平衡.水合过程中氢键作用比静电作用更占优势,layer-water型氢键要略强于anion-water型氢键.当n=1、2时,Cl-与水分子所在平面以平行层板的方式存在于LDHs层间,并且与两层板的距离基本相等;当n=3、4时,Cl-与水分子则以偏向某一层的方式随机地存在于LDHs 层板间,并且得出LDHs-Cl的水合具有饱和量.Anderson等[37]在实验合成sulfonato-salen-M III (M=Mn,Fe,Co)配合物插层Zn/Al-LDHs的基础上,在分子氧和常温、常压条件下,测试其对生成环己烯和二聚环戊二烯的环氧化反应的催化性能.采用混合密度泛函B3LYP方法,计算了sulfonato-salen-M III (M=Mn,Fe,Co)的结构参数(如图5),发现不同插层产物的层间通道高度和催化行为是有区别的,中心金属离子的性质较大地修饰了催化活性位附近的化学环境,从而导致了不同配合物的催化活性不同,催化性能大小为LDH-[Fe(Cl)(salen)]<LDH-[Co(Cl) (salen)]<LDH-[Mn(Cl)(salen)].Greenwell等[38]采用平面波密度泛函理论(PW-DFT)研究了镁铝水滑石催化叔丁醇酯交换反应的机理.通过计算反应机理中涉及的过渡态,指出Choudary等提出的机理(如图6(a))中催化剂再生的步骤无法实现.通过一系列计算模拟,提出层间水的图4LDHs-Cl-n H2O(n=1-4)主客体作用模型[36]Fig.4Host-guest interaction models of LDHs-Cl-n H2O(n=1-4)[36]图5Sulfonato-salen-M III配合物的几何结构[37]Fig.5Computed structures of sulfonato-salen-M III [37] 796No.4倪哲明等:层状双金属氢氧化物微观结构与性质的理论研究进展存在是催化剂再生的必要条件(如图6(b)),叔丁基阳离子在层间不可能单独存在,活性部分叔丁醇的羟基—OH与LDHs层板间存在着比较强的相互作用.LDHs层板的亲水性与t-Bu-LDH的层间区域的疏水性,导致有机物分子的极化基团排列于LDHs 表面,增强了材料的催化活性,促进整个催化反应的进行.Wei等[39]采用混合密度泛函B3PW91方法在6-31G(d,p)基组水平上,对手性药物左旋多巴(L-dopa)插层前后的外消旋现象进行了研究.对反应中涉及的过渡态的模拟结果表明,插层前左旋多巴单体手性碳上的H会迁移至羧基,构成烯醇式的活性中间体,从而外消旋化.插层后,左旋多巴的羧基会和LDHs层板发生强的主客体相互作用(相互作用能为-1100kJ·mol-1),而无法成为质子接受体,外消旋化得到了抑制.从而证明了LDHs材料是一种很好的用来贮存和运载手性药物的载体.2.2分子力学方法分子力学方法起源于1970年左右,是依据经典力学(classical mechanics)的计算方法.此种方法主要依据Born-Oppenheimer近似原理,计算中将电子的运动忽略,而将系统的能量视为原子核位置的函数[23,24].以原子间相互作用势为基础,主要依据分子的力场计算分子的各种特性.该方法主要包括:能量最小化(energy minimization)、蒙持卡罗计算法(Monte Carlo method,MC)和分子动力学模拟(molecular dynamics simulation,MD).分子力场中的关于LDHs材料的结构参数通常可经由量子力学计算或实验方法得到.与量子力学相比较,此方法可以快速地得到分子的各种性质,但无法得到有关体系电子性质方面的结果.分子力学方法常被用于药物、团簇体、生化大分子的研究、复杂的有机阴离子(药物、氨基酸、DNA)插层LDHs复合材料超分子结构的优化计算.2.2.1能量最小化法能量最小化方法是将最初的结构进行模型修饰(model refinement)的过程,藉由分子力学的能量最小化来修正不利的非共价碰触及达到理想的键结合和能量最低的构型.分子力学方法主要计算包括键长、键角、二面角、静电作用力和范德华作用力等位能参数,它的能量计算公式:E total=E stretching+E bending+E dihedral+E out-of-plane+E cross terms+E van der Waals+E coulombic在分子力学方法中常用于能量最小化的力场有CHARMM[42],AMBER[43],CVFF[44],CFF91[45]或GROMOS[46]等.Fogg等[47]采用GULP程序(general utility lattice program)计算了Li/Al-LDHs-Cl、Li/Al-LDHs-Br和Li/ Al-LDHs-NO3体系的最优结构.模拟结果表明,能量最低时所得的结构与实验表征的结果相一致,能够较好地解释NO-3在Li/Al-LDHs-NO3层板间的无规律排列现象.这种计算方法同时也被认为是研究Li/ Al-LDHs-CO3、Li/Al-LDHs-SO4和Li/Al-LDHs-C2O4等体系层间间距和层间客体排布取向的有效手段. 2.2.2蒙特卡罗计算法蒙特卡罗计算法借由系统中质点(原子或分子)的随机运动,结合统计力学的概率分配原理,以得到体系的统计及热力学资料.此方法多用以研究复杂体系及金属的结构及其相变性质.蒙特卡罗计算法的弱点在于只能计算统计的平均值,不能追踪势能变化的路径,无法得到系统的动态信息[24].此计算所依据的随机运动并不适合物理学的运动原理,与其他的非量子计算方法相较亦非特别经济快速.因此,自分子动力学计算逐渐盛行后,蒙特卡罗计算方(a)Choudary et al.′s proposed mechanism(b)Greenwell et al.′s proposed mechanism图6两种可能的酯交换反应机理[38]Fig.6Two possible reaction mechanism for the transesterification reaction [38]797Acta Phys.-Chim.Sin.,2009Vol.25法已较少为人所采用.Kirkpatrick等[48]采用NMR与Monte Carlo模拟相结合的方法,观察模拟了SO2-3、SeO2-4、PO2-4、HPO3-4、MoO2-4、ClO-4、SeO2-3、CO2-3、F-、Cl-、Br-、I-、OH-和NO-3阴离子进入Li/Al和Mg/Al-LDHs后与层间水相互影响可能发生的三种膨胀情况,并分析了相对湿度(RH)对该体系膨胀行为的影响.类型I,明显膨胀行为,膨胀尺度为0.15-0.30nm,通过XRD和NMR 测定发现,层间水从单层排列转变为双层排列,与吸附水等温曲线相一致.类型II,轻微膨胀行为,膨胀尺度<0.05nm,伴随着大量的层间水交换行为;层间水在层间只呈单层排列,且随着RH的增加,层间阴离子会经历一个动力学无序化阶段.类型III,基本不产生膨胀行为,膨胀尺度为0-0.02nm,只有微量的层间水交换行为;由于层间客体的紧密排列,只有极少量的水分子被吸收进入层间.此外,由于阴离子的体积较小,使其和层板羟基之间存在着强烈的静电作用和氢键作用,导致RH对环境结构和阴离子的动态特征几乎没有影响.2.2.3分子动力学模拟分子动力学模拟是应用力场及根据牛顿运动力学原理所发展的计算方法[23],在物理学、化学、生物学和材料科学等许多领域中得到广泛地应用.与蒙特卡罗计算方法比较,分子动力学模拟时系统中粒子的运动有正确的物理依据.优点是精准性高,可同时获得系统的动态与热力学统计资料,并可广泛地适用于各种系统及各类特性的探讨.分子动力学模拟方法本身亦有一定的限制,由于此计算需要引用数理积分方法,因此仅能研究系统短时间范围内的运动,而无法模拟一些时间较长的运动问题[24].MD方法主要用于软性层状粘土材料的模拟,在可变层间空间条件下,计算LDHs层间客体(简单阴离子、有机大分子、生物分子)的排布方式及取向[49-55]、层间阴离子与主体层板的成键情况、吸附、水合膨胀特性模拟[50-59]以及氢键结构分析[57-60],预测化学反应的活性及产物分析[55],LDHs材料XRD图谱模拟计算[61,62],药物分子在层板间的存在形式、结合情况[63-65]、热效应[62]等方面的计算模拟研究.Ma等[50]对包含水分子和不同客体阴离子(CO2-3、SO2-4、OH-、F-、Cl-、Br-、NO-3)的α-Ni(OH)2(1)、β-Ni(OH)2 (2)和Ni/Al-LDHs(3)三个体系的结构进行了分子动力学模拟,发现对于α-Ni(OH)2和Ni/Al-LDHs体系,当层间阴离子为F-、Cl-、Br-、OH-、NO-3、CO2-3时,层间水分子的堆积模式为紧密堆积(如图7(a));当层间阴离子为SO2-4时,层间水分子的排列方式相对松散(如图7(b));且对于Ni/Al-LDHs-SO2-4体系,由于层间含水量较高,水分子在层间为双层排布(如图7(c)).同时,对β-Ni(OH)2体系水合能以及无水β-Ni(OH)2的相对结合能进行了有关计算,为不同阴离子在离子交换反应的相对亲和力提供了理论依据,并指出库仑引力是影响势能的主要因素,层间阴离子的净电荷和范德华半径以及层间水的含量都对结合能有显著的影响,尤其当层间为有机阴离子时,效果更为显著.Lombardo等[62]首次以实验XRD和MD相结合的方法应用于获取热处理过程中低晶状[Zn0.65Al0.35 (OH)2]Cl0.35·0.35H2O(I)和[Zn0.65Al0.35(OH)2](CO3)0.175·0.69H2O(II)的结构、动力学等性质.他们工作的亮点是MD模拟所得到的XRD谱图是通过计算一系列晶胞参数不同的结构模型拟合得到的,而不是传图7层间水分子的堆积方式[50]Fig.7Schematic to show possible packing styles of interlayer water molecules [50] 798。

FORNELL教授经典的顾客满意度论文1

FORNELL教授经典的顾客满意度论文1

TOTAL QUALITY MANAGEMENT, VOL. 11, NO. 7, 2000, S869-S882EUGENE W. ANDERSON & CLAES FORNELLNational Quality Research Center, University of Michigan Business School, Ann Arbor,MI 48109-1234, USAABSTRACT How do we know if an economy is performing well? How do we know if a company is performing well? The fact is that we have serious difficulty answering these questions today. The economy—for nations and for corporations—has changed much more than our theories and measurements. The development of national customer satisfaction indices (NCSIs) represents an important step towards addressing the gap between what we know and what we need to know. This paper describes the methodology underlying one such measure, the American Customer Satisfaction Index (ACSI). ACSI represents a uniform system for evaluating, comparing, and—ultimately- enhancing customer satisfaction across ifrms, industries and nations. Other nations are now adopting the same approach. It is argued that a global network of NCSIs based on a common methodology is not simply desirable, but imperative.IntroductionHow do we know if an economy is performing well? How do we know if a company is performing well? The fact is that we have serious difficulty answering these questions today. It is even more difficult to tell where we are going.Why is this? A good part of the explanation is that the economy—for nations and for corporations—has changed much more than our theories and measurements. One can easily make the case that the measures on which we rely for determining corporate and national economic performance have not kept pace. For example, the service sector and information technology play a dominant role in the modern economy. An implication of this change is that economic assets today reside heavily in intangibles—knowledge, systems, customer relationships, etc. (see Fig. 1). The building of shareholder wealth is no longer a matter of the management of ifnancial and physical assets. The same is true with the wealth of nations.As a result, one cannot continue to apply models of measurement and theory developed for a 'tangible' manufacturing economy to the economy we have today. How important is it to know about coal production, rail freight, textile mill or pig-iron production in the modern economy? Such measures are still collected in the US and reported in the media as if theyhad the same importance now as they did over 50 years ago.The problem gets worse when we take all these measures, add them up and draw conclusions. For example, in early 1999, the US stock market set an all time record highCorrespondence: E. W. Anderson, National Quality Research Center, University of Michigan Business School, Ann Arbor, MI 48109-1234, USA. Tel: (313) 763-1566; Fax: (313) 763-9768; E-mail: genea@ISSN 0954-4127 print/ISSN 1360-0613 online/00/07S869-14 0 2000 Taylor & Francis LtdS870 E. W. ANDERSON & C. FORNELLDow Jones Industrials:Price-to-Book Ratios11970 1999Source: Business Week, March 9, 1999Figure 1. Tangible versus intangible sources of value, 1970-99.with the Dow Jones Index passing 11 000 points, unemployment was at record lows, the economy expanded and inflation was almost non-existent. These statistics suggested a strong economy, which was also what was reported in the press and in most commentary by economists. As always, however, the real question is: Are we better off? How well are the actual experiences of people captured by the reported measures? Do the things economists and Governments choose to measure correspond with how people feel about their economic well-being? A closer inspection of the numbers and their underlying statistics reveals a somewhat different picture of the US economy than that typically held up as an example.?Corporate earnings growth for 1997 and 1998 were much lower than in the previous2 years, with a negative growth for 1998.?The major portion of the earnings growth in 1995 and 1996 was due to cost-cutting rather than revenue growth.?The trade deficit in 1999 was at a record high and growing.?Wages have been stagnant in the last 15 years (although there were small increases in 1997 and 1998).?The proportion of stock market capitalization versus GDP was about 150% of GDP in 1998 (the historical average is 48%; the proportion before the 1929 stock market crash was 82%).?Consumer and business debt were high and rising.?Even though many new jobs were created, 70% of those who lost their jobs got new jobs that paid less.?The number of bankruptcies was high and growing.?Worker absenteeism was at record highs.?Household savings were negative.Add the above to the fact that there is a great deal of worker anxiety over job security and lower levels of customer satisfaction than 5 years ago, and the question of whether we areyrFOUNDATIONS OF ACSI S871better off is cast in a different light. How much does it matter if we increase productivity,that the economy is growing or that the stock market is breaking records, if customers arenot satisifed? The basic idea behind a market economy is that businesses exist and competein order to create a satisifed customer. Investors will lfock to the companies that are expectedto do this well. It is not possible to increase economic prosperity without also increasingcustomer satisfaction. In a market economy, where suppliers compete for buyers, but buyersdo not compete for products, customer satisfaction defines the meaning of economic activity,because what matters in the final analysis is not how much we produce or consume, but howwell our economy satisfies its consumers.Together with other economic objectives—such as employment and growth—thequality of what is produced is a part of standard of living and a source of national competitiveness. Like other objectives, it should be subjected to systematic and uniform measurement. This is why there is a need for national indices of customer satisfaction. Anational index of customer satisfaction contributes to a more accurate picture of economicoutput, which in turn leads to better economic policy decisions and improvement of standard ofliving. Neither productivitymeasures nor price indices can be properly calibrated without taking quality into account.It is difficult to conduct economic policy without accurate and comprehensive measures. Customer satisfaction is of considerable value as a complement to the traditional measures.This is true for both macro and micro levels. Because it is derived from consumption data(as opposed to production) it is also a leading indicator of future proifts. Customer satisfactionleads to greater customer loyalty (Anderson & Sullivan, 1993; Bearden & Teel, 1983; Bolton& Drew, 1991; Boulding et al., 1993; Fornell, 1992; LaBarbera & Mazurski, 1983; Oliver,1980; Oliver & Swan, 1989; Yi, 1991). Through increasing loyalty, customer satisfactionsecures future revenues (Bolton, 1998; Fornell, 1992; Rust et al., 1994, 1995), reduces thecost of future transactions (Reichheld & Sasser, 1990), decreases price elasticities (Anderson,1996), and minimizes the likelihood customers will defect if quality falters (Anderson & Sullivan, 1993). Word-of-mouth from satisifed customers lowers the cost of attracting new customers and enhances the firm's overall reputation, while that of dissatisifed customersnaturally has the opposite effect (Anderson, 1998; Fornell, 1992). For all these reasons, it isnot surprising that empirical work indicates that ifrms providing superior quality enjoy higher economic returns (Aaker & Jacobson, 1994; Anderson et al., 1994, 1997; Bolton, 1998;Capon et al., 1990).Satisfied customers can therefore be considered an asset to the ifrm and should be acknowledged as such on the balance sheet. Current accounting-based measures are probablymore lagging than leading—they say more about past decisions than they do about tomorrow's performance (Kaplan & Norton, 1992). If corporations did incorporate customer satisfactionas a measurable asset, we would have a better accounting of the relationship between theenterprise's current condition and its future capacity to produce wealth.If customer satisfaction is so important, how should it be measured? It is too complicatedand too important to be casually implemented via standard market research surveys. The remainder of this article describes the methodology underlying the American Customer Satisfaction Index (ACSI) and discusses many of the key ifndings from this approach.Nature of the American Customer Satisfaction IndexACSI measures the quality of goods and services as experienced by those that consume them.An individual ifrm's customer satisfaction index (CSI) represents its served market's—its customers'—overall evaluation of total purchase and consumption experience, both actualand anticipated (Anderson et al., 1994; Fonrell, 1992; Johnson & Fornell, 1991).S872 E. W. ANDERSON & C. FORNELLThe basic premise of ACSI, a measure of overall customer satisfaction that is uniform and comparable, requires a methodology with two fundamental properties. (For a complete description of the ACSI methodology, please see the 'American Customer Staisfaction Index: Methodology Report' available from the American Society for Quailty Control, Milwaukee, WI.) First, the methodology must recognize that CSI is a customer evaluation that cannot be measured directly. Second, as an overall measure of customer satisfaction, CSI must be measured in a way that not only accounts for consumption experience, but is also forward-looking.Direct measurement of customer satisfaction: observability with errorEconomists have long expressed reservations about whether an individual's satisfaction or utility can be measured, compared, or aggregated (Hicks, 1934, 1939a,b, 1941; Pareto, 1906; Ricardo, 1817; Samuelson, 1947). Early economists who believed it was possible to produce a 'cardinal' measure of utility (Bentham, 1802; Marshall, 1890; Pigou, 1920) have been replaced by ordinalist economists who argue that the structure and implications of utility-maximizing economics can be retained while relaxing the cardinal assumption. How_ ever, cardinal or direct measurement of such judgements and evaluations is common in other social sciences. For example, in marketing, conjoint analysis is used to measure individual utilities (Green & Srinivasan, 1978, 1990; Green & Tull, 1975).Based on what Kenneth Boulding (1972) referred to as Katona's Law (the summation of ignorance can produce knowledge due to the self-canceling of random factors), the recent advances in latent variable modeling and the call from economists such as the late Jan Tinbergen (1991) for economic science to address better what is required for economic policy, scholars are once again focusing on the measurement of subjective (experience) utility. The challenge is not to arrive at a measurement system according to a universal system of axioms, but rather one where fallibility is recognized and error is admitted (Johnson & Fornell, 1991) .The ACSI draws upon considerable advances in measurement technology over the past 75 years. In the 1950s, formalized systems for prediction and explanation (in terms of accounting for variation around the mean of a variable) started to appear. Before then, research was essentially descriptive, although the single correlation was used to depict the degree of a relationship between two variables. Unfortunately, the correlation coefficient was otfen (and still is) misinterpreted and used to infer much more than what is permissible. Even though it provides very little information about the nature of a relationship (any given value of the correlation coefficient is consistent with an inifnite number of linear relationships), it was sometimes inferred as having both predictive and causal properties. The latter was not achieved until the 1980s with the advent of the second generation of multivariate analysisand associated sotfware (e.g. Lisrel).It was not until very recently, however, that causal networks could be applied to customer satisfaction data. What makes customer satisfaction data difficult to analyze via traditional methods is that they are associated with two aspects that play havoc with most statistical estimation techniques: (1) distributional skewness; and (2) multicollinearity. Both are extreme in this type of data. Fortunately, there has been methodological progress on both fronts particularly from the field of chemometrics, where the focus has been on robust estimation with small sample sizes and many variables.Not only is it now feasible to measure that which cannot be observed, it is also possible to incorporate these unobservables into systems of equations. The implication is that the conventional argument for limiting measurement to that which is numerical is no longer allFOUNDATIONS OF ACSI S873that compelling. Likewise, simply because consumer choice, as opposed to experience, is publicly observable does not mean that it must be the sole basis for utility measurement. Such reasoning only diminishes the influence of economic science in economic policy (Tinbergen 1991).Hence, even though experience may be a private matter, it does not follow that it is inaccessible to measurement or irrelevant for scientific inquiry, for cardinalist comparisons of utility are not mandatory for meaningful interpretation. For something to be 'meaningful,' it does not have to be 'flawless' or free of error. Even though (experience) utility or customer satisfaction cannot be directly observed, it is possible to employ proxies (fallible indicators) to capture empirically the construct. In the ifnal analysis, success or failure will depend on how well we explain and predict.Forward-looking measurement of customer satisfaction: explanation and predictionFor ACSI to be forward-looking, it must be embedded in a system of cause-and-effect relationships as shown in Fig. 2, making CSI the centerpiece in a chain of relationships running from the antecedents of customer satisfaction —expectations, perceived quality and value —to its consequences —voice and loyalty. The primary objective in estimating this system or model is to explain customer loyalty. It is through this design that ACSI captures the served market's evaluation of the ifrm's offering in a manner that is both backward- and forward-looking.Customer satisfaction (ACSI) has three antecedents: perceived quality, perceived value and customer expectations. Perceived quality or performance, the served market's evaluation of recent consumption experience, is expected to have a direct and positive effect on customer satisfaction. The second determinant of customer satisfaction is perceived value, or the perceived level of product quality relative to the price paid. Adding perceived value incorpo-rates price information into the model and increases the comparability of the results across ifrms, industries and sectors. The third determinant, the served market's expectations, represents both the served market's prior consumption experience with the firm's offeringCustomization Complaints to Complaints toinagement PersonnelPriceü GivenQualityQualityGivenPrice DelepurchasePrice Likelihood ToleranceCustomization Reliability O v e r a l l Figure 2. The American Customer Satisfaction Index model.S874 E. W. ANDERSON & C. FORNELLincluding non-experiential information available through sources such as advertising and word-of-mouth—and a forecast of the supplier's ability to deliver quality in the future.Following Hirschman's (1970) exit-voice theory, the immediate consequences of increased customer satisfaction are decreased customer complaints and increased customer loyalty (Fornell & Wemerfelt, 1988). When dissatisifed, customers have the option of exiting (e.g. going to a competitor) or voicing their complaints. An increase in satisfaction should decrease the incidence of complaints. Increased satisfaction should also increase customer loyalty. Loyalty is the ultimate dependent variable in the model because of its value as aproxy for profitability (Reichheld & Sasser, 1990).ACSI and the other constructs are latent variables that cannot be measured directly, each is assessed by multiple measures, as indicated in Fig. 1. To estimate the model requires data from recent customers on each of these 15 manifest variables (for an extended discussion of the survey design, see Fomell et al., 1996). Based on the survey data, ACSI is estimated as shown in Appendix B.Customer satisfaction index properties: the case of the American Customer Satisfaction IndexAt the most basic level the ACSI uses the only direct way to ifnd out how satisifed or dissatisifed customers are—that is, to ask them. Customers are asked to evaluate products and services that they have purchased and used. A straightforward summary of what customers say in their responses to the questions may have certain simplistic appeal, but such an approach will fall short on any other criterion. For the index to be useful, it must meet criteria related to its objectives. If the ACSI is to contribute to more accurate and comprehen-sive measurement of economic output, predict economic returns, provide useful information for economic policy and become an indicator of economic health, it must satisfy certain properties in measurement. These are: precision; validity; reliability; predictive power; coverage; simplicity; diagnostics; and comparability.PrecisionPrecision refers to the degree of certainty of the estimated value of the ACSI. ACSI results show that the 90% confidence interval (on a 0-100 scale) for the national index is ± 0.2 points throughout its first 4 years of measurement. For each of the six measured private sectors, it is an average ± 0.5 points and for the public administration/government sector, it is + 1.3 points. For industries, the conifdence interval is an average ±1.0 points for manufacturing industries, + 1.7 points for service industries and ± 2.5 points for government agencies. For the typical company, it is an average ± 2.0 points for manufacturing ifrms and 2.6 points for service companies and agencies. This level of precision is obtained as a result of great care in data collection, careful variable speciifcation and latent variable modeling. Latent variable modeling produces an average improvement of 22% in precision over use of responses from a single question, according to ACSI research.ValidityValidity refers to the ability of the individual measures to represent the underlying construct customer satisfaction (ACSI) and to relate effects and consequences in an expected manner. Discriminant validity, which is the degree to which a measured construct differs from other measured constructs, is also evidenced. For example, there is not only an importanto-FOUNDATIONS OF ACSI S875 conceptual distinction between perceived quality and customer satisfaction, but also anempirical distinction. That is, the covariance between the questions measuring the ACSI ishigher than the covariances between the ACSI and any other construct in the system.The nomological validity of the ACSI model can be checked by two measures: (1) latentvariable covariance explained; and (2) multiple correlations (R'). On average, 94% of thelatent variable covariance structure is explained by the structural model. The average R2ofthe customer satisfaction equation in the model is 0.75. In addition, all coefficients relatingthe variables of the model have the expected sign. All but a few are statistically signiifcant.In measures of customer satisfaction, there are several threats to validity. The most seriousof these is the skewness of the frequency distributions. Customers tend disproportionately touse the high scores on a scale to express satisfaction. Skewness is addressed by using a fairlyhigh number of scale categories (1-10) and by using a multiple indicator approach (Fornell,1992, 1995). It is a well established fact that vaildity typically increases with the use of more categories (Andrews, 1984), and it is particularly so when the respondent has good knowledgeabout the subject matter and when the distribution of responses is highly skewed. An indexof satisfaction is much to be preferred over a categorization of respondents as either 'satisfied'or 'dissatisfied'. Satisfaction is a matter of degree—it is not a binary concept. If measured asbinary, precision is low, validity is suspect and predictive power is poor.ReliabilityReliability of a measure is determined by its signal-to-noise ratio. That is, the extent to whichthe variation of the measure is due to the 'true' underlying phenomenon versus randomeffects. High reliability is evident if a measure is stable over time or equivalent with identicalmeasures (Fonrell, 1992). Signal-to-noise in the items that make up the index (in terms of variances) is about 4 to 1.Predictive power and financial implications of ACSIAn important part of the ACSI is its ability to predict economic returns. The model, ofwhich the ACSI is a part, uses two proxies for economic returns as criterion variables: (1)customer retention (estimated from a non-linear transformation of a measure of repurchase likelihood); and (2) price tolerance (reservation price). The items included in the index areweighted in such a way that the proxies and the ACSI are maximally correlated (subject tocertain constraints). Unless such weighting is done, the index is more likely to include mattersthat may be satisfying to the customer, but for which he or she is not willing to pay.The empirical evidence for predictive power is available from both the Swedish data andthe ACSI data. Using data from the Swedish Barometer, a one-point increase in the SCSBeach year over 5 years yields, on the average, a 6.6% increase in current return-on-investment (Anderson et al., 1994). Of the firms traded on the Stockholm Stock Market Exchange, it isalso evident that changes in the SCSB have been predictive of stock returns.A basic tenet underlying the ACSI is that satisifed customers represent a real, albeit intangible, economic asset to a ifrm. By deifnition, an economic asset generates future incomestreams to the owner of that asset. Therefore, if customer satisfaction is indeed an economicasset, it should be possible to use the ACSI for prediction of company ifnancial results. It is,of course, of considerable importance that the ifnancial consequences of the ACSI arespecified and documented. If it can be shown that the ACSI is related to ifnancial returns,then the index demonstrates external validity.The University of Michigan Business School faculty have done considerable research onS876 E. W. ANDERSON & C. FORNELLthe linkage between ACSI and economic returns, analyzing both accounting and stock market returns from measured companies. The pattern from all of these studies suggests a statistically strong and positive relationship. Speciifcally:?There is a positive and significant relationship between ACSI and accounting return_ on-assets (Fornell et al., 1995).?There is a positive and signiifcant relationship between the ACSI and the market valueof common equity (Ittner & Larcker, 1996). When controlling for accounting book values of total assets and liabilities, a one-unit change (on the 0-100-point scale used for the ACSI) is associated with an average of US$646 million increase in market value. There are also significant and positive relationships between ACSI and market-to-book values and price/earnings ratios. There is a negative relationship between ACSI and risk measures, implying that firms with high loyalty and customersatisfactionhave less variability and stronger financial positions.?There is a positive and significant relationship between the ACSI and the long-term adjusted financial performance of companies. Tobin's Q is generally accepted as the best measure of long-term performance. It is deifned as the ratio of a firm's present value of expected cash lfows to the replacement costs of its assets. Controlling for other factors, ACSI has a significant relationship to Tobin's Q (Mazvancheryl et al.,1999).?Since 1994, changes in the ACSI have correlated with the stock market (Martin,1998). The current market value of any security is the market's estimate of the discounted present value of the future income stream that the underlying asset will generate. If the most important asset is the satisfaction of the customer base, changes in ACSI should be related to changes in stock price. Until 1997, the stock market went up, whereas ACSI went down. However, in quarters following a sharp drop in ACSI, the stock market has slowed. Conversely, when the ACSI has gone down only slightly, the following quarter's stock market has gone up substantially. For the 6 years of ACSI measurement, the correlation between changes in the ACSI and changes in the Dow Jones industrial average has been quite strong. The interpretation of this relationship suggests that stock prices have responded to downsizing, cost cutting and productivity improvements, and that the deterioration in quality (particularly in the service sectors) has not been large enough to offset the positive effects. It also suggests that there is a limit beyond which it is unlikely that customers will tolerate further decreases in satisfaction. Once that limit is reached (which is now estimated to be approximately —1.4% quarterly decline in ACSI), the stock market will not go up further.ACSI scores of approximately 130 publicly traded companies display a statistically positive relationship with the traditional performance measures used by firms and security analysts (i.e. return-on-assets, return-on-equity, price—earnings ratio and the market-to-book ratio). In addition, the companies with the higher ACSI scores display stock price returns above the market adjusted average (Ittner & Larcker, 1996). The ACSI is also positively correlated with 'market value added'. This evidence indicates that the ACSI methodology produces a reliable and valid measure for customer satisfaction that is forward-looking and relevant to a company's economic performance.CoverageThe ACSI measures a substantial portion of the US economy. In terms of sales dollars, it is approximately 30% of the GDP. The measured companies produce over 40%, but the ACSIFOUNDATIONS OF ACSI S877measures only the sales of these companies to household consumers in the domestic market. The economic sectors and industries covered are discussed in Chapter III. Within each industry, the number of companies measured varies from 2 to 22.The national index and the indices for each industry and sector are relfective of the total value (quality times sales) of products and services provided by the ifrms at each respective level of aggregation. Relative sales are used to determine each company's or agency's contribution to its respective industry index. In turn, relative sales by each industry are used to determine each industry's contribution to its respective sector index. To calculate the national index, the percentage contributions of each sector to the GDP are used to top-weight the sector indices. Mathematically, this is deifned as:Index for industry i in sector s at time t = ES f i;If _S S ,, S I Index for sector s at time t =I g = E ,whereSr…, = sales by ifrm f, industry i, sector s at time t= index for firm f, industry i, sector s at time tandSit = E S,, = total sales for industry i at time tS, = E S i , = total sales for sector s at time t ,The index is updated on a quarterly basis. For each quarter, new indices are estimated for one or two sectors with total replacement of all data annually at the end of the third calendar quarter. The national index is comprised of the most recent estimate for each sectorT S National index at time t — ____________ E 4, V s9t t =T -3 s W,13where I s , = 0 for all t in which the index for a sector is not estimated, and I = I for all ,, quarters in which an index is estimated. In this way, the national index represents company, industry and sector indices for the prior year.SimplicityGiven the complexity of model estimation, the ACSI maintains reasonable simpilcity. It is calibrated on a 0-100 scale. Whereas the absolute values of the ACSI are of interest, much of the index's value, as with most other economic indicators, is found in changes over time, which can be expressed as percentages.DiagnosticsThe ACSI methodology estimates the relationships between customer satisfaction and its causes as seen by the customer: customer expectations, perceived quality and perceived value. Also estimated are the relationships between the ACSI, customer loyalty (as measured by customer retention and price tolerance (reservation prices)) and customer complaints. The。

a customer loyalty model for e service context

a customer loyalty model for e service context

A CUSTOMER LOYALTY MODEL FOR E-SERVICE CONTEXTPin LuarnDepartment of Business AdministrationNational Taiwan University of Science and Technologyluarn@.twHsin-Hui LinDepartment of Business AdministrationNational Taiwan University of Science and Technologybrenda@.twABSTRACTWhile the importance of customer loyalty has been recognized in the marketing literature for at least three decades, the conceptualization and empirical validation of a customer loyalty model for e-service context has not been addressed. This paper describes a theoretical model for investigating the three main antecedent influences on loyalty (attitudinal commitment and behavioral loyalty) for e-service context: trust, customer satisfaction, and perceived value. Based on the theoretical model, a comprehensive set of hypotheses were formulated and a methodology for testing them was outlined. These hypotheses were tested empirically to demonstrate the applicability of the theoretical model. The results indicate that trust, customer satisfaction, perceived value, and commitment are separate constructs that combine to determine the loyalty, with commitment exerting a stronger influence than trust, customer satisfaction, and perceived value. Customer satisfaction and perceived value were also indirectly related to loyalty through commitment. Finally, the authors discuss the managerial and theoretical implications of these results.Keywords: Loyalty, e-service, trust, customer satisfaction, perceived value1. IntroductionRetaining customers is a financial imperative for electronic vendor (e-vendor), especially as attracting new customers is considerably more expensive than for comparable, traditional, bricks-and-mortar stores (Reichheld and Schefter, 2000). Understanding how or why a sense of loyalty develops in customers remains one of the crucial management issues of our day. Aaker (1991) has discussed the role of loyalty in the brand equity process and has specifically noted that brand loyalty leads to certain marketing advantages such as reduced marketing costs, more new customers, and greater trade leverage. In increasingly competitive markets, being able to build loyalty in consumers is seen as the key factor in winning market share (Jarvis and Mayo, 1986) and developing sustainable competitive advantage (Kotler and Singh, 1981). While the importance of brand loyalty has been recognized in the marketing literature for at least three decades (Howard and Sheth, 1969), the conceptualization and empirical validation of a loyalty model for e-service context has not been addressed. E-commerce success, especially in the business-to-consumer area, is determined in part by whether consumers show loyalty to a particular e-service provider they cannot touch. Thus, research attention should more fruitfully focus on the development and validation of a loyalty model for e-service context.Recognizing that a vital key to retaining customers is maintaining their trust in the e-vendor (Reichheld and Schefter, 2000), this study investigates customer trust as a primary factor for customer commitment and loyalty. In addition, our study incorporates customer satisfaction and perceived value as additional explanatory variables in understanding the determinants of why online customers show attitudinal commitment and behavioral purchase loyalty to a specific e-service provider. Accordingly, the primary purpose of this study is to explore the factors (i.e., customer satisfaction, trust, and perceived value) that influence attitudinal commitment and purchase loyalty in an e-service environment. This paper is structured as follows. First, we discuss the concept of e-service. Subsequently, the study defines the constructs of interest and develops a model of the relationships between the constructs. A comprehensive review of the marketing literature provides a theoretical basis for clarifying what the constructs mean. Next, hypotheses were proposed concerning these relationships. The methods, measures, and results of this study were then presented. Finally, the results were discussed in terms of their implications for research and managerial activity. Based on the findings of this study, Internet marketers will be able to justify expenditures, which promote increased online customer loyalty.Page 1562. Conceptualization of E-ServicesThe concept of e-service seems to be inextricably linked to e-business. Several conceptualization of e-service have been offered in the literature (de Ruyter et al., 2001; van Riel et al., 2001; Featherman and Pavlou, 2002; Pollard, 2003). As de Ruyter et al. (2001) contend, the self-service kind of marketplace environment has already made more and more customers look for company access and customer support through the Internet. In addition to the provision of peripheral service such as customer support, an increasing number of service providers are using electronic ways to distributing their core products/services (de Ruyter et al., 2001). Featherman and Pavlou (2002) also suggest that e-services enable electronic communication, information gathering, transaction processing and data interchange within and between businesses across time and space. Turban et al. (2002) defined pure e-commerce as a case where the product, the agent, and the process are all digitized. In most cases, products that are traded must be physically delivered to the customer, making pure e-commerce impossible. However, with the digital product/service industry, pure e-commerce can be used in most cases, since the industry deals with contents that can be digitized easily. When companies deal with pure e-commerce, the potential advantages are the greatest, since automating the entire process (including product/service delivery) can result in a substantial cost reduction. Delivering value-added, interactive services to customers on-line, in real time, in a shared community of users seems increasingly important to gaining a competitive edge in the electronic marketplace by strengthening relationships with key constituencies (de Ruyter et al., 2001). Consequently, banks, travel agencies, airlines, car rental companies, job placement agencies, real estate agencies, insurance agencies, brokerage houses, online publishers (e.g., newspapers, magazines, music, videos, games, and other digitizable information), management consulting companies and educational institutions are increasingly opting for online service delivery to meet e-customer demand (Forrest and Mizerski, 1996; Turban et al., 2002). Aforementioned issues lead us to compose the following conceptualization of e-service: “E-service is an interactive content-centered and Internet-based customer service, driven by customer and integrated with related organizational customer support processes and technologies with the goal of strengthening the customer-service provider relationship” (de Ruyter et al., 2001, p.185). With the rapid growth and proliferation of e-service, it seems, therefore, imperative to know what factors influence customer attitudinal commitment and repeat purchase behaviors towards e-service.3. Research Model and HypothesesGiven that an e-service in the Internet context is an electronic channel through which consumers received products/services, trust in electronic channel, customer satisfaction with e-service, and perceived value of products/services provided by an e-service vendor should work together to influence the decision to participate in repeat purchase with a particular e-service vendor. The research model used to guide the study is shown in Figure 1, which suggests that customer satisfaction, trust, and perceived value are all directly and indirectly related to loyalty, with the indirect path occurring through commitment. This section elaborates on the theory base and derives the hypotheses.3.1 Definitions and ModelsOliver (1999) defines brand loyalty as “a deeply held commitment to rebuy or repatronize a preferred product/service consistently in the future, thereby causing repetitive same-brand or same brand-set purchasing, despite situational influences and marketing efforts having the potential to cause switching behavior.” This definition emphasizes the two different aspects of brand loyalty that have been described in prior studies on the concept--behavioral and attitudinal (Aaker, 1991; Jacoby and Chestnut, 1978; Oliver, 1999; Jacoby and Kyner, 1973; Day, 1969). Still, this view is not universally held, as others suggest that the two constructs are either not related (Oliva et al., 1992) or that they are synonymous and represent each other (Assael, 1987). Chaudhuri and Holbrook (2001) suggest that behavioral, or purchase, loyalty consists of repeated purchases of the brand, whereas attitudinal brand loyalty includes a degree of dispositional commitment in terms of some unique value associated with the brand. Hence, an intermediate view on the matter asserts the constructs are related, yet by definition are distinct, with commitment leading to loyalty (Beatty et al., 1988). In this study, commitment is defined as a consumer’s psychological attachment to an e-service that develops before a customer would be able to determine that their repeat purchase behavior was derived from a sense of loyalty (Beatty and Kahle, 1988). Loyalty is defined as the intention of a consumer to repurchase products/services through a particular e-service vendor.Trust has been conceptualized by previous research in a variety of ways, both theoretically and operationally, and researchers have long acknowledged the confusion in the field (e.g., Lewis and Weigert, 1985; McKnight et al., 1998, 2002; Shapiro, 1987). In e-commerce contexts, the diversity in trust conceptualization is also evident (Gefen et al., 2003). Prior studies have viewed trust as (a) trusting beliefs (Doney and Cannon, 1997; Ganesan, 1994; Gefen and Silver, 1999; McKnight et al., 1998, 2002; Gefen et al., 2003) or (b) trusting intentions (Gefen, 2000; Hosmer, 1995; Moorman et al., 1992; Mayer et al., 1995; McKnight et al., 1998, 2002). In e-commerce environment, trusting beliefs, which have also been referred to as “trustworthiness” by Mayer et al. (1995), are consumers’ perceptions of particular attributes of e-vendors, including the abilities, integrity, andPage 157benevolence exhibited by the vendors when they handle the consumers’ transactions (McKnight et al., 2002; Kim and Benbasat, 2003). Trusting intentions means “the truster is securely willing to depend, or intends to depend, on the trustee” (McKnight et al., 2002, p.337). Most researchers agree that trusting beliefs positively influence trusting intentions (McKnight et al., 1998, 2002; Kim and Benbasat, 2003; Gefen et al., 2003; Jarvenpaa and Tractinsky, 1999; Mayer and Davis, 1999; Mayer et al., 1995). Commonly discussed trust-related behavioral intentions in electronic commerce include sharing personal information, making a one time or repeating purchase, or acting on information provided by an e-vendor. Although some researchers have treated trust as a unitary concept (e.g., Rotter, 1971), most now agree that trust is multidimensional (Mayer et al., 1995; Rousseau et al., 1998; McKnight et al., 2002). In consonance with the definition of trust adopted by Gefen et al. (2003), this study defines trust is a set of specific beliefs dealing primarily with the integrity (trustee honesty and promise keeping), benevolence (trustee caring and motivation to act in the truster’s interest), competence (ability of trustee to do what the truster needs), and predictability (trustee’s behavioral consistency) of a particular e-service vendor (McKnight et al., 2002; Doney and Cannon, 1997; Ganesan, 1994; Gefen and Silver, 1999; Giffin, 1967; Larzelere and Huston, 1980). Gefen et al. (2003) suggest that this definition relies on separation between trust and actual behavioral intentions (e.g., repeat purchase intentions) in the ongoing economic relationship of customers and e-vendors, and that this trust conceptualization is akin to that of other studies dealing with ongoing economic relationships (e.g., Crosby et al., 1990; Gefen, 2002), including those with e-vendors (Jarvenpaa et al., 2000). We also included “predictability” dimension into our trust conceptualization because it is more relevant to an ongoing trust model than to an initial trust model (McKnight et al., 1998, 2002).Traditionally, user satisfaction was employed as a label of IS success (Bailey and Pearson, 1983), and therefore frequently measured in past studies. Both user information satisfaction (UIS) and end-user computing satisfaction (EUCS) scales have been used to measure user satisfaction indirectly through information quality, system quality, and other variables (Bailey and Pearson, 1983; Ives, et al., 1983; Doll and Torkzadeh, 1988). Based on seven indirect measuring factors of overall level of Web customer satisfaction, Wang et al. (2001) developed a 21-item instrument for measuring customer satisfaction with a particular Web site that markets digital products/services. However, the concept of IS and/or e-commerce success has been refined in the context of integrated IS and/or e-commerce success models, including DeLone and McLean (1992, 2003), Seddeon (1997), and Molla and Licker (2001) models, to develop causal relations between antecedents (indirect measures) of overall user/customer satisfaction (e.g., system quality and information quality), overall user/customer satisfaction, and consequents of overall user/customer satisfaction (e.g., individual impact and customer loyalty). Given our interest in capturing a overall measure of customer satisfaction with e-service and concerns about survey length and respondent convenience, the conceptualization of customer satisfaction adopted here therefore corresponds to the summary affective response or feeling of a customer in relation to her/his experience with all aspects of an e-service put in place by an organization to market its products and services (Molla and Licker, 2001).It is widely known that perceived value, the potential key determinant of loyalty, is composed of a “get” component--that is, the benefits a buyer derives from a seller’s offering--and a “give” component--that is, the buyer’s monetary and nonmonetary costs of acquiring the offering (e.g., Dodds et al., 1991; Zeithaml, 1988). This study focuses primarily on product and service quality, including Web site quality, as the get component and on time and money spent as the give component (Grewal et al., 1998; Lichtenstein et al., 1990; Zeithaml, 1988; Parasuraman and Grewal, 2000).3.2 HypothesesAs mentioned previously, it has been suggested that loyalty includes some degree of predispositional commitment toward a brand. Therefore, our notion of customer loyalty in this study includes both attitudinal commitment and behavioral purchase loyalty (see Figure 1). Based on the emerging theory of brandPage 158commitment in relationship marketing (e.g., Fournier, 1998; Gundlach et al., 1995; Morgan and Hunt, 1994; Parasuraman and Grewal, 2000; Chaudhuri and Holbrook, 2001), we propose that trust, customer satisfaction, and perceived value are each related to both commitment and loyalty, consistent with the concept of one-to-one marketing relationships.Trust is vital in many business relationships (Dasgupta, 1988; Fukuyama, 1995; Gambetta, 1988; Gulati, 1995; Kumar et al. 1995; Ganesan, 1994; Moorman et al. 1992), especially those containing an element of risk, including interacting with an e-vendor (Reichheld and Schefter, 2000; Gefen et al., 2003). Lacking effective regulation in the Internet context, consumers have to trust that the e-service vendor will not engage in harmful opportunistic behaviors, or else the overwhelming social complexity will cause them to avoid purchasing (Gefen, 2000). Some researchers have suggested that online customers generally stay away from e-vendors whom they do not trust (Jarvenpaa and Tractinsky, 1999; Reichheld and Schefter, 2000). Following McKnight et al. (1998, 2002), we integrate trust-related constructs mentioned earlier within the broad framework of the Theory of Reasoned Action (TRA) (Fishbein and Ajzen, 1975). TRA posits that beliefs lead to attitudes, which lead to behavioral intentions, which lead to the behavior itself. Applying the viewpoints of TRA, we posit that trusting beliefs (perceptions of specific e-service vendor attributes) lead to trust-related attitude (i.e., attitudinal commitment), which in turn result in intentions to engage in trust-related behaviors with a specific e-vendor (i.e., behavioral loyalty). As mentioned earlier, most researchers also agree that trusting beliefs directly influence trusting intentions (e.g., repeat purchase intentions) (McKnight et al., 1998, 2002; Kim and Benbasat, 2003; Gefen et al., 2003). We did not measure actual behavior in this study because prior research has confirmed a strong correlation between behavioral intentions and actual behavior (Sheppard et al., 1998; Venkatesh and Davis, 2000).In the marketing literature, Morgan and Hunt (1994) also suggest that brand trust leads to brand loyalty and commitment because trust creates exchange relationships that are highly valued. Thus, loyalty or commitment underlies the ongoing process of continuing and maintaining a valued and important relationship that has been created by trust (Chaudhuri and Holbrook, 2001). We suggest that trust will contribute to both commitment and loyalty. Trusted e-services should be purchased more often and should evoke a higher degree of attitudinal commitment. Thus, the following hypotheses are tested:H1a: Trust will positively affect loyalty.H1b: Trust will positively affect commitment.Dick and Basu (1994) have proposed that brand loyalty should be greater under conditions of more positive emotional mood or affect. The brands that make consumers happy or joyful or affectionate should prompt greater behavioral (purchase) loyalty and attitudinal commitment (Chaudhuri and Holbrook, 2001). Similarly, consumer satisfaction is believed to mediate consumer learning from prior experience and to explain key postpurchase behaviors, such as complaining, word of mouth, repurchase intention, and product usage (Oliver, 1980; Westbrook and Oliver, 1991). Indeed, Wang et al. (2001) has suggested that Web customer satisfaction have a significant influence on repurchase intention and postpurchase complaint. Therefore, we test the following hypotheses:H2a: Customer satisfaction will positively affect loyalty.H2b: Customer satisfaction will positively affect commitment.Perceived value is the perceived e-service utility relative to its monetary and nonmonetary costs, assessed by the consumer and based on simultaneous considerations of what is received and what is given up to received it. Clearly, quality of product/service and Web site is a logical driver of perceived value. In instances where the core of what the e-vendor offers to the customers is a digitized product/service (e.g., online banking, content aggregators, and online stock trading), there is no tangible product and, as such, it is difficult for consumers to differentiate product quality, service quality, and Web site quality. Even in instances where the e-vendor offers to the buyers is a physical product, superior presale and postsale service rendered by the e-vendor can add to the benefits received (get component) and also reduce the customer’s nonmonetary cost such as time, effort, and mental stress (give component). Furthermore, part of the “give” and “get” of the experience also involves the Web site quality. The online consumer gives time, cognition and effort to the experience of interacting with the Web site, and gets an experience enabled by the Web site that hopefully makes it easy to find needed/wanted products, to checkout quickly and to received confirmation about all important aspects of the purchase, such as order-confirmation and delivery-tracking. In this regard, the product quality, service quality, and Web site quality are also intertwined with each other.Cumulative insights from prior studies support the general notion that perceived value contributes to customer loyalty (e.g., Parasuraman and Grewal, 2000; Dodds et al., 1991; Grewal et al., 1998; Voss et al., 1998). The value-loyalty linkage is also consistent with Reichheld’s (1996) work on loyalty. Regardless ofPage 159whether the core offerings of an e-vendor are products or services, customer perceived value of products/services and Web quality provided by an e-vendor should be positively related to customer loyalty and commitment. Parasuraman and Grewal (2000) suggest that the influence of perceived value on loyalty is an issue in need of more empirical research. Therefore, this study tests the following hypotheses: H3a: Perceived value will positively affect loyalty.H3b: Perceived value will positively affect commitment.Based on the TRA mentioned earlier, attitudinal commitment positively influences intentions to engage in repeat purchase behaviors with a specific e-vendor. Previous studies of purchase behavior (Beatty and Kahle, 1988), consumer expectations (Kelley and Davis, 1994), and advertising effectiveness (Robertson, 1976) all attest to commitment’s ability to affect a variety of outcomes. Kiesler and Sakumura (1966) described customer commitment as a stable preference that was bound by an attitude of resistance to change. Crosby and Taylor (1983) also suggest that the “tendency to resist changing preference” provides the principle evidence of commitment. As the principle evidence of commitment, resistance to change is central to a variety of outcomes, the foremost of which is loyalty (Jacoby and Kyner, 1973). Therefore, this study tests the following hypothesis: H4: Commitment will have a positive effect on LoyaltyIn sum, previous researches have implied that attitudinal commitment and behavioral loyalty should be the product of trust in e-service, customer satisfaction with e-service, and perceived value of products/services provided by an e-service vendor. But these perspectives has been examined independently by IS and marketing researcher. Integrating these perspectives and empirically examining the factors that build customer loyalty in an e-service context that lacks the typical human interaction advances our understanding of these constructs and their linkage to repeat Web purchase behavior.4. Methodology4.1 MeasuresTo ensure the content validity of the scales, the items selected must represent the concept about which generalizations are to be made. Therefore, items selected for the constructs were mainly adapted from prior studies to ensure content validity. Four items for the trust construct were adapted from Gefen et al. (2003). The items to measure customer satisfaction were taken from previous measures of overall level of user satisfaction or Web customer satisfaction (Wang et al., 2001; Doll et al., 1988; Palvia, 1996; Rai et al., 2002). Perceived value was measured by three items adapted from Lassar et al. (1995). Items for the loyalty were taken from the previous validated inventory (Chaudhuri and Holbrook, 2001) and modified to fit the e-service context studied. Finally, commitment was measured by four items adapted from the Pritchard et al. (1999) “resistance to change” scales. Likert scales (1~7), with anchors ranging from “strongly disagree” to “strongly agree” were used for all questions. Pre-testing and pilot testing of the measures were conducted by selected consumers from the B2C e-commerce field, as well as experts in the e-commerce research area. The items were modified to make them relevant to the e-service context. The Appendix lists the items used in this study.4.2 SubjectsThis study used online traveling services and video on demand (VOD) as the e-service categories of reference because these two categories are among the most popular B2C e-services. Data used to test the research model was gathered from a quota sample of 180 respondents attending an e-commerce exposition and symposium held in Taiwan, with an equal quota of 90 responses from each category of the traveling and VOD e-services. Respondents were asked first whether they had bought the traveling or VOD products/services through the e-service vendors, and if they relied in the affirmative, they were asked to participate in a survey. The screened and qualified respondents self-administered a 16-item questionnaire. The first part of the questionnaire focused on demographic data, while the second part required respondents to name one e-service vendor where they had purchased the product/service in question. This served to anchor the survey to a particular e-service vendor. For each question, respondents were asked to circle the response which best described their level of agreement with the statements.A total of 572 approaches were made to obtain 180 completed surveys. Reasons for nonparticipation were either due to non-usage of the e-service category or a lack of time to complete the survey. 72 percent of the completed surveys were from male respondents. Respondents ranged from 16 to 45 years of age (mean = 32 years). 52 percent had completed one college or university degree.Page 1605. Results5.1 Measurement AssessmentConstruct validity determines the extent to which a scale measures a variable of interest. In this study, we follow the Straub’s (1989) processes of validating instruments in MIS research in terms of convergent validityand discriminant validity. Thus, a principal components factor analysis with varimax rotation was conducted to investigate the distinctions among customer satisfaction, trust, perceived value, commitment, and loyalty. In this study, Bartlett’s test of sphericity (p=0.00) indicated the statistical probability that the correlation matrix has significant correlations among at least some of the variables, and the Kaiser-Meyer-Olkin measure of sampling adequacy (0.872) showed middling sampling adequacy. As shown in Table 1, the five factors emerged with no cross-construct loadings above 0.5, indicating good discriminant validity. The instrument also demonstrated convergent validity with factor loadings exceeding 0.5 for each construct. Consequently, these results confirmthat each of the five constructs is unidimensional and factorially distinct and that all items used to operationalizea particular construct is loaded onto a single factor.Reliability was evaluated by assessing the internal consistency of the items representing each construct using Cronbach’s alpha. The reliability of each construct was as follows: customer satisfaction = 0.90; trust =0.93; perceived value = 0.91; commitment = .94; loyalty = .89. All the values were above 0.8, exceeding the common threshold values recommended by Nunnally (1978).Table 1. Factor Analysis Results: Principal Component ExtractionSatisfaction0.900C30.839C10.832C20.811C40.861T40.858T30.835T20.793T10.866V10.855V30.821V20.873S30.821S20.675S10.719 L10.615 L25.2 Hypothesis TestingThe hypothesized relationships were tested using the multiple regression analysis of SPSS 9.0 for Windows.The average scores of the items representing each construct were used in the data analysis1. The R2 was used to assess the model’s overall predictive fit. Properties of the causal paths, including standardized path coefficients,t-values, and variance explained for each equation in the hypothesized model are presented in Figure 2. In hypotheses H1a, H2a, H3a, and H4, we investigate the influence of trust, customer satisfaction, perceived value,and commitment on loyalty. As expected, trust (β=0.163, t-value=2.707, p<0.01) and customer satisfaction (β=0.219, t-value=3.588, p<0.001) had a strong positive influence on the loyalty. Also, perceived value (β=0.230,t-value=4.237, p<0.001) and commitment (β=0.392, t-value=6.755, p<0.001) had a significant positive effect onthe loyalty. Therefore, hypotheses H1a, H2a, H3a, and H4 were supported. We found that the proposed model explained a significant percentage of variance in loyalty (R2=65.7%, F=value=83.692, p<0.001). According tothe path coefficients shown in Figure 2, commitment exhibited the strongest direct effect on loyalty.Hypotheses H1b, H2b, and H3b examine the paths from trust, customer satisfaction, and perceived value to commitment. Customer satisfaction (β=0.343, t-value=4.580, p<0.001) and perceived value (β=0.302,t-value=4.534, p<0.001) had a significant positive effect on the commitment. However, trust had no significant influence on the commitment (β=0.142, t-value=1.836, p=0.068) at the 0.05 level. Thus, hypotheses H2b and1The covariance matrix used in the data analysis is available from the corresponding author upon request.Page 161。

Empirical processes of dependent random variables

Empirical processes of dependent random variables

2
Preliminaries
n i=1
from R to R. The centered G -indexed empirical process is given by (P n − P )g = 1 n
n
the marginal and empirical distribution functions. Let G be a class of measurabrocesses that have been discussed include linear processes and Gaussian processes; see Dehling and Taqqu (1989) and Cs¨ org˝ o and Mielniczuk (1996) for long and short-range dependent subordinated Gaussian processes and Ho and Hsing (1996) and Wu (2003a) for long-range dependent linear processes. A collection of recent results is presented in Dehling, Mikosch and Sorensen (2002). In that collection Dedecker and Louhichi (2002) made an important generalization of Ossiander’s (1987) result. Here we investigate the empirical central limit problem for dependent random variables from another angle that avoids strong mixing conditions. In particular, we apply a martingale method and establish a weak convergence theory for stationary, causal processes. Our results are comparable with the theory for independent random variables in that the imposed moment conditions are optimal or almost optimal. We show that, if the process is short-range dependent in a certain sense, then the limiting behavior is similar to that of iid random variables in that the limiting distribution is a Gaussian process and the norming √ sequence is n. For long-range dependent linear processes, one needs to apply asymptotic √ expansions to obtain n-norming limit theorems (Section 6.2.2). The paper is structured as follows. In Section 2 we introduce some mathematical preliminaries necessary for the weak convergence theory and illustrate the essence of our approach. Two types of empirical central limit theorems are established. Empirical processes indexed by indicators of left half lines, absolutely continuous functions, and piecewise differentiable functions are discussed in Sections 3, 4 and 5 respectively. Applications to linear processes and iterated random functions are made in Section 6. Section 7 presents some integral and maximal inequalities that may be of independent interest. Some proofs are given in Sections 8 and 9.

Rough Approximation of a perference Relation by Dominance Relations

Rough Approximation of a perference Relation by Dominance Relations
This explains our interest in the rough sets theory (Pawlak, 1982, 1991), which proved to be a useful tool for analysis of vague description of decision situations (Pawlak and Slowinski, 1994). We remember that the rough set concept is founded on the assumption that with every object of the universe of discourse there is associated some information (data, knowledge). For example, if objects are potential projects, their technical and economic characteristics form information (description) about the projects. Objects characterized by the same information are indiscernible (similar) in view of available information about them. The indiscernibility relation generated in this way is the mathematical basis of the rough sets theory. Any set of indiscernible objects is called elementary set. Any subset of the universe can either be expressed precisely in terms of elementary sets or roughly only. In the latter case, this subset can be characterized by two ordinary sets, called lower and upper approximations. The lower approximation contains objects surely belonging to the subset considered; the upper approximation contains objects possibly belonging to the subset considered.

天然多酚类成分缓解高尿酸血症及其机制研究进展

天然多酚类成分缓解高尿酸血症及其机制研究进展

山东科学SHANDONGSCIENCE第37卷第2期2024年4月出版Vol.37No.2Apr.2024收稿日期:2024 ̄02 ̄20基金项目:山东省重点研发计划(2021CXGC010508)作者简介:刘双(1997 )ꎬ男ꎬ硕士ꎬ研究方向为中药活性成分分离及质量评价方法ꎮE ̄mail:lius9709@163.com∗通信作者ꎬ王晓(1971 )ꎬ男ꎬ博士ꎬ研究员ꎬ研究方向为中药资源及质量控制ꎮE ̄mail:wangx@sdas.org天然多酚类成分缓解高尿酸血症及其机制研究进展刘双aꎬbꎬ董红敬aꎬbꎬ陈盼盼aꎬbꎬ王晓aꎬb∗(齐鲁工业大学(山东省科学院)a.山东省分析测试中心山东省大型精密分析仪器应用技术重点实验室ꎻb.药学院山东省高等学校天然药物活性成分研究重点实验室ꎬ山东济南250014)摘要:高尿酸血症(hyperuricemiaꎬHUA)是一种机体中嘌呤类物质代谢紊乱导致血清中尿酸水平升高的一种代谢性疾病ꎬ严重者可导致痛风ꎮHUA的发病机制主要包括酶活失调㊁尿酸转运体表达失衡㊁糖代谢及脂代谢紊乱㊁肠道稳态失衡等ꎮ许多研究报道了天然多酚对高尿酸血症和痛风具有良好的缓解作用ꎮ本文对HUA的发病机制和多酚类成分的降尿酸作用及其机制进行了总结与归纳ꎬ以期为降尿酸药物的研究与开发提供理论依据ꎮ关键词:多酚类成分ꎻ高尿酸血症ꎻ作用机制ꎻ研究进展中图分类号:R285㊀㊀㊀文献标志码:A㊀㊀㊀文章编号:1002 ̄4026(2024)02 ̄0012 ̄08开放科学(资源服务)标志码(OSID):ResearchprogressonthemechanismsbywhichnaturalphenoliccompoundsalleviatehyperuricemiaLIUShuangaꎬbꎬDONGHongjingaꎬbꎬCHENPanpanaꎬbꎬWANGXiaoaꎬb∗(a.ShandongProvincialKeyLaboratoryofAppliedTechnologyofSophisticatedAnalyticalInstrumentsꎬShandongAnalysisandTestCenterꎻb.ShandongProvincialKeyLaboratoryofNaturalActivePharmaceuticalConstituentsResearchinUniversitiesꎬSchoolofPharmaceuticalSciencesꎬQiluUniversityofTechnology(ShandongAcademyofSciences)ꎬJinan250014ꎬChina)AbstractʒHyperuricemia(HUA)isametabolicdisordercausedbythephysiologicdisordersinpurinemetabolismꎬresultinginincreasedserumuricacidlevelsꎬwhichcanleadtogoutinseverecases.HUApathogenesisprimarilyinvolvesenzymedysfunctionꎬuratetransporterexpressiondysregulationꎬglucoseandlipidmetabolismdisordersꎬandintestinalhomeostasisdisruption.Numerousstudieshavereportedtheeffectivenessofnaturalpolyphenolsinalleviatinghyperuricemiaandgout.ThisarticlesummarizesHUApathogenesisandthemechanismsofactionofpolyphenoliccompoundsinreducinguricacidꎬtoprovideatheoreticalbasisfortheresearchanddevelopmentofuricacid ̄loweringdrugs.Keywordsʒpolyphenolsꎻhyperuricemiaꎻmechanismofactionꎻresearchprogress㊀㊀高尿酸血症(hyperuricemiaꎬHUA)是一种由体内嘌呤类物质代谢紊乱导致血清中尿酸水平升高的一种代谢性疾病[1 ̄2]ꎮ近年来ꎬ我国HUA的发病率呈显著上升趋势ꎬ2015 2016年ꎬ我国成年人HUA发病率为11.1%ꎬ2018 2019年ꎬ发病率为14.0%[3]ꎮ研究表明血中尿酸水平的持续升高与糖尿病㊁高脂血症㊁慢性肾脏疾病㊁心血管疾病的风险增加密切相关[4]ꎬ严重者可导致痛风ꎮ痛风的主要发病机制为单钠尿酸盐(MSU)晶体在关节及其周围组织内持续沉积ꎬ引起关节疼痛[5]ꎮ目前ꎬ非甾体抗炎药㊁糖皮质激素㊁秋水仙碱㊁别嘌醇㊁非布司他等为痛风的临床常用药物ꎬ然而这些药物存在胃肠道㊁肾脏㊁心脏毒性及超敏反应等多种不良反应[6]ꎮ因此控制尿酸水平药物的研究成为目前开发重点和热点ꎮ天然多酚类成分是一类化学结构以酚羟基为主的次生代谢产物ꎬ具有抗氧化㊁抗炎㊁免疫调节㊁抗过敏㊁抗动脉粥样硬化㊁抗微生物㊁抗血栓形成㊁调节血糖㊁心脏保护和抗肿瘤等多种药理活性[7 ̄9]ꎮ同时ꎬ多种多酚类成分已被报道具有降尿酸的作用ꎬ本文基于国内外研究进展对高尿酸血症发病及多酚类成分的降尿酸机制进行综述ꎬ以期为降尿酸药物的研究与开发提供理论依据ꎮ1㊀高尿酸血症的发病机制1.1㊀酶活失调人体内尿酸的生成涉及多种酶的参与ꎬ其主要过程如图1所示ꎮ嘌呤核苷磷酸化酶(PNP)是催化形成次黄嘌呤的关键酶ꎬPNP可以催化肌酐分解为次黄嘌呤[10]ꎮ随后ꎬ黄嘌呤氧化酶(XOD)作为机体内尿酸生成的关键酶ꎬ可将次黄嘌呤催化氧化成中间产物黄嘌呤ꎬ并进一步将黄嘌呤氧化成尿酸[11]ꎮ当XOD活性失调时ꎬ较高活性的XOD将加速催化次黄嘌呤及黄嘌呤的氧化ꎬ导致机体尿酸水平持续升高ꎬ产生高尿酸血症ꎮ图1㊀酶催化尿酸的生成过程Fig.1㊀Enzymescatalyzetheprocessofuricacidproduction1.2㊀尿酸转运体表达失衡人体内尿酸的排泄主要通过肾脏(约为2/3)ꎬ少部分通过肠道(约为1/3)[12]ꎬ其中肾脏中尿酸转运体调控尿酸重吸收和分泌的动态平衡ꎬ在尿酸排泄过程中发挥着重要作用[13]ꎮ尿酸转运体主要分为尿酸重吸收转运蛋白ꎬ包括尿酸盐转运蛋白1(eecombinanturatetransporter1ꎬURAT1)㊁葡萄糖转运体9(glucosetransporter9ꎬGLUT9)㊁有机阴离子转运蛋白4(organicaniontransporter4ꎬOAT4)和OAT10等ꎬ以及尿酸分泌转运蛋白ꎬ包括人腺苷三磷酸结合盒转运体G2(humanATP ̄bindingcassettetransporterG2ꎬABCG2)㊁OAT1㊁OAT3㊁钠依赖性磷酸盐转运蛋白1(sodium ̄dependentphosphatetransporter1ꎬNPT1)和NPT4等[14]ꎮ其中ꎬ尿酸重吸收转运蛋白的过高表达会引起尿酸重吸收异常ꎬ导致血清尿酸水平过高ꎻ尿酸分泌转运蛋白的表达过低会引起肾尿酸分泌减少ꎬ出现排泄不足ꎬ使血清尿酸水平升高ꎮ据统计ꎬ90%的高尿酸血症患者都会出现肾脏排泄和尿酸转运体表达失衡的情况[15]ꎮ1.3㊀糖代谢和脂代谢紊乱糖代谢和脂代谢紊乱均会引起高尿酸血症ꎮ果糖水平升高和胰岛素生物效应降低是糖代谢紊乱的主要表现形式ꎬ其中ꎬ果糖的代谢主要是在果糖激酶的作用下发生磷酸化反应生成果糖 ̄1 ̄磷酸ꎬ该过程会消耗大量ATP且不存在负反馈调节ꎬ果糖水平升高ꎬ将会使ATP的消耗量增加ꎬ进而激活嘌呤代谢酶ꎬ使尿酸的生成量增加ꎮ果糖还可以介导还原型辅酶Ⅱ的激活ꎬ阻止肠道中的尿酸排泄ꎬ导致机体内尿酸升高[16]ꎮ脂代谢紊乱会导致脂肪细胞肥大且数量增多ꎬ使其分泌的瘦素㊁抵抗素及脂联素等激素的表达异常ꎬ进而影响胰岛素生物效应ꎬ导致胰岛素抵抗ꎬ高含量的胰岛素可以使肾小管Na+ ̄H+的交换增加ꎬ促进肾小管的重吸收ꎬ在URAT1的作用下ꎬ机体对尿酸的重吸收增加ꎬ排泄减少ꎬ引起高尿酸血症及痛风的发作[17]ꎮ此外ꎬ脂代谢紊乱会导致内脏脂肪积累ꎬ造成新陈代谢中游离脂肪酸水平升高ꎬ进而刺激脂肪酸的合成ꎬ影响嘌呤的合成过程ꎬ促使甘油三酯的合成以及尿酸的产生[18]ꎮ同时ꎬ甘油三酯的升高会消耗更多的ATPꎬ同时引起炎症反应和氧化应激ꎬ进而增加尿酸的生成量ꎮ此外ꎬ脂肪分解产生的中间代谢产物酮体会阻碍尿酸的排泄ꎬ间接使尿酸的水平升高ꎬ引起高尿酸血症[19]ꎮ1.4㊀肠道稳态失衡研究表明多种肠道菌群可以降解嘌呤类成分ꎬ进而调节尿酸的生成ꎬ例如ꎬ肠道中的加氏乳杆菌PA ̄3可以吸收和利用嘌呤ꎬ从而减少嘌呤的肠道吸收ꎬ以降低血清中尿酸的水平[20]ꎻ肠致病性大肠杆菌和产志贺毒素性大肠杆菌可以促使XOD的释放ꎬ促进次黄嘌呤和黄嘌呤转化为尿酸[21]ꎻ乳酸杆菌DM9218可通过抑制XOD的活性ꎬ降低血清中尿酸的水平[22]ꎻ罗伊氏乳杆菌TSR332和发酵乳杆菌TSF331可以降解嘌呤ꎬ以缓解尿酸的生成过程[23]ꎮ有些肠道菌群产生的代谢物可以直接或间接调节尿酸的代谢进而调控尿酸水平ꎬ例如ꎬ乳酸杆菌和假单胞菌可以产生SCFAs(短链脂肪酸)ꎬ进而促进尿酸的分解和排泄[24]ꎻ乳酸杆菌OL ̄5㊁植物乳杆菌Mut ̄7和植物乳杆菌Dad ̄13等肠道菌群中含有较高活性的尿酸酶ꎬ可促进尿酸的分解[25]ꎮ肠道菌群也会通过影响氨基酸代谢ꎬ引发高尿酸血症[26]ꎮ综上可见ꎬ肠道菌群稳态被破坏后ꎬ有益菌和有害菌群失调ꎬ明确的分工被打破ꎬ进而导致嘌呤㊁尿酸及氨基酸等的代谢异常ꎬ引发高尿酸血症ꎮ2㊀多酚类成分降尿酸作用及机制多种多酚类成分已被证实具有降尿酸的作用ꎬ如咖啡酸㊁绿原酸㊁菊苣酸㊁迷迭香酸及芥子酸等(图2)ꎮ图2㊀多酚类成分的化学结构式Fig.2㊀Thechemicalstructureofphenoliccompounds2.1㊀抑制尿酸生成酶的活性多酚类成分可以抑制XOD的活性ꎬ进而调节次黄嘌呤和黄嘌呤的催化氧化ꎬ减少机体尿酸的生成量ꎮ多种多酚类成分在体内外表现出良好的XOD抑制活性ꎬ如咖啡酸[27]㊁绿原酸[28]㊁菊苣酸[29]㊁迷迭香酸[30]㊁芥子酸[31]㊁阿魏酸[32]㊁没食子酸[33]㊁儿茶素[34]㊁白藜芦醇[35]㊁大黄酸[36]㊁鞣花酸[37]㊁5 ̄O ̄咖啡酰莽草酸[38]等ꎮ这是由于多酚类成分含有较多的电负性基团ꎬ能够与XOD之间发生较强的相互作用ꎮ2.2㊀恢复尿酸转运体的表达平衡尿酸转运体的动态平衡会影响尿酸的代谢ꎮ多酚类成分可以上调尿酸分泌转运蛋白水平并下调尿酸重吸收转运蛋白水平以促进机体尿酸排泄过程ꎬ降低机体尿酸水平ꎬ缓解高尿酸血症ꎮ例如ꎬ咖啡酸可通过下调URAT1和GLUT9的水平ꎬ上调OAT1㊁UAT和ABCG2的水平ꎬ恢复尿酸重吸收和排泄的动态平衡[27]ꎮ绿原酸可以通过上调肾脏和回肠中尿酸分泌蛋白的表达ꎬ下调URAT1和GLUT9的水平ꎬ抑制尿酸的重吸收过程ꎬ降低机体尿酸水平[39 ̄40]ꎮ没食子酸可以有效地下调URAT1和GLUT9的表达减少机体对尿酸的重吸收过程ꎬ上调ABCG2㊁OAT1和OAT3的表达提高机体对尿酸的排泄过程[41]ꎮ白藜芦醇可以降低URAT1的表达ꎬ抑制肾脏中尿酸的重吸收过程ꎬ以降低机体尿酸水平[42]ꎮ2.3㊀恢复糖代谢及脂代谢紊乱多酚类成分可以通过调节糖代谢及脂代谢紊乱ꎬ降低机体尿酸水平并缓解高尿酸血症ꎮ例如ꎬ咖啡酸可以下调炎症标志物和氧化应激参数ꎬ以逆转脂代谢和糖代谢紊乱ꎬ进而降低尿酸水平㊁缓解高尿酸血症[43]ꎮ阿魏酸可以通过减轻脂肪沉积㊁氧化应激和炎症反应ꎬ恢复多种代谢紊乱ꎬ抑制尿酸生成ꎬ进而改善高尿酸血症[44]ꎮ白藜芦醇可以通过抑制糖异生过程㊁抑制糖苷酶活性㊁促进胰岛素合成与分泌等途径以调节糖代谢ꎬ进而恢复糖代谢紊乱[35]ꎮ白藜芦醇还可以抑制NOD样受体家族㊁NLRP3㊁TLR4㊁MyD88及NF ̄κB等信号通路ꎬ进而逆转脂质沉积㊁糖原积累㊁炎症反应及肾脏纤维化改变等过程ꎬ下调小鼠肾脏中尿酸转运蛋白的表达ꎬ降低机体尿酸水平[45]ꎮ大黄酸可以逆转果糖诱导的痛风大鼠的肾损伤ꎬ恢复尿酸的代谢ꎬ降低机体尿酸水平[46]ꎮ鞣花酸可以显著降低血清脂质㊁尿酸㊁葡萄糖㊁胰岛素水平㊁ATP ̄柠檬酸裂解酶活性㊁醛缩酶B和脂肪酸合酶活性㊁固醇调节元件结合蛋白1水平改善尿酸水平ꎬ这可能与鞣花酸激活C1q肿瘤坏死因子相关蛋白3和抑制ATP ̄柠檬酸裂解酶活性有关[47]ꎮ2.4㊀调节肠道菌群结构高尿酸血症与肠道菌群存在密切关系ꎬ研究发现许多HUA患者存在肠道菌群紊乱㊁有益菌属丰度下降的现象[48]ꎮ多酚类成分可以改善肠道菌群结构ꎬ提高有益菌丰度ꎬ进而降低机体尿酸水平并缓解高尿酸血症ꎮ其中ꎬ绿原酸可以降低拟杆菌属㊁普雷沃氏菌属及丁酸弧菌的相对丰度ꎬ逆转肠道中的嘌呤代谢和谷氨酸代谢ꎬ缓解高尿酸血症和痛风[40]ꎮ绿原酸还可以提高经黏液真杆菌属㊁肠球菌及粪杆菌属的相对丰度ꎬ逆转血清中三甲胺氧化物水平的升高ꎬ进而减少蛋白激酶B(proteinkinaseBꎬPKB)㊁胞内磷脂酰肌醇激酶(phosphoinositide3kinaseꎬPI3K)和哺乳动物雷帕霉素靶蛋白(mammaliantargetofRapamycinꎬmTOR)等蛋白的表达ꎬ缓解大鼠肾纤维化ꎬ避免高尿酸血症的发生[49]ꎮ2.5㊀抑制炎症反应机体尿酸水平持续升高会诱导MSU晶体的形成ꎬMSU晶体可以通过影响免疫细胞㊁激活Toll样受体(Toll ̄likereceptorsꎬTLRs)和NOD样受体热蛋白结构域相关蛋白3(NOD ̄likereceptorthermalproteindomainassociatedprotein3ꎬNLRP3)受体ꎬ直接诱导炎症因子的分泌失调等途径启动炎症反应ꎬ引起组织或器官损伤ꎮ多酚类成分可以通过抑制炎症反应ꎬ以减轻炎症反应引起的机体损伤ꎬ恢复尿酸正常代谢ꎬ降低机体尿酸水平ꎮ例如ꎬ绿原酸可以通过抑制IL ̄1β㊁IL ̄6和TNF ̄α等促炎细胞因子的分泌ꎬ降低血清尿酸水平ꎬ改善MSU晶体引起的炎症反应和高尿酸症状[28]ꎮ绿原酸还可以降低NLRP3和caspase ̄1的水平ꎬ抑制肾脏中TLR4㊁MyD88及NF ̄κB等信号通路的激活ꎬ调节炎症微环境ꎬ抑制氧化应激ꎬ降低小鼠的尿素氮㊁肌酐㊁谷草转氨酶和谷丙转氨酶的水平ꎬ缓解肝损伤和肾损伤ꎬ恢复尿酸代谢[40]ꎮ菊苣酸可以显著抑制MSU晶体诱导的THP ̄M细胞中人核因子κB抑制蛋白α(NF ̄kappa ̄BinhibitoralphaꎬIκB ̄α)的降解ꎬ阻断NF ̄κB信号通路和NLRP3炎症小体的激活ꎬ下调IL ̄1β㊁TNF ̄α㊁环氧化酶 ̄2(cyclooxygenase ̄2ꎬCOX ̄2)及前列腺素E2(prostaglandinE2ꎬPGE2)的水平ꎬ调控炎症反应ꎬ缓解机体损伤ꎬ恢复尿酸代谢[50]ꎮ芥子酸可以清除自由基ꎬ下调TNF ̄α和IL ̄1β的水平ꎬ调节血清肌酐和尿素氮水平ꎬ减轻肾小管炎症反应以缓解肾损伤ꎬ恢复尿酸代谢并治疗高尿酸血症[31]ꎮ没食子酸可以抑制丙二醛(malondialdehydeꎬMDA)㊁IL ̄6㊁IL ̄1β㊁TNF ̄α㊁转化生长因子β1(transforminggrowthfactorbeta1ꎬTGF ̄β1)㊁COX ̄2和胱抑素C(cystatinCꎬCys ̄C)的表达ꎬ提高肾脏中超氧化物歧化酶(superoxidedismutaseꎬSOD)㊁谷胱甘肽过氧化物酶(glutathioneperoxidaseꎬGSH ̄Px)㊁过氧化氢酶(catalaseꎬCAT)和钠钾ATP酶(Na ̄K ̄ATPaseꎬNKA)的活性ꎬ抑制氧化应激和炎症反应ꎬ缓解以上过程引起的肾损伤ꎬ恢复肾脏的正常排泄ꎬ恢复尿酸的生成和代谢平衡[41]ꎮ儿茶素可以通过抑制氧化应激和炎症反应ꎬ间接地调节高尿酸血症的发作ꎬ如减少IL ̄1β和IL ̄6等促炎细胞因子的分泌与释放ꎬ抑制NLRP3炎症小体的激活ꎬ避免巨噬细胞被过量激活ꎬ减轻炎症反应ꎻ同时清除自由基㊁降低线粒体的活性氧簇(mitochondriaROSꎬmtROS)的生成和细胞内钙水平ꎬ上调B细胞淋巴瘤因子 ̄2(recombinantB ̄cellleukemia/lymphoma2ꎬBc1 ̄2)水平ꎬ恢复线粒体膜电位损伤等ꎬ抑制氧化应激ꎬ缓解高尿酸血症[51]ꎮ大黄酸可以显著降低巨噬细胞中IL ̄1β㊁TNF ̄α和caspase ̄1蛋白酶的产生ꎬ抑制NLRP3蛋白复合体形成使巨噬细胞数量恢复正常水平ꎬ通过恢复炎症微环境稳态ꎬ改善肾损伤ꎬ使尿酸代谢恢复正常[52]ꎮ鞣花酸可以抑制NLRP3炎症小体和TLR4信号通路的激活ꎬ降低caspase ̄1的水平ꎬ减少TNF ̄α和IL ̄18的释放ꎬ抑制炎症反应ꎬ改善高尿酸血症[37]ꎮ丹皮酚可以显著下调TNF ̄α㊁IL ̄1β和IL ̄6的水平ꎬ抑制炎症反应ꎻ降低大鼠关节滑膜组织中p65表达水平和NF ̄κBDNA结合活性ꎬ抑制NF ̄κB的活化ꎬ缓解高尿酸血症和痛风[53]ꎮ此外ꎬ丹皮酚还可以降低IL ̄1β和caspase ̄1的水平ꎬ减少MSU诱导的胱天蛋白募集域(card)和热蛋白样结构域(pyd)的凋亡相关斑点样蛋白(ASC)与pro ̄caspase ̄1之间的相互作用ꎬ降低HAP㊁NLRP3㊁磷酸化κB抑制蛋白激酶(phosphorylatedkappaBinhibitorproteinkinaseELISAKitꎬp ̄IKK)㊁p ̄IκBα和p ̄p65的水平ꎬ抑制p65的DNA结合活性㊁下调磷酸化氨基末端蛋白激酶(phosphorylatedC ̄JUNN ̄terminalproteinkinaseꎬp ̄JNK)㊁磷酸化细胞外调节蛋白激酶(phospho ̄extracellularsignal ̄regulatedkinaseꎬp ̄ERK)和磷酸化p38丝裂原活化蛋白激酶(phosphorylatedp38mitogen ̄activatedproteinkinaseꎬp ̄p38)的水平ꎬ进而抑制NLRP3炎症小体的激活㊁NF ̄κB信号通路及丝裂原活化蛋白激酶(mitogen ̄activatedproteinkinaseꎬMAPK)信号通路的活性ꎬ减轻机体损伤ꎬ促进尿酸排泄[54]ꎮ5 ̄O ̄咖啡酰莽草酸可以降低TNF ̄α㊁IL ̄1β㊁IL ̄6和IL 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Principles of Plasma Discharges and Materials Processing9

Principles of Plasma Discharges and Materials Processing9

CHAPTER8MOLECULAR COLLISIONS8.1INTRODUCTIONBasic concepts of gas-phase collisions were introduced in Chapter3,where we described only those processes needed to model the simplest noble gas discharges: electron–atom ionization,excitation,and elastic scattering;and ion–atom elastic scattering and resonant charge transfer.In this chapter we introduce other collisional processes that are central to the description of chemically reactive discharges.These include the dissociation of molecules,the generation and destruction of negative ions,and gas-phase chemical reactions.Whereas the cross sections have been measured reasonably well for the noble gases,with measurements in reasonable agreement with theory,this is not the case for collisions in molecular gases.Hundreds of potentially significant collisional reactions must be examined in simple diatomic gas discharges such as oxygen.For feedstocks such as CF4/O2,SiH4/O2,etc.,the complexity can be overwhelming.Furthermore,even when the significant processes have been identified,most of the cross sections have been neither measured nor calculated. Hence,one must often rely on estimates based on semiempirical or semiclassical methods,or on measurements made on molecules analogous to those of interest. As might be expected,data are most readily available for simple diatomic and polyatomic gases.Principles of Plasma Discharges and Materials Processing,by M.A.Lieberman and A.J.Lichtenberg. ISBN0-471-72001-1Copyright#2005John Wiley&Sons,Inc.235236MOLECULAR COLLISIONS8.2MOLECULAR STRUCTUREThe energy levels for the electronic states of a single atom were described in Chapter3.The energy levels of molecules are more complicated for two reasons. First,molecules have additional vibrational and rotational degrees of freedom due to the motions of their nuclei,with corresponding quantized energies E v and E J. Second,the energy E e of each electronic state depends on the instantaneous con-figuration of the nuclei.For a diatomic molecule,E e depends on a single coordinate R,the spacing between the two nuclei.Since the nuclear motions are slow compared to the electronic motions,the electronic state can be determined for anyfixed spacing.We can therefore represent each quantized electronic level for a frozen set of nuclear positions as a graph of E e versus R,as shown in Figure8.1.For a mole-cule to be stable,the ground(minimum energy)electronic state must have a minimum at some value R1corresponding to the mean intermolecular separation (curve1).In this case,energy must be supplied in order to separate the atoms (R!1).An excited electronic state can either have a minimum( R2for curve2) or not(curve3).Note that R2and R1do not generally coincide.As for atoms, excited states may be short lived(unstable to electric dipole radiation)or may be metastable.Various electronic levels may tend to the same energy in the unbound (R!1)limit. Array FIGURE8.1.Potential energy curves for the electronic states of a diatomic molecule.For diatomic molecules,the electronic states are specifiedfirst by the component (in units of hÀ)L of the total orbital angular momentum along the internuclear axis, with the symbols S,P,D,and F corresponding to L¼0,+1,+2,and+3,in analogy with atomic nomenclature.All but the S states are doubly degenerate in L.For S states,þandÀsuperscripts are often used to denote whether the wave function is symmetric or antisymmetric with respect to reflection at any plane through the internuclear axis.The total electron spin angular momentum S (in units of hÀ)is also specified,with the multiplicity2Sþ1written as a prefixed superscript,as for atomic states.Finally,for homonuclear molecules(H2,N2,O2, etc.)the subscripts g or u are written to denote whether the wave function is sym-metric or antisymmetric with respect to interchange of the nuclei.In this notation, the ground states of H2and N2are both singlets,1Sþg,and that of O2is a triplet,3SÀg .For polyatomic molecules,the electronic energy levels depend on more thanone nuclear coordinate,so Figure8.1must be generalized.Furthermore,since there is generally no axis of symmetry,the states cannot be characterized by the quantum number L,and other naming conventions are used.Such states are often specified empirically through characterization of measured optical emission spectra.Typical spacings of low-lying electronic energy levels range from a few to tens of volts,as for atoms.Vibrational and Rotational MotionsUnfreezing the nuclear vibrational and rotational motions leads to additional quan-tized structure on smaller energy scales,as illustrated in Figure8.2.The simplest (harmonic oscillator)model for the vibration of diatomic molecules leads to equally spaced quantized,nondegenerate energy levelse E v¼hÀv vib vþ1 2(8:2:1)where v¼0,1,2,...is the vibrational quantum number and v vib is the linearized vibration frequency.Fitting a quadratic functione E v¼12k vib(RÀ R)2(8:2:2)near the minimum of a stable energy level curve such as those shown in Figure8.1, we can estimatev vib%k vibm Rmol1=2(8:2:3)where k vib is the“spring constant”and m Rmol is the reduced mass of the AB molecule.The spacing hÀv vib between vibrational energy levels for a low-lying8.2MOLECULAR STRUCTURE237stable electronic state is typically a few tenths of a volt.Hence for molecules in equi-librium at room temperature (0.026V),only the v ¼0level is significantly popula-ted.However,collisional processes can excite strongly nonequilibrium vibrational energy levels.We indicate by the short horizontal line segments in Figure 8.1a few of the vibrational energy levels for the stable electronic states.The length of each segment gives the range of classically allowed vibrational motions.Note that even the ground state (v ¼0)has a finite width D R 1as shown,because from(8.2.1),the v ¼0state has a nonzero vibrational energy 1h Àv vib .The actual separ-ation D R about Rfor the ground state has a Gaussian distribution,and tends toward a distribution peaked at the classical turning points for the vibrational motion as v !1.The vibrational motion becomes anharmonic and the level spa-cings tend to zero as the unbound vibrational energy is approached (E v !D E 1).FIGURE 8.2.Vibrational and rotational levels of two electronic states A and B of a molecule;the three double arrows indicate examples of transitions in the pure rotation spectrum,the rotation–vibration spectrum,and the electronic spectrum (after Herzberg,1971).238MOLECULAR COLLISIONSFor E v.D E1,the vibrational states form a continuum,corresponding to unbound classical motion of the nuclei(breakup of the molecule).For a polyatomic molecule there are many degrees of freedom for vibrational motion,leading to a very compli-cated structure for the vibrational levels.The simplest(dumbbell)model for the rotation of diatomic molecules leads to the nonuniform quantized energy levelse E J¼hÀ22I molJ(Jþ1)(8:2:4)where I mol¼m Rmol R2is the moment of inertia and J¼0,1,2,...is the rotational quantum number.The levels are degenerate,with2Jþ1states for the J th level. The spacing between rotational levels increases with J(see Figure8.2).The spacing between the lowest(J¼0to J¼1)levels typically corresponds to an energy of0.001–0.01V;hence,many low-lying levels are populated in thermal equilibrium at room temperature.Optical EmissionAn excited molecular state can decay to a lower energy state by emission of a photon or by breakup of the molecule.As shown in Figure8.2,the radiation can be emitted by a transition between electronic levels,between vibrational levels of the same electronic state,or between rotational levels of the same electronic and vibrational state;the radiation typically lies within the optical,infrared,or microwave frequency range,respectively.Electric dipole radiation is the strongest mechanism for photon emission,having typical transition times of t rad 10À9s,as obtained in (3.4.13).The selection rules for electric dipole radiation areDL¼0,+1(8:2:5a)D S¼0(8:2:5b) In addition,for transitions between S states the only allowed transitions areSþÀ!Sþand SÀÀ!SÀ(8:2:6) and for homonuclear molecules,the only allowed transitions aregÀ!u and uÀ!g(8:2:7) Hence homonuclear diatomic molecules do not have a pure vibrational or rotational spectrum.Radiative transitions between electronic levels having many different vibrational and rotational initial andfinal states give rise to a structure of emission and absorption bands within which a set of closely spaced frequencies appear.These give rise to characteristic molecular emission and absorption bands when observed8.2MOLECULAR STRUCTURE239using low-resolution optical spectrometers.As for atoms,metastable molecular states having no electric dipole transitions to lower levels also exist.These have life-times much exceeding10À6s;they can give rise to weak optical band structures due to magnetic dipole or electric quadrupole radiation.Electric dipole radiation between vibrational levels of the same electronic state is permitted for molecules having permanent dipole moments.In the harmonic oscillator approximation,the selection rule is D v¼+1;weaker transitions D v¼+2,+3,...are permitted for anharmonic vibrational motion.The preceding description of molecular structure applies to molecules having arbi-trary electronic charge.This includes neutral molecules AB,positive molecular ions ABþ,AB2þ,etc.and negative molecular ions ABÀ.The potential energy curves for the various electronic states,regardless of molecular charge,are commonly plotted on the same diagram.Figures8.3and8.4give these for some important electronic statesof HÀ2,H2,and Hþ2,and of OÀ2,O2,and Oþ2,respectively.Examples of both attractive(having a potential energy minimum)and repulsive(having no minimum)states can be seen.The vibrational levels are labeled with the quantum number v for the attrac-tive levels.The ground states of both Hþ2and Oþ2are attractive;hence these molecular ions are stable against autodissociation(ABþ!AþBþor AþþB).Similarly,the ground states of H2and O2are attractive and lie below those of Hþ2and Oþ2;hence they are stable against autodissociation and autoionization(AB!ABþþe).For some molecules,for example,diatomic argon,the ABþion is stable but the AB neutral is not stable.For all molecules,the AB ground state lies below the ABþground state and is stable against autoionization.Excited states can be attractive or repulsive.A few of the attractive states may be metastable;some examples are the 3P u state of H2and the1D g,1Sþgand3D u states of O2.Negative IonsRecall from Section7.2that many neutral atoms have a positive electron affinity E aff;that is,the reactionAþeÀ!AÀis exothermic with energy E aff(in volts).If E aff is negative,then AÀis unstable to autodetachment,AÀ!Aþe.A similar phenomenon is found for negative molecular ions.A stable ABÀion exists if its ground(lowest energy)state has a potential minimum that lies below the ground state of AB.This is generally true only for strongly electronegative gases having large electron affinities,such as O2 (E aff%1:463V for O atoms)and the halogens(E aff.3V for the atoms).For example,Figure8.4shows that the2P g ground state of OÀ2is stable,with E aff% 0:43V for O2.For weakly electronegative or for electropositive gases,the minimum of the ground state of ABÀgenerally lies above the ground state of AB,and ABÀis unstable to autodetachment.An example is hydrogen,which is weakly electronegative(E aff%0:754V for H atoms).Figure8.3shows that the2Sþu ground state of HÀ2is unstable,although the HÀion itself is stable.In an elec-tropositive gas such as N2(E aff.0),both NÀ2and NÀare unstable. 240MOLECULAR COLLISIONS8.3ELECTRON COLLISIONS WITH MOLECULESThe interaction time for the collision of a typical (1–10V)electron with a molecule is short,t c 2a 0=v e 10À16–10À15s,compared to the typical time for a molecule to vibrate,t vib 10À14–10À13s.Hence for electron collisional excitation of a mole-cule to an excited electronic state,the new vibrational (and rotational)state canbeFIGURE 8.3.Potential energy curves for H À2,H 2,and H þ2.(From Jeffery I.Steinfeld,Molecules and Radiation:An Introduction to Modern Molecular Spectroscopy ,2d ed.#MIT Press,1985.)8.3ELECTRON COLLISIONS WITH MOLECULES 241FIGURE 8.4.Potential energy curves for O À2,O 2,and O þ2.(From Jeffery I.Steinfeld,Molecules and Radiation:An Introduction to Modern Molecular Spectroscopy ,2d ed.#MIT Press,1985.)242MOLECULAR COLLISIONS8.3ELECTRON COLLISIONS WITH MOLECULES243 determined by freezing the nuclear motions during the collision.This is known as the Franck–Condon principle and is illustrated in Figure8.1by the vertical line a,showing the collisional excitation atfixed R to a high quantum number bound vibrational state and by the vertical line b,showing excitation atfixed R to a vibra-tionally unbound state,in which breakup of the molecule is energetically permitted. Since the typical transition time for electric dipole radiation(t rad 10À9–10À8s)is long compared to the dissociation( vibrational)time t diss,excitation to an excited state will generally lead to dissociation when it is energetically permitted.Finally, we note that the time between collisions t c)t rad in typical low-pressure processing discharges.Summarizing the ordering of timescales for electron–molecule collisions,we havet at t c(t vib t diss(t rad(t cDissociationElectron impact dissociation,eþABÀ!AþBþeof feedstock gases plays a central role in the chemistry of low-pressure reactive discharges.The variety of possible dissociation processes is illustrated in Figure8.5.In collisions a or a0,the v¼0ground state of AB is excited to a repulsive state of AB.The required threshold energy E thr is E a for collision a and E a0for Array FIGURE8.5.Illustrating the variety of dissociation processes for electron collisions with molecules.collision a0,and it leads to an energy after dissociation lying between E aÀE diss and E a0ÀE diss that is shared among the dissociation products(here,A and B). Typically,E aÀE diss few volts;consequently,hot neutral fragments are typically generated by dissociation processes.If these hot fragments hit the substrate surface, they can profoundly affect the process chemistry.In collision b,the ground state AB is excited to an attractive state of AB at an energy E b that exceeds the binding energy E diss of the AB molecule,resulting in dissociation of AB with frag-ment energy E bÀE diss.In collision b0,the excitation energy E b0¼E diss,and the fragments have low energies;hence this process creates fragments having energies ranging from essentially thermal energies up to E bÀE diss few volts.In collision c,the AB atom is excited to the bound excited state ABÃ(labeled5),which sub-sequently radiates to the unbound AB state(labeled3),which then dissociates.The threshold energy required is large,and the fragments are hot.Collision c can also lead to dissociation of an excited state by a radiationless transfer from state5to state4near the point where the two states cross:ABÃðboundÞÀ!ABÃðunboundÞÀ!AþBÃThe fragments can be both hot and in excited states.We discuss such radiationless electronic transitions in the next section.This phenomenon is known as predisso-ciation.Finally,a collision(not labeled in thefigure)to state4can lead to dis-sociation of ABÃ,again resulting in hot excited fragments.The process of electron impact excitation of a molecule is similar to that of an atom,and,consequently,the cross sections have a similar form.A simple classical estimate of the dissociation cross section for a level having excitation energy U1can be found by requiring that an incident electron having energy W transfer an energy W L lying between U1and U2to a valence electron.Here,U2is the energy of the next higher level.Then integrating the differential cross section d s[given in(3.4.20)and repeated here],d s¼pe24021Wd W LW2L(3:4:20)over W L,we obtains diss¼0W,U1pe24pe021W1U1À1WU1,W,U2pe24021W1U1À1U2W.U28>>>>>><>>>>>>:(8:3:1)244MOLECULAR COLLISIONSLetting U2ÀU1(U1and introducing voltage units W¼e E,U1¼e E1and U2¼e E2,we haves diss¼0E,E1s0EÀE11E1,E,E2s0E2ÀE1EE.E28>>>><>>>>:(8:3:2)wheres0¼pe4pe0E12(8:3:3)We see that the dissociation cross section rises linearly from the threshold energy E thr%E1to a maximum value s0(E2ÀE1)=E thr at E2and then falls off as1=E. Actually,E1and E2can depend on the nuclear separation R.In this case,(8.3.2) should be averaged over the range of R s corresponding to the ground-state vibrational energy,leading to a broadened dependence of the average cross section on energy E.The maximum cross section is typically of order10À15cm2. Typical rate constants for a single dissociation process with E thr&T e have an Arrhenius formK diss/K diss0expÀE thr T e(8:3:4)where K diss0 10À7cm3=s.However,in some cases E thr.T e.For excitation to an attractive state,an appropriate average over the fraction of the ground-state vibration that leads to dissociation must be taken.Dissociative IonizationIn addition to normal ionization,eþABÀ!ABþþ2eelectron–molecule collisions can lead to dissociative ionizationeþABÀ!AþBþþ2eThese processes,common for polyatomic molecules,are illustrated in Figure8.6.In collision a having threshold energy E iz,the molecular ion ABþis formed.Collisionsb andc occur at higher threshold energies E diz and result in dissociative ionization,8.3ELECTRON COLLISIONS WITH MOLECULES245leading to the formation of fast,positively charged ions and neutrals.These cross sections have a similar form to the Thompson ionization cross section for atoms.Dissociative RecombinationThe electron collision,e þAB þÀ!A þB Ãillustrated as d and d 0in Figure 8.6,destroys an electron–ion pair and leads to the production of fast excited neutral fragments.Since the electron is captured,it is not available to carry away a part of the reaction energy.Consequently,the collision cross section has a resonant character,falling to very low values for E ,E d and E .E d 0.However,a large number of excited states A Ãand B Ãhaving increasing principal quantum numbers n and energies can be among the reaction products.Consequently,the rate constants can be large,of order 10À7–10À6cm 3=s.Dissocia-tive recombination to the ground states of A and B cannot occur because the potential energy curve for AB þis always greater than the potential energycurveFIGURE 8.6.Illustration of dissociative ionization and dissociative recombination for electron collisions with molecules.246MOLECULAR COLLISIONSfor the repulsive state of AB.Two-body recombination for atomic ions or for mol-ecular ions that do not subsequently dissociate can only occur with emission of a photon:eþAþÀ!Aþh n:As shown in Section9.2,the rate constants are typically three tofive orders of magnitude lower than for dissociative recombination.Example of HydrogenThe example of H2illustrates some of the inelastic electron collision phenomena we have discussed.In order of increasing electron impact energy,at a threshold energy of 8:8V,there is excitation to the repulsive3Sþu state followed by dissociation into two fast H fragments carrying 2:2V/atom.At11.5V,the1Sþu bound state is excited,with subsequent electric dipole radiation in the ultraviolet region to the1Sþg ground state.At11.8V,there is excitation to the3Sþg bound state,followedby electric dipole radiation to the3Sþu repulsive state,followed by dissociation with 2:2V/atom.At12.6V,the1P u bound state is excited,with UV emission tothe ground state.At15.4V,the2Sþg ground state of Hþ2is excited,leading to the pro-duction of Hþ2ions.At28V,excitation of the repulsive2Sþu state of Hþ2leads to thedissociative ionization of H2,with 5V each for the H and Hþfragments.Dissociative Electron AttachmentThe processes,eþABÀ!AþBÀproduce negative ion fragments as well as neutrals.They are important in discharges containing atoms having positive electron affinities,not only because of the pro-duction of negative ions,but because the threshold energy for production of negative ion fragments is usually lower than for pure dissociation processes.A variety of pro-cesses are possible,as shown in Figure8.7.Since the impacting electron is captured and is not available to carry excess collision energy away,dissociative attachment is a resonant process that is important only within a narrow energy range.The maximum cross sections are generally much smaller than the hard-sphere cross section of the molecule.Attachment generally proceeds by collisional excitation from the ground AB state to a repulsive ABÀstate,which subsequently either auto-detaches or dissociates.The attachment cross section is determined by the balance between these processes.For most molecules,the dissociation energy E diss of AB is greater than the electron affinity E affB of B,leading to the potential energy curves shown in Figure8.7a.In this case,the cross section is large only for impact energies lying between a minimum value E thr,for collision a,and a maximum value E0thr for8.3ELECTRON COLLISIONS WITH MOLECULES247FIGURE 8.7.Illustration of a variety of electron attachment processes for electron collisions with molecules:(a )capture into a repulsive state;(b )capture into an attractive state;(c )capture of slow electrons into a repulsive state;(d )polar dissociation.248MOLECULAR COLLISIONScollision a 0.The fragments are hot,having energies lying between minimum and maximum values E min ¼E thr þE affB ÀE diss and E max ¼E 0thr þE af fB ÀE diss .Since the AB Àstate lies above the AB state for R ,R x ,autodetachment can occur as the mol-ecules begin to separate:AB À!AB þe.Hence the cross section for production of negative ions can be much smaller than that for excitation of the AB Àrepulsive state.As a crude estimate,for the same energy,the autodetachment rate is ffiffiffiffiffiffiffiffiffiffiffiffiffiM R =m p 100times the dissociation rate of the repulsive AB Àmolecule,where M R is the reduced mass.Hence only one out of 100excitations lead to dissociative attachment.Excitation to the AB Àbound state can also lead to dissociative attachment,as shown in Figure 8.7b .Here the cross section is significant only for E thr ,E ,E 0thr ,but the fragments can have low energies,with a minimum energy of zero and a maximum energy of E 0thr þE affB ÀE diss .Collision b,e þAB À!AB ÀÃdoes not lead to production of AB Àions because energy and momentum are not gen-erally conserved when two bodies collide elastically to form one body (see Problem3.12).Hence the excited AB ÀÃion separates,AB ÀÃÀ!e þABunless vibrational radiation or collision with a third body carries off the excess energy.These processes are both slow in low-pressure discharges (see Section 9.2).At high pressures (say,atmospheric),three-body attachment to form AB Àcan be very important.For a few molecules,such as some halogens,the electron affinity of the atom exceeds the dissociation energy of the neutral molecule,leading to the potential energy curves shown in Figure 8.7c .In this case the range of electron impact ener-gies E for excitation of the AB Àrepulsive state includes E ¼0.Consequently,there is no threshold energy,and very slow electrons can produce dissociative attachment,resulting in hot neutral and negative ion fragments.The range of R s over which auto-detachment can occur is small;hence the maximum cross sections for dissociative attachment can be as high as 10À16cm 2.A simple classical estimate of electron capture can be made using the differential scattering cross section for energy loss (3.4.20),in a manner similar to that done for dissociation.For electron capture to an energy level E 1that is unstable to autode-tachment,and with the additional constraint for capture that the incident electron energy lie within E 1and E 2¼E 1þD E ,where D E is a small energy difference characteristic of the dissociative attachment timescale,we obtain,in place of (8.3.2),s att¼0E ,E 1s 0E ÀE 1E 1E 1,E ,E 20E .E 28>><>>:(8:3:5)8.3ELECTRON COLLISIONS WITH MOLECULES 249wheres 0%p m M R 1=2e 4pe 0E 1 2(8:3:6)The factor of (m =M R )1=2roughly gives the fraction of excited states that do not auto-detach.We see that the dissociative attachment cross section rises linearly at E 1to a maximum value s 0D E =E 1and then falls abruptly to zero.As for dissociation,E 1can depend strongly on the nuclear separation R ,and (8.3.5)must be averaged over the range of E 1s corresponding to the ground state vibrational motion;e.g.,from E thr to E 0thr in Figure 8.7a .Because generally D E (E 0thr ÀE thr ,we can write (8.3.5)in the forms att %p m M R 1=2e 4pe 0 2(D E )22E 1d (E ÀE 1)(8:3:7)where d is the Dirac delta ing (8.3.7),the average over the vibrational motion can be performed,leading to a cross section that is strongly peaked lying between E thr and E 0thr .We leave the details of the calculation to a problem.Polar DissociationThe process,e þAB À!A þþB Àþeproduces negative ions without electron capture.As shown in Figure 8.7d ,the process proceeds by excitation of a polar state A þand B Àof AB Ãthat has a separ-ated atom limit of A þand B À.Hence at large R ,this state lies above the A þB ground state by the difference between the ionization potential of A and the electron affinity of B.The polar state is weakly bound at large R by the Coulomb attraction force,but is repulsive at small R .The maximum cross section and the dependence of the cross section on electron impact energy are similar to that of pure dissociation.The threshold energy E thr for polar dissociation is generally large.The measured cross section for negative ion production by electron impact in O 2is shown in Figure 8.8.The sharp peak at 6.5V is due to dissociative attachment.The variation of the cross section with energy is typical of a resonant capture process.The maximum cross section of 10À18cm 2is quite low because autode-tachment from the repulsive O À2state is strong,inhibiting dissociative attachment.The second gradual maximum near 35V is due to polar dissociation;the variation of the cross section with energy is typical of a nonresonant process.250MOLECULAR COLLISIONS。

Gdel, Nagel, minds and machines

Gdel, Nagel, minds and machines
Gödel, Nagel, minds and machines Solomon Feferman Ernest Nagel Lecture, Columbia University September 27, 2007 Just fifty years ago, Ernest Nagel and Kurt Gödel became involved in a serious imbroglio about the possible inclusion of Gödel’s original work on incompleteness in the book, Gödel’s Proof, then being written by Nagel with James R. Newman. What led to the conflict were some unprecedented demands that Gödel made over the use of his material and his involvement in the contents of the bookdemands that resulted in an explosive reaction on Nagel’s part. In the end the proposal came to naught. But the story is of interest because of what was basically at issue, namely their provocative related but contrasting views on the possible significance of Gödel’s theorems for minds vs. machines in the development of mathematics. That is our point of departure for the attempts by Gödel, and later Lucas and Penrose, to establish definitive consequences of those theorems, attempts whichas we shall seedepend on highly idealized and problematic assumptions about minds, machines and mathematics. In particular, I shall argue that there is a fundamental equivocation involved in those assumptions that needs to be reexamined. In conclusion, that will lead us to a new way of looking at how the mind works in deriving mathematics that in a way straddles the mechanist and antimechanist viewpoints. The story of the conflict between Gödel and Nagel has been told in full in the introductory note by Charles Parsons and Wilfried Sieg to the correspondence between them in Volume V of the Gödel Collected Works, so I’ll confine myself to the high points. The first popular exposition of Gödel’s incompleteness theo and Newman in 1956 in an article entitled “Goedel’s proof” for the Scientific American. The article was reprinted soon after in the four volume anthology edited by Newman, The World of Mathematics: A small library of the literature of mathematics from A'h-mosé the Scribe to Albert Einstein, presented with commentaries and notes. That was an instant best-seller, and has since been reprinted many times. It was a must

减基法在轨道-隧道-土体系统谐响应分析中的应用

减基法在轨道-隧道-土体系统谐响应分析中的应用

第 55 卷第 3 期2024 年 3 月中南大学学报(自然科学版)Journal of Central South University (Science and Technology)V ol.55 No.3Mar. 2024减基法在轨道−隧道−土体系统谐响应分析中的应用王森1, 2,辛涛1, 2, 3,王朋松1, 2,杨燚1, 2, 3,戴传青1, 2,滕明利1, 2(1. 北京交通大学 土木建筑工程学院,北京,100044;2. 北京市轨道工程重点实验室,北京,100044;3. 智慧高铁系统前沿科学中心,北京,100044)摘要:为了提高轨道交通环境振动预测效率,提出基于减基法原理的轨道−隧道−土体系统谐响应分析方法,即将减基法应用到轨道−隧道−土体系统的谐响应分析中。

结合有限元方法和理论解析方法,在既有计算频率样本的基础上,实现原求解域内系统频响函数的重采样计算。

将本文方法与有限元方法和线性插值方法进行对比分析。

研究结果表明:在不同规模模型条件下,所提出方法的计算误差要明显低于线性插值方法的计算误差。

同时,相比于有限元求解方法,本文方法能够在不同线程条件下均保持较高的计算精度和效率;且随着模型规模增大,本文方法相比有限元法的加速比不断提高,最大加速比可以超过2 000。

关键词:轨道交通;环境振动;振动预测;传递函数;减基法中图分类号:U231 文献标志码:A 文章编号:1672-7207(2024)03-1231-10Application of reduced basis method in harmonic analysis oftrack −tunnel −soil systemWANG Sen 1, 2, XIN Tao 1, 2, 3, WANG Pengsong 1, 2, YANG Yi 1, 2, 3, DAI Chuanqing 1, 2, TENG Mingli 1, 2(1. School of Civil Engineering, Beijing Jiaotong University, Beijing 100044, China;2. Beijing Key Laboratory of Track Engineering, Beijing Jiaotong University, Beijing 100044, China;3. Frontiers Science Center for Smart High-speed Railway System, Beijing 100044, China)Abstract: In order to improve the prediction efficiency of railway-induced vibration, the harmonic analysis method of the track −tunnel −soil system was proposed based on the reduced basis method. The reduced basis method was applied in the harmonic analysis of the track −tunnel −soil system. Combining the finite element method and the theoretical analytical method, the resampling calculation of the frequency response function of the system in the original solution domain was realized on the basis of the existing calculation frequency samples. Theproposed method in this paper was compared with the finite element method and linear interpolation method. The收稿日期: 2023 −05 −24; 修回日期: 2023 −07 −14基金项目(Foundation item):国家重点研发计划项目(2023YFB2604300);111引智基地项目(B20040) (Project(2023YFB2604300)supported by the National Key Research and Development Program of China; Project(B20040) supported by the 111 Project)通信作者:辛涛,博士,教授,从事轨道动力学研究;E-mail :*************.cnDOI: 10.11817/j.issn.1672-7207.2024.03.033引用格式: 王森, 辛涛, 王朋松, 等. 减基法在轨道−隧道−土体系统谐响应分析中的应用[J]. 中南大学学报(自然科学版), 2024, 55(3): 1231−1240.Citation: WANG Sen, XIN Tao, WANG Pengsong, et al. Application of reduced basis method in harmonic analysis of track −tunnel −soil system[J]. Journal of Central South University(Science and Technology), 2024, 55(3): 1231−1240.第 55 卷中南大学学报(自然科学版)results show that in any models with different scales, the calculation errors of the proposed method are obviously lower than those of linear interpolation. Meanwhile, compared with the finite element method, the proposed method can maintain high calculation accuracy and efficiency under different threads. With the increase of model scale, the acceleration ratio of the proposed method is higher than that of the finite element method, and the maximum acceleration ratio can exceed 2 000.Key words: rail transit; environmental vibration; vibration prediction; transfer function; reduced basis method近年来,我国城市轨道交通得到了迅猛发展,截至2022年底,城市轨道交通运营里程已突破1万km。

Principles of Plasma Discharges and Materials Processing第2章

Principles of Plasma Discharges and Materials Processing第2章

CHAPTER 2BASIC PLASMA EQUATIONS AND EQUILIBRIUM2.1INTRODUCTIONThe plasma medium is complicated in that the charged particles are both affected by external electric and magnetic fields and contribute to them.The resulting self-consistent system is nonlinear and very difficult to analyze.Furthermore,the inter-particle collisions,although also electromagnetic in character,occur on space and time scales that are usually much shorter than those of the applied fields or the fields due to the average motion of the particles.To make progress with such a complicated system,various simplifying approxi-mations are needed.The interparticle collisions are considered independently of the larger scale fields to determine an equilibrium distribution of the charged-particle velocities.The velocity distribution is averaged over velocities to obtain the macro-scopic motion.The macroscopic motion takes place in external applied fields and in the macroscopic fields generated by the average particle motion.These self-consistent fields are nonlinear,but may be linearized in some situations,particularly when dealing with waves in plasmas.The effect of spatial variation of the distri-bution function leads to pressure forces in the macroscopic equations.The collisions manifest themselves in particle generation and loss processes,as an average friction force between different particle species,and in energy exchanges among species.In this chapter,we consider the basic equations that govern the plasma medium,con-centrating attention on the macroscopic system.The complete derivation of these 23Principles of Plasma Discharges and Materials Processing ,by M.A.Lieberman and A.J.Lichtenberg.ISBN 0-471-72001-1Copyright #2005John Wiley &Sons,Inc.equations,from fundamental principles,is beyond the scope of the text.We shall make the equations plausible and,in the easier instances,supply some derivations in appendices.For the reader interested in more rigorous treatment,references to the literature will be given.In Section2.2,we introduce the macroscopicfield equations and the current and voltage.In Section2.3,we introduce the fundamental equation of plasma physics, for the evolution of the particle distribution function,in a form most applicable for weakly ionized plasmas.We then define the macroscopic quantities and indicate how the macroscopic equations are obtained by taking moments of the fundamental equation.References given in the text can be consulted for more details of the aver-aging procedure.Although the macroscopic equations depend on the equilibrium distribution,their form is independent of the equilibrium.To solve the equations for particular problems the equilibrium must be known.In Section2.4,we introduce the equilibrium distribution and obtain some consequences arising from it and from thefield equations.The form of the equilibrium distribution will be shown to be a consequence of the interparticle collisions,in Appendix B.2.2FIELD EQUATIONS,CURRENT,AND VOLTAGEMaxwell’s EquationsThe usual macroscopic form of Maxwell’s equations arerÂE¼Àm0@H@t(2:2:1)rÂH¼e0@E@tþJ(2:2:2)e0rÁE¼r(2:2:3) andmrÁH¼0(2:2:4) where E(r,t)and H(r,t)are the electric and magneticfield vectors and wherem 0¼4pÂ10À7H/m and e0%8:854Â10À12F/m are the permeability and per-mittivity of free space.The sources of thefields,the charge density r(r,t)and the current density J(r,t),are related by the charge continuity equation(Problem2.1):@rþrÁJ¼0(2:2:5) In general,J¼J condþJ polþJ mag24BASIC PLASMA EQUATIONS AND EQUILIBRIUMwhere the conduction current density J cond is due to the motion of the free charges, the polarization current density J pol is due to the motion of bound charges in a dielectric material,and the magnetization current density J mag is due to the magnetic moments in a magnetic material.In a plasma in vacuum,J pol and J mag are zero and J¼J cond.If(2.2.3)is integrated over a volume V,enclosed by a surface S,then we obtain its integral form,Gauss’law:e0þSEÁd A¼q(2:2:6)where q is the total charge inside the volume.Similarly,integrating(2.2.5),we obtaind q d t þþSJÁd A¼0which states that the rate of increase of charge inside V is supplied by the total currentflowing across S into V,that is,that charge is conserved.In(2.2.2),thefirst term on the RHS is the displacement current densityflowing in the vacuum,and the second term is the conduction current density due to the free charges.We can introduce the total current densityJ T¼e0@E@tþJ(2:2:7)and taking the divergence of(2.2.2),we see thatrÁJ T¼0(2:2:8)In one dimension,this reduces to d J T x=d x¼0,such that J T x¼J T x(t),independent of x.Hence,for example,the total currentflowing across a spatially nonuniform one-dimensional discharge is independent of x,as illustrated in Figure2.1.A generalization of this result is Kirchhoff’s current law,which states that the sum of the currents entering a node,where many current-carrying conductors meet,is zero.This is also shown in Figure2.1,where I rf¼I TþI1.If the time variation of the magneticfield is negligible,as is often the case in plasmas,then from Maxwell’s equations rÂE%0.Since the curl of a gradient is zero,this implies that the electricfield can be derived from the gradient of a scalar potential,E¼Àr F(2:2:9)2.2FIELD EQUATIONS,CURRENT,AND VOLTAGE25Integrating (2.2.9)around any closed loop C givesþC E Ád ‘¼ÀþC r F Ád ‘¼ÀþC d F ¼0(2:2:10)Hence,we obtain Kirchhoff’s voltage law ,which states that the sum of the voltages around any loop is zero.This is illustrated in Figure 2.1,for which we obtainV rf ¼V 1þV 2þV 3that is,the source voltage V rf is equal to the sum of the voltages V 1and V 3across the two sheaths and the voltage V 2across the bulk plasma.Note that currents and vol-tages can have positive or negative values;the directions for which their values are designated as positive must be specified,as shown in the figure.If (2.2.9)is substituted in (2.2.3),we obtainr 2F ¼Àre 0(2:2:11)Equation (2.2.11),Poisson’s equation ,is one of the fundamental equations that we shall use.As an example of its application,consider the potential in the center (x ¼0)of two grounded (F ¼0)plates separated by a distance l ¼10cm and con-taining a uniform ion density n i ¼1010cm 23,without the presence of neutralizing electrons.Integrating Poisson’s equationd 2F d x 2¼Àen i eFIGURE 2.1.Kirchhoff’s circuit laws:The total current J T flowing across a nonuniform one-dimensional discharge is independent of x ;the sum of the currents entering a node is zero (I rf ¼I T þI 1);the sum of voltages around a loop is zero (V rf ¼V 1þV 2þV 3).26BASIC PLASMA EQUATIONS AND EQUILIBRIUMusing the boundary conditions that F ¼0at x ¼+l =2and that d F =d x ¼0at x ¼0(by symmetry),we obtainF ¼12en i e 0l 22Àx 2"#The maximum potential in the center is 2.3Â105V,which is impossibly large for a real discharge.Hence,the ions must be mostly neutralized by electrons,leading to a quasi-neutral plasma.Figure 2.2shows a PIC simulation time history over 10210s of (a )the v x –x phase space,(b )the number N of sheets versus time,and (c )the potential F versus x for 100unneutralized ion sheets (with e /M for argon ions).We see the ion acceleration in (a ),the loss of ions in (b ),and the parabolic potential profile in (c );the maximum potential decreases as ions are lost from the system.We consider quasi-neutrality further in Section 2.4.Electric and magnetic fields exert forces on charged particles given by the Lorentz force law :F ¼q (E þv ÂB )(2:2:12)FIGURE 2.2.PIC simulation of ion loss in a plasma containing ions only:(a )v x –x ion phase space,showing the ion acceleration trajectories;(b )number N of ion sheets versus t ,with the steps indicating the loss of a single sheet;(c )the potential F versus x during the first 10210s of ion loss.2.2FIELD EQUATIONS,CURRENT,AND VOLTAGE 2728BASIC PLASMA EQUATIONS AND EQUILIBRIUMwhere v is the particle velocity and B¼m0H is the magnetic induction vector.The charged particles move under the action of the Lorentz force.The moving charges in turn contribute to both r and J in the plasma.If r and J are linearly related to E and B,then thefield equations are linear.As we shall see,this is not generally the case for a plasma.Nevertheless,linearization may be possible in some cases for which the plasma may be considered to have an effective dielectric constant;that is,the “free charges”play the same role as“bound charges”in a dielectric.We consider this further in Chapter4.2.3THE CONSERVATION EQUATIONSBoltzmann’s EquationFor a given species,we introduce a distribution function f(r,v,t)in the six-dimensional phase space(r,v)of particle positions and velocities,with the interpret-ation thatf(r,v,t)d3r d3v¼number of particles inside a six-dimensional phasespace volume d3r d3v at(r,v)at time tThe six coordinates(r,v)are considered to be independent variables.We illus-trate the definition of f and its phase space in one dimension in Figure2.3.As particles drift in phase space or move under the action of macroscopic forces, theyflow into or out of thefixed volume d x d v x.Hence the distribution functionaf should obey a continuity equation which can be derived as follows.InFIGURE2.3.One-dimensional v x–x phase space,illustrating the derivation of the Boltzmann equation and the change in f due to collisions.time d t,f(x,v x,t)d x a x(x,v x,t)d t particlesflow into d x d v x across face1f(x,v xþd v x,t)d x a x(x,v xþd v x,t)d t particlesflow out of d x d v x across face2 f(x,v x,t)d v x v x d t particlesflow into d x d v x across face3f(xþd x,v x,t)d v x v x d t particlesflow out of d x d v x across face4where a x v d v x=d t and v x;d x=d t are theflow velocities in the v x and x directions, respectively.Hencef(x,v x,tþd t)d x d v xÀf(x,v x,t)d x d v x¼½f(x,v x,t)a x(x,v x,t)Àf(x,v xþd v x,t)a x(x,v xþd v x,t) d x d tþ½f(x,v x,t)v xÀf(xþd x,v x,t)v x d v x d tDividing by d x d v x d t,we obtain@f @t ¼À@@x(f v x)À@@v x(fa x)(2:3:1)Noting that v x is independent of x and assuming that the acceleration a x¼F x=m of the particles does not depend on v x,then(2.3.1)can be rewritten as@f @t þv x@f@xþa x@f@v x¼0The three-dimensional generalization,@f@tþvÁr r fþaÁr v f¼0(2:3:2)with r r¼(^x@=@xþ^y@=@yþ^z@=@z)and r v¼(^x@=@v xþ^y@=@v yþ^z@=@v z)is called the collisionless Boltzmann equation or Vlasov equation.In addition toflows into or out of the volume across the faces,particles can “suddenly”appear in or disappear from the volume due to very short time scale interparticle collisions,which are assumed to occur on a timescale shorter than the evolution time of f in(2.3.2).Such collisions can practically instantaneously change the velocity(but not the position)of a particle.Examples of particles sud-denly appearing or disappearing are shown in Figure2.3.We account for this effect,which changes f,by adding a“collision term”to the right-hand side of (2.3.2),thus obtaining the Boltzmann equation:@f @t þvÁr r fþFmÁr v f¼@f@tc(2:3:3)2.3THE CONSERVATION EQUATIONS29The collision term in integral form will be derived in Appendix B.The preceding heuristic derivation of the Boltzmann equation can be made rigorous from various points of view,and the interested reader is referred to texts on plasma theory, such as Holt and Haskel(1965).A kinetic theory of discharges,accounting for non-Maxwellian particle distributions,must be based on solutions of the Boltzmann equation.We give an introduction to this analysis in Chapter18. Macroscopic QuantitiesThe complexity of the dynamical equations is greatly reduced by averaging over the velocity coordinates of the distribution function to obtain equations depending on the spatial coordinates and the time only.The averaged quantities,such as species density,mean velocity,and energy density are called macroscopic quantities,and the equations describing them are the macroscopic conservation equations.To obtain these averaged quantities we take velocity moments of the distribution func-tion,and the equations are obtained from the moments of the Boltzmann equation.The average quantities that we are concerned with are the particle density,n(r,t)¼ðf d3v(2:3:4)the particlefluxG(r,t)¼n u¼ðv f d3v(2:3:5)where u(r,t)is the mean velocity,and the particle kinetic energy per unit volumew¼32pþ12mu2n¼12mðv2f d3v(2:3:6)where p(r,t)is the isotropic pressure,which we define below.In this form,w is sumof the internal energy density32p and theflow energy density12mu2n.Particle ConservationThe lowest moment of the Boltzmann equation is obtained by integrating all terms of(2.3.3)over velocity space.The integration yields the macroscopic continuity equation:@n@tþrÁ(n u)¼GÀL(2:3:7)The collision term in(2.3.3),which yields the right-hand side of(2.3.7),is equal to zero when integrated over velocities,except for collisions that create or destroy 30BASIC PLASMA EQUATIONS AND EQUILIBRIUMparticles,designated as G and L ,respectively (e.g.,ionization,recombination).In fact,(2.3.7)is transparent since it physically describes the conservation of particles.If (2.3.7)is integrated over a volume V bounded by a closed surface S ,then (2.3.7)states that the net number of particles generated per second within V ,either flows across the surface S or increases the number of particles within V .For common low-pressure discharges in the steady state,G is usually due to ioniz-ation by electron–neutral collisions:G ¼n iz n ewhere n iz is the ionization frequency.The volume loss rate L ,usually due to recom-bination,is often negligible.Hencer Á(n u )¼n iz n e (2:3:8)in a typical discharge.However,note that the continuity equation is clearly not sufficient to give the evolution of the density n ,since it involves another quantity,the mean particle velocity u .Momentum ConservationTo obtain an equation for u ,a first moment is formed by multiplying the Boltzmann equation by v and integrating over velocity.The details are complicated and involve evaluation of tensor elements.The calculation can be found in most plasma theory texts,for example,Krall and Trivelpiece (1973).The result is mn @u @t þu Ár ðÞu !¼qn E þu ÂB ðÞÀr ÁP þf c (2:3:9)The left-hand side is the species mass density times the convective derivative of the mean velocity,representing the mass density times the acceleration.The convective derivative has two terms:the first term @u =@t represents an acceleration due to an explicitly time-varying u ;the second “inertial”term (u Ár )u represents an acceleration even for a steady fluid flow (@=@t ;0)having a spatially varying u .For example,if u ¼^xu x (x )increases along x ,then the fluid is accelerating along x (Problem 2.4).This second term is nonlinear in u and can often be neglected in discharge analysis.The mass times acceleration is acted upon,on the right-hand side,by the body forces,with the first term being the electric and magnetic force densities.The second term is the force density due to the divergence of the pressure tensor,which arises due to the integration over velocitiesP ij ¼mn k v i Àu ðÞv j Àu ÀÁl v (2:3:10)2.3THE CONSERVATION EQUATIONS 31where the subscripts i,j give the component directions and kÁl v denotes the velocity average of the bracketed quantity over f.ÃFor weakly ionized plasmas it is almost never used in this form,but rather an isotropic version is employed:P¼p000p000p@1A(2:3:11)such thatrÁP¼r p(2:3:12) a pressure gradient,withp¼13mn k(vÀu)2l v(2:3:13)being the scalar pressure.Physically,the pressure gradient force density arises as illustrated in Figure2.4,which shows a small volume acted upon by a pressure that is an increasing function of x.The net force on this volume is p(x)d AÀp(xþd x)d A and the volume is d A d x.Hence the force per unit volume isÀ@p=@x.The third term on the right in(2.3.9)represents the time rate of momentum trans-fer per unit volume due to collisions with other species.For electrons or positive ions the most important transfer is often due to collisions with neutrals.The transfer is usually approximated by a Krook collision operatorf j c¼ÀXbmn n m b(uÀu b):Àm(uÀu G)Gþm(uÀu L)L(2:3:14)where the summation is over all other species,u b is the mean velocity of species b, n m b is the momentum transfer frequency for collisions with species b,and u G and u L are the mean velocities of newly created and lost particles.Generally j u G j(j u j for pair creation by ionization,and u L%u for recombination or charge transfer lossprocesses.We discuss the Krook form of the collision operator further in Chapter 18.The last two terms in(2.3.14)are generally small and give the momentum trans-fer due to the creation or destruction of particles.For example,if ions are created at rest,then they exert a drag force on the moving ionfluid because they act to lower the averagefluid velocity.A common form of the average force(momentum conservation)equation is obtained from(2.3.9)neglecting the magnetic forces and taking u b¼0in theÃWe assume f is normalized so that k f lv ¼1.32BASIC PLASMA EQUATIONS AND EQUILIBRIUMKrook collision term for collisions with one neutral species.The result is mn @u @t þu Ár u !¼qn E Àr p Àmn n m u (2:3:15)where only the acceleration (@u =@t ),inertial (u Ár u ),electric field,pressure gradi-ent,and collision terms appear.For slow time variation,the acceleration term can be neglected.For high pressures,the inertial term is small compared to the collision term and can also be dropped.Equations (2.3.7)and (2.3.9)together still do not form a closed set,since the pressure tensor P (or scalar pressure p )is not determined.The usual procedure to close the equations is to use a thermodynamic equation of state to relate p to n .The isothermal relation for an equilibrium Maxwellian distribution isp ¼nkT(2:3:16)so thatr p ¼kT r n (2:3:17)where T is the temperature in kelvin and k is Boltzmann’s constant (k ¼1.381Â10223J /K).This holds for slow time variations,where temperatures are allowed to equilibrate.In this case,the fluid can exchange energy with its sur-roundings,and we also require an energy conservation equation (see below)to deter-mine p and T .For a room temperature (297K)neutral gas having density n g and pressure p ,(2.3.16)yieldsn g (cm À3)%3:250Â1016p (Torr)(2:3:18)p FIGURE 2.4.The force density due to the pressure gradient.2.3THE CONSERVATION EQUATIONS 33Alternatively,the adiabatic equation of state isp¼Cn g(2:3:19) such thatr p p ¼gr nn(2:3:20)where g is the ratio of specific heat at constant pressure to that at constant volume.The specific heats are defined in Section7.2;g¼5/3for a perfect gas; for one-dimensional adiabatic motion,g¼3.The adiabatic relation holds for fast time variations,such as in waves,when thefluid does not exchange energy with its surroundings;hence an energy conservation equation is not required. For almost all applications to discharge analysis,we use the isothermal equation of state.Energy ConservationThe energy conservation equation is obtained by multiplying the Boltzmannequation by12m v2and integrating over velocity.The integration and some othermanipulation yield@ @t32pþrÁ32p uðÞþp rÁuþrÁq¼@@t32pc(2:3:21)Here32p is the thermal energy density(J/m3),32p u is the macroscopic thermal energyflux(W/m2),representing theflow of the thermal energy density at thefluid velocityu,p rÁu(W/m3)gives the heating or cooling of thefluid due to compression orexpansion of its volume(Problem2.5),q is the heatflow vector(W/m2),whichgives the microscopic thermal energyflux,and the collisional term includes all col-lisional processes that change the thermal energy density.These include ionization,excitation,elastic scattering,and frictional(ohmic)heating.The equation is usuallyclosed by setting q¼0or by letting q¼Àk T r T,where k T is the thermal conduc-tivity.For most steady-state discharges the macroscopic thermal energyflux isbalanced against the collisional processes,giving the simpler equationrÁ32p u¼@32pc(2:3:22)Equation(2.3.22),together with the continuity equation(2.3.8),will often prove suf-ficient for our analysis.34BASIC PLASMA EQUATIONS AND EQUILIBRIUMSummarySummarizing our results for the macroscopic equations describing the electron and ionfluids,we have in their most usually used forms the continuity equationrÁ(n u)¼n iz n e(2:3:8) the force equation,mn @u@tþuÁr u!¼qn EÀr pÀmn n m u(2:3:15)the isothermal equation of statep¼nkT(2:3:16) and the energy-conservation equationrÁ32p u¼@@t32pc(2:3:22)These equations hold for each charged species,with the total charges and currents summed in Maxwell’s equations.For example,with electrons and one positive ion species with charge Ze,we haver¼e Zn iÀn eðÞ(2:3:23)J¼e Zn i u iÀn e u eðÞ(2:3:24)These equations are still very difficult to solve without simplifications.They consist of18unknown quantities n i,n e,p i,p e,T i,T e,u i,u e,E,and B,with the vectors each counting for three.Various simplifications used to make the solutions to the equations tractable will be employed as the individual problems allow.2.4EQUILIBRIUM PROPERTIESElectrons are generally in near-thermal equilibrium at temperature T e in discharges, whereas positive ions are almost never in thermal equilibrium.Neutral gas mol-ecules may or may not be in thermal equilibrium,depending on the generation and loss processes.For a single species in thermal equilibrium with itself(e.g.,elec-trons),in the absence of time variation,spatial gradients,and accelerations,the2.4EQUILIBRIUM PROPERTIES35Boltzmann equation(2.3.3)reduces to@f @tc¼0(2:4:1)where the subscript c here represents the collisions of a particle species with itself. We show in Appendix B that the solution of(2.4.1)has a Gaussian speed distribution of the formf(v)¼C eÀj2m v2(2:4:2) The two constants C and j can be obtained by using the thermodynamic relationw¼12mn k v2l v¼32nkT(2:4:3)that is,that the average energy of a particle is12kT per translational degree offreedom,and by using a suitable normalization of the distribution.Normalizing f(v)to n,we obtainCð2p0d fðpsin u d uð1expÀj2m v2ÀÁv2d v¼n(2:4:4)and using(2.4.3),we obtain1 2mCð2pd fðpsin u d uð1expÀj2m v2ÀÁv4d v¼32nkT(2:4:5)where we have written the integrals over velocity space in spherical coordinates.The angle integrals yield the factor4p.The v integrals are evaluated using the relationÃð10eÀu2u2i d u¼(2iÀ1)!!2ffiffiffiffipp,where i is an integer!1:(2:4:6)Solving for C and j we havef(v)¼nm2p kT3=2expÀm v22kT(2:4:7)which is the Maxwellian distribution.Ã!!denotes the double factorial function;for example,7!!¼7Â5Â3Â1. 36BASIC PLASMA EQUATIONS AND EQUILIBRIUMSimilarly,other averages can be performed.The average speed vis given by v ¼m =2p kT ðÞ3=2ð10v exp Àv 22v 2th !4p v 2d v (2:4:8)where v th ¼(kT =m )1=2is the thermal velocity.We obtainv ¼8kT p m 1=2(2:4:9)The directed flux G z in (say)the þz direction is given by n k v z l v ,where the average is taken over v z .0only.Writing v z ¼v cos u we have in spherical coordinatesG z ¼n m 2p kT 3=2ð2p 0d f ðp =20sin u d u ð10v cos u exp Àv 22v 2th v 2d v Evaluating the integrals,we findG z ¼14n v (2:4:10)G z is the number of particles per square meter per second crossing the z ¼0surfacein the positive direction.Similarly,the average energy flux S z ¼n k 1m v 2v z l v in theþz direction can be found:S z ¼2kT G z .We see that the average kinetic energy W per particle crossing z ¼0in the positive direction isW ¼2kT (2:4:11)It is sometimes convenient to define the distribution in terms of other variables.For example,we can define a distribution of energies W ¼12m v 2by4p g W ðÞd W ¼4p f v ðÞv 2d vEvaluating d v =d W ,we see that g and f are related byg W ðÞ¼v (W )f ½v (W ) m (2:4:12)where v (W )¼(2W =m )1=2.Boltzmann’s RelationA very important relation can be obtained for the density of electrons in thermal equilibrium at varying positions in a plasma under the action of a spatially varying 2.4EQUILIBRIUM PROPERTIES 3738BASIC PLASMA EQUATIONS AND EQUILIBRIUMpotential.In the absence of electron drifts(u e;0),the inertial,magnetic,and fric-tional forces are zero,and the electron force balance is,from(2.3.15)with@=@t;0,en e Eþr p e¼0(2:4:13) Setting E¼Àr F and assuming p e¼n e kT e,(2.4.13)becomesÀen e r FþkT e r n e¼0or,rearranging,r(e FÀkT e ln n e)¼0(2:4:14) Integrating,we havee FÀkT e ln n e¼constorn e(r)¼n0e e F(r)=kT e(2:4:15)which is Boltzmann’s relation for electrons.We see that electrons are“attracted”to regions of positive potential.We shall generally write Boltzmann’s relation in more convenient unitsn e¼n0e F=T e(2:4:16)where T e is now expressed in volts,as is F.For positive ions in thermal equilibrium at temperature T i,a similar analysis shows thatn i¼n0eÀF=T i(2:4:17) Hence positive ions in thermal equilibrium are“repelled”from regions of positive potential.However,positive ions are almost never in thermal equilibrium in low-pressure discharges because the ion drift velocity u i is large,leading to inertial or frictional forces in(2.3.15)that are comparable to the electricfield or pressure gra-dient forces.Debye LengthThe characteristic length scale in a plasma is the electron Debye length l De.As we will show,the Debye length is the distance scale over which significant charge densities can spontaneously exist.For example,low-voltage(undriven)sheaths are typically a few Debye lengths wide.To determine the Debye length,let us intro-duce a sheet of negative charge having surface charge density r S,0C/m2into an。

工程热力学10 Reaction rate theories

工程热力学10 Reaction rate theories
is the average velocity(not the average relative velocity)
Thus the 1-1 collision frequency for a give molecule is:
The total number of 1-1 collision per unit volume per unit time is:
10 Reaction rate theories
Chemical kinetics govern the rate which chemical species are created or destroyed via reactions.
Rates are determined by the concentrations of the chemical species involved in the reaction and an experimentally determined rate coefficient k.
Section 10.2: Both can lead to a simple collision theory expression for the reaction rate constant k.
Section 10.3: Transition-state theory is derived.
The number of collisions per unit time is:
Based on a Maxwell-Boltzmann distribution of collision velocities, the average collision frequency:
The average collision frequency of a type 2 molecule with type 1 molecules is:

Instructional_design

Instructional_design

Instructional designFrom Wikipedia, the free encyclopediaInstructional Design(also called Instructional Systems Design (ISD)) is the practice of maximizing the effectiveness, efficiency and appeal of instruction and other learning experiences. The process consists broadly of determining the current state and needs of the learner, defining the end goal of instruction, and creating some "intervention" to assist in the transition. Ideally the process is informed by pedagogically(process of teaching) and andragogically(adult learning) tested theories of learning and may take place in student-only, teacher-led or community-based settings. The outcome of this instruction may be directly observable and scientifically measured or completely hidden and assumed. There are many instructional design models but many are based on the ADDIE model with the five phases: 1) analysis, 2) design, 3) development, 4) implementation, and 5) evaluation. As a field, instructional design is historically and traditionally rooted in cognitive and behavioral psychology.HistoryMuch of the foundations of the field of instructional design was laid in World War II, when the U.S. military faced the need to rapidly train large numbers of people to perform complex technical tasks, fromfield-stripping a carbine to navigating across the ocean to building a bomber—see "Training Within Industry(TWI)". Drawing on the research and theories of B.F. Skinner on operant conditioning, training programs focused on observable behaviors. Tasks were broken down into subtasks, and each subtask treated as a separate learning goal. Training was designed to reward correct performance and remediate incorrect performance. Mastery was assumed to be possible for every learner, given enough repetition and feedback. After the war, the success of the wartime training model was replicated in business and industrial training, and to a lesser extent in the primary and secondary classroom. The approach is still common in the U.S. military.[1]In 1956, a committee led by Benjamin Bloom published an influential taxonomy of what he termed the three domains of learning: Cognitive(what one knows or thinks), Psychomotor (what one does, physically) and Affective (what one feels, or what attitudes one has). These taxonomies still influence the design of instruction.[2]During the latter half of the 20th century, learning theories began to be influenced by the growth of digital computers.In the 1970s, many instructional design theorists began to adopt an information-processing-based approach to the design of instruction. David Merrill for instance developed Component Display Theory (CDT), which concentrates on the means of presenting instructional materials (presentation techniques).[3]Later in the 1980s and throughout the 1990s cognitive load theory began to find empirical support for a variety of presentation techniques.[4]Cognitive load theory and the design of instructionCognitive load theory developed out of several empirical studies of learners, as they interacted with instructional materials.[5]Sweller and his associates began to measure the effects of working memory load, and found that the format of instructional materials has a direct effect on the performance of the learners using those materials.[6][7][8]While the media debates of the 1990s focused on the influences of media on learning, cognitive load effects were being documented in several journals. Rather than attempting to substantiate the use of media, these cognitive load learning effects provided an empirical basis for the use of instructional strategies. Mayer asked the instructional design community to reassess the media debate, to refocus their attention on what was most important: learning.[9]By the mid- to late-1990s, Sweller and his associates had discovered several learning effects related to cognitive load and the design of instruction (e.g. the split attention effect, redundancy effect, and the worked-example effect). Later, other researchers like Richard Mayer began to attribute learning effects to cognitive load.[9] Mayer and his associates soon developed a Cognitive Theory of MultimediaLearning.[10][11][12]In the past decade, cognitive load theory has begun to be internationally accepted[13]and begun to revolutionize how practitioners of instructional design view instruction. Recently, human performance experts have even taken notice of cognitive load theory, and have begun to promote this theory base as the science of instruction, with instructional designers as the practitioners of this field.[14]Finally Clark, Nguyen and Sweller[15]published a textbook describing how Instructional Designers can promote efficient learning using evidence-based guidelines of cognitive load theory.Instructional Designers use various instructional strategies to reduce cognitive load. For example, they think that the onscreen text should not be more than 150 words or the text should be presented in small meaningful chunks.[citation needed] The designers also use auditory and visual methods to communicate information to the learner.Learning designThe concept of learning design arrived in the literature of technology for education in the late nineties and early 2000s [16] with the idea that "designers and instructors need to choose for themselves the best mixture of behaviourist and constructivist learning experiences for their online courses" [17]. But the concept of learning design is probably as old as the concept of teaching. Learning design might be defined as "the description of the teaching-learning process that takes place in a unit of learning (eg, a course, a lesson or any other designed learning event)" [18].As summarized by Britain[19], learning design may be associated with:∙The concept of learning design∙The implementation of the concept made by learning design specifications like PALO, IMS Learning Design[20], LDL, SLD 2.0, etc... ∙The technical realisations around the implementation of the concept like TELOS, RELOAD LD-Author, etc...Instructional design modelsADDIE processPerhaps the most common model used for creating instructional materials is the ADDIE Process. This acronym stands for the 5 phases contained in the model:∙Analyze– analyze learner characteristics, task to be learned, etc.Identify Instructional Goals, Conduct Instructional Analysis, Analyze Learners and Contexts∙Design– develop learning objectives, choose an instructional approachWrite Performance Objectives, Develop Assessment Instruments, Develop Instructional Strategy∙Develop– create instructional or training materialsDesign and selection of materials appropriate for learning activity, Design and Conduct Formative Evaluation∙Implement– deliver or distribute the instructional materials ∙Evaluate– make sure the materials achieved the desired goals Design and Conduct Summative EvaluationMost of the current instructional design models are variations of the ADDIE process.[21] Dick,W.O,.Carey, L.,&Carey, J.O.(2004)Systematic Design of Instruction. Boston,MA:Allyn&Bacon.Rapid prototypingA sometimes utilized adaptation to the ADDIE model is in a practice known as rapid prototyping.Proponents suggest that through an iterative process the verification of the design documents saves time and money by catching problems while they are still easy to fix. This approach is not novel to the design of instruction, but appears in many design-related domains including software design, architecture, transportation planning, product development, message design, user experience design, etc.[21][22][23]In fact, some proponents of design prototyping assert that a sophisticated understanding of a problem is incomplete without creating and evaluating some type of prototype, regardless of the analysis rigor that may have been applied up front.[24] In other words, up-front analysis is rarely sufficient to allow one to confidently select an instructional model. For this reason many traditional methods of instructional design are beginning to be seen as incomplete, naive, and even counter-productive.[25]However, some consider rapid prototyping to be a somewhat simplistic type of model. As this argument goes, at the heart of Instructional Design is the analysis phase. After you thoroughly conduct the analysis—you can then choose a model based on your findings. That is the area where mostpeople get snagged—they simply do not do a thorough-enough analysis. (Part of Article By Chris Bressi on LinkedIn)Dick and CareyAnother well-known instructional design model is The Dick and Carey Systems Approach Model.[26] The model was originally published in 1978 by Walter Dick and Lou Carey in their book entitled The Systematic Design of Instruction.Dick and Carey made a significant contribution to the instructional design field by championing a systems view of instruction as opposed to viewing instruction as a sum of isolated parts. The model addresses instruction as an entire system, focusing on the interrelationship between context, content, learning and instruction. According to Dick and Carey, "Components such as the instructor, learners, materials, instructional activities, delivery system, and learning and performance environments interact with each other and work together to bring about the desired student learning outcomes".[26] The components of the Systems Approach Model, also known as the Dick and Carey Model, are as follows:∙Identify Instructional Goal(s): goal statement describes a skill, knowledge or attitude(SKA) that a learner will be expected to acquire ∙Conduct Instructional Analysis: Identify what a learner must recall and identify what learner must be able to do to perform particular task ∙Analyze Learners and Contexts: General characteristic of the target audience, Characteristic directly related to the skill to be taught, Analysis of Performance Setting, Analysis of Learning Setting∙Write Performance Objectives: Objectives consists of a description of the behavior, the condition and criteria. The component of anobjective that describes the criteria that will be used to judge the learner's performance.∙Develop Assessment Instruments: Purpose of entry behavior testing, purpose of pretesting, purpose of posttesting, purpose of practive items/practive problems∙Develop Instructional Strategy: Pre-instructional activities, content presentation, Learner participation, assessment∙Develop and Select Instructional Materials∙Design and Conduct Formative Evaluation of Instruction: Designer try to identify areas of the instructional materials that are in need to improvement.∙Revise Instruction: To identify poor test items and to identify poor instruction∙Design and Conduct Summative EvaluationWith this model, components are executed iteratively and in parallel rather than linearly.[26]/akteacher/dick-cary-instructional-design-mo delInstructional Development Learning System (IDLS)Another instructional design model is the Instructional Development Learning System (IDLS).[27] The model was originally published in 1970 by Peter J. Esseff, PhD and Mary Sullivan Esseff, PhD in their book entitled IDLS—Pro Trainer 1: How to Design, Develop, and Validate Instructional Materials.[28]Peter (1968) & Mary (1972) Esseff both received their doctorates in Educational Technology from the Catholic University of America under the mentorship of Dr. Gabriel Ofiesh, a Founding Father of the Military Model mentioned above. Esseff and Esseff contributed synthesized existing theories to develop their approach to systematic design, "Instructional Development Learning System" (IDLS).The components of the IDLS Model are:∙Design a Task Analysis∙Develop Criterion Tests and Performance Measures∙Develop Interactive Instructional Materials∙Validate the Interactive Instructional MaterialsOther modelsSome other useful models of instructional design include: the Smith/Ragan Model, the Morrison/Ross/Kemp Model and the OAR model , as well as, Wiggins theory of backward design .Learning theories also play an important role in the design ofinstructional materials. Theories such as behaviorism , constructivism , social learning and cognitivism help shape and define the outcome of instructional materials.Influential researchers and theoristsThe lists in this article may contain items that are not notable , not encyclopedic , or not helpful . Please help out by removing such elements and incorporating appropriate items into the main body of the article. (December 2010)Alphabetic by last name∙ Bloom, Benjamin – Taxonomies of the cognitive, affective, and psychomotor domains – 1955 ∙Bonk, Curtis – Blended learning – 2000s ∙ Bransford, John D. – How People Learn: Bridging Research and Practice – 1999 ∙ Bruner, Jerome – Constructivism ∙Carr-Chellman, Alison – Instructional Design for Teachers ID4T -2010 ∙Carey, L. – "The Systematic Design of Instruction" ∙Clark, Richard – Clark-Kosma "Media vs Methods debate", "Guidance" debate . ∙Clark, Ruth – Efficiency in Learning: Evidence-Based Guidelines to Manage Cognitive Load / Guided Instruction / Cognitive Load Theory ∙Dick, W. – "The Systematic Design of Instruction" ∙ Gagné, Robert M. – Nine Events of Instruction (Gagné and Merrill Video Seminar) ∙Heinich, Robert – Instructional Media and the new technologies of instruction 3rd ed. – Educational Technology – 1989 ∙Jonassen, David – problem-solving strategies – 1990s ∙Langdon, Danny G - The Instructional Designs Library: 40 Instructional Designs, Educational Tech. Publications ∙Mager, Robert F. – ABCD model for instructional objectives – 1962 ∙Merrill, M. David - Component Display Theory / Knowledge Objects ∙ Papert, Seymour – Constructionism, LOGO – 1970s ∙ Piaget, Jean – Cognitive development – 1960s∙Piskurich, George – Rapid Instructional Design – 2006∙Simonson, Michael –Instructional Systems and Design via Distance Education – 1980s∙Schank, Roger– Constructivist simulations – 1990s∙Sweller, John - Cognitive load, Worked-example effect, Split-attention effect∙Roberts, Clifton Lee - From Analysis to Design, Practical Applications of ADDIE within the Enterprise - 2011∙Reigeluth, Charles –Elaboration Theory, "Green Books" I, II, and III - 1999-2010∙Skinner, B.F.– Radical Behaviorism, Programed Instruction∙Vygotsky, Lev– Learning as a social activity – 1930s∙Wiley, David– Learning Objects, Open Learning – 2000sSee alsoSince instructional design deals with creating useful instruction and instructional materials, there are many other areas that are related to the field of instructional design.∙educational assessment∙confidence-based learning∙educational animation∙educational psychology∙educational technology∙e-learning∙electronic portfolio∙evaluation∙human–computer interaction∙instructional design context∙instructional technology∙instructional theory∙interaction design∙learning object∙learning science∙m-learning∙multimedia learning∙online education∙instructional design coordinator∙storyboarding∙training∙interdisciplinary teaching∙rapid prototyping∙lesson study∙Understanding by DesignReferences1.^MIL-HDBK-29612/2A Instructional Systems Development/SystemsApproach to Training and Education2.^Bloom's Taxonomy3.^TIP: Theories4.^Lawrence Erlbaum Associates, Inc. - Educational Psychologist -38(1):1 - Citation5.^ Sweller, J. (1988). "Cognitive load during problem solving:Effects on learning". Cognitive Science12 (1): 257–285.doi:10.1016/0364-0213(88)90023-7.6.^ Chandler, P. & Sweller, J. (1991). "Cognitive Load Theory andthe Format of Instruction". Cognition and Instruction8 (4): 293–332.doi:10.1207/s1532690xci0804_2.7.^ Sweller, J., & Cooper, G.A. (1985). "The use of worked examplesas a substitute for problem solving in learning algebra". Cognition and Instruction2 (1): 59–89. doi:10.1207/s1532690xci0201_3.8.^Cooper, G., & Sweller, J. (1987). "Effects of schema acquisitionand rule automation on mathematical problem-solving transfer". Journal of Educational Psychology79 (4): 347–362.doi:10.1037/0022-0663.79.4.347.9.^ a b Mayer, R.E. (1997). "Multimedia Learning: Are We Asking theRight Questions?". Educational Psychologist32 (41): 1–19.doi:10.1207/s1*******ep3201_1.10.^ Mayer, R.E. (2001). Multimedia Learning. Cambridge: CambridgeUniversity Press. ISBN0-521-78239-2.11.^Mayer, R.E., Bove, W. Bryman, A. Mars, R. & Tapangco, L. (1996)."When Less Is More: Meaningful Learning From Visual and Verbal Summaries of Science Textbook Lessons". Journal of Educational Psychology88 (1): 64–73. doi:10.1037/0022-0663.88.1.64.12.^ Mayer, R.E., Steinhoff, K., Bower, G. and Mars, R. (1995). "Agenerative theory of textbook design: Using annotated illustrations to foster meaningful learning of science text". Educational TechnologyResearch and Development43 (1): 31–41. doi:10.1007/BF02300480.13.^Paas, F., Renkl, A. & Sweller, J. (2004). "Cognitive Load Theory:Instructional Implications of the Interaction between InformationStructures and Cognitive Architecture". Instructional Science32: 1–8.doi:10.1023/B:TRUC.0000021806.17516.d0.14.^ Clark, R.C., Mayer, R.E. (2002). e-Learning and the Science ofInstruction: Proven Guidelines for Consumers and Designers of Multimedia Learning. San Francisco: Pfeiffer. ISBN0-7879-6051-9.15.^ Clark, R.C., Nguyen, F., and Sweller, J. (2006). Efficiency inLearning: Evidence-Based Guidelines to Manage Cognitive Load. SanFrancisco: Pfeiffer. ISBN0-7879-7728-4.16.^Conole G., and Fill K., “A learning design toolkit to createpedagogically effective learning activities”. Journal of Interactive Media in Education, 2005 (08).17.^Carr-Chellman A. and Duchastel P., “The ideal online course,”British Journal of Educational Technology, 31(3), 229-241, July 2000.18.^Koper R., “Current Research in Learning Design,” EducationalTechnology & Society, 9 (1), 13-22, 2006.19.^Britain S., “A Review of Learning Design: Concept,Specifications and Tools” A report for the JISC E-learning Pedagogy Programme, May 2004.20.^IMS Learning Design webpage21.^ a b Piskurich, G.M. (2006). Rapid Instructional Design: LearningID fast and right.22.^ Saettler, P. (1990). The evolution of American educationaltechnology.23.^ Stolovitch, H.D., & Keeps, E. (1999). Handbook of humanperformance technology.24.^ Kelley, T., & Littman, J. (2005). The ten faces of innovation:IDEO's strategies for beating the devil's advocate & driving creativity throughout your organization. New York: Doubleday.25.^ Hokanson, B., & Miller, C. (2009). Role-based design: Acontemporary framework for innovation and creativity in instructional design. Educational Technology, 49(2), 21–28.26.^ a b c Dick, Walter, Lou Carey, and James O. Carey (2005) [1978].The Systematic Design of Instruction(6th ed.). Allyn & Bacon. pp. 1–12.ISBN020*******./?id=sYQCAAAACAAJ&dq=the+systematic+design+of+instruction.27.^ Esseff, Peter J. and Esseff, Mary Sullivan (1998) [1970].Instructional Development Learning System (IDLS) (8th ed.). ESF Press.pp. 1–12. ISBN1582830371. /Materials.html.28.^/Materials.htmlExternal links∙Instructional Design - An overview of Instructional Design∙ISD Handbook∙Edutech wiki: Instructional design model [1]∙Debby Kalk, Real World Instructional Design InterviewRetrieved from "/wiki/Instructional_design" Categories: Educational technology | Educational psychology | Learning | Pedagogy | Communication design | Curricula。

有限元中弹性连接单元的刚度矩阵

有限元中弹性连接单元的刚度矩阵

第 39 卷第 6 期2023 年12 月结构工程师Structural Engineers Vol. 39 , No. 6Dec. 2023有限元中弹性连接单元的刚度矩阵张军锋1,*胡连超2温珺博1耿玉鹏3李杰1(1.郑州大学土木工程学院,郑州 450001; 2.中建七局交通建设有限公司,郑州 450003;3.河南濮泽高速公路有限公司,濮阳 457000)摘要针对常用有限元软件中弹性连接单元的刚度矩阵开展研究。

类似普通梁单元刚度矩阵的分析方法,将弹性连接单元的空间受力状态分解为伸缩、弯曲和扭转三种独立的模式进行分析,并提出两种方式推导弯曲受力模式下的刚度矩阵。

对于弯曲受力状态下的刚度矩阵,明确了MIDAS中弹性连接单元输入参数包括弯曲和剪切刚度系数、弹性连接长度和剪切距离比R在刚度矩阵中的表现形式,给出了其刚度矩阵的理论表达式;阐明了剪切距离比R的力学意义,即用以考虑弹性支承两端因剪力传递的弯矩,其对结构的影响只体现在杆端位移结果中,杆端力始终满足静力平衡条件而不受R的影响,并且在R取0.5时,MIDAS中弹性连接的单元刚度矩阵与普通欧拉梁单元的刚度矩阵最为接近。

同时通过分析对比,明确了ANSYS和ABAQUS中弹性连接单元的弯剪效应是独立的,这与MIDAS中弹性连接单元在不考虑剪切距离比R时的特性一致。

研究成果既有助于理解弹性连接单元刚度矩阵,又为其工程应用提供了参考。

关键词弹性连接单元,刚度矩阵,平面弯曲受力,剪切距离比,有限元软件Stiffness Matrixes of Elastic Connection Elements inFinite Element MethodZHANG Junfeng1,*HU Lianchao2WEN Junbo1GENG Yupeng3LI Jie1(1.School of Civil Engineering,Zhengzhou University, Zhengzhou 450001, China;munications Construction Company of CSCEC 7th Division Co.,LTD., Zhengzhou 450003, China;3.Henan Puze Expressway Co.,LTD, Puyang 457000, China)Abstract The study was initiated for the stiffness matrixes of elastic connection elements in Finite Element Method (FEM). The derivation was decomposed into three uncoupled conditions, including tension, torsion,and bending, as the derivation for beam elements. Two methods were proposed to derivate the matrix in the bending condition. Following the analysis of the participation of parameters of the elastic connection element in MIDAS, including the bending and shearing stiffness values, the connection length, and the shear distance ratio R,the theoretical expression of the stiffness matrix of the elastic connection element in MIDAS was obtained. Especially,the mechanical implications of the shear distance ratio R were also elaborated:it was used to transfer the bending moment from one end to another due to the shear force; it had influence on the displacement results but not on the static equilibrium condition;the matrix of elastic connection element in MIDAS was close to the matrix of Euler-beam element if R=0.5. Moreover,a comparative investigation was given on the elastic connection elements in ANSYS, ABAQUS and MIDAS. It was found that the shear and bending effects are independent for the elastic connection elements in ANSYS and ABAQUS,which is the case when R is not considered for the elastic connection element in MIDAS. The derivation process and conclusion are instructive for the understanding of stiffness matrixes of elastic connection elements and helpful for practical application.收稿日期:2022-06-25*联系作者:张军锋(1983-),男,博士,副教授,主要研究方向为结构和桥梁抗风。

theoretical economics letters 检索

theoretical economics letters 检索

theoretical economics letters 检索首页搜索“Theoretical Economics Letters”检索Theoretical Economics Letters is an open-access, peer-reviewed journal that focuses on publishing innovative and high-quality research in the field of theoretical economics. The journal covers a broad range of topics, including microeconomics, macroeconomics, game theory, and economic theory.In this article, we will discuss the importance of Theoretical Economics Letters as a platform for researchers to disseminate their work and contribute to the theoretical economics literature. We will also explore the journal's submission process, publication standards, and its impact on the field of economics.1. IntroductionTheoretical Economics Letters is a leading journal in the field of theoretical economics. With its open-access policy, researchers from around the world can access and benefit from the latest advancements in economic theory. The journal aims to bridge the gap between theoretical research and real-world applications,providing valuable insights and analysis that can contribute to economic policy-making.2. The importance of Theoretical Economics LettersTheoretical Economics Letters plays a crucial role in the dissemination of innovative research in theoretical economics. By publishing cutting-edge papers, the journal fosters academic debate and enhances the overall knowledge and understanding of economic theory. It provides a platform for researchers to exchange ideas, collaborate, and build upon each other's work, thereby pushing the boundaries of economic theory.3. Submission processTo submit an article to Theoretical Economics Letters, authors need to register on the journal's website and follow the submission guidelines. The journal accepts papers in various formats, including research articles, reviews, and letters to the editor. The submission should adhere to the journal's publication standards in terms of originality, rigor, and relevance to the field of theoretical economics.4. Publication standardsTheoretical Economics Letters maintains rigorous publication standards to ensure the quality and integrity of the articles it publishes. The journal follows a double-blind peer-review process, meaning that both the authors and reviewers remain anonymous throughout the review process. This ensures that the evaluation is fair and unbiased. The journal also upholds strict ethical guidelines, such as ensuring the confidentiality of the review process and avoiding any conflicts of interest.5. Impact on the field of economicsTheoretical Economics Letters has made a significant impact on the field of economics by publishing groundbreaking research that challenges existing theories and pushes the boundaries of economic knowledge. With its high visibility and accessibility, the journal's articles have been widely cited and used as references by researchers and policymakers worldwide. The journal's impact factor and citation index serve as indicators of its influence and relevance in the field. Additionally, the journal organizesconferences and symposiums where researchers can present their work and engage in meaningful discussions.ConclusionTheoretical Economics Letters is a vital platform for researchers to share their innovative ideas and contribute to the field of theoretical economics. By maintaining high publication standards and fostering academic debate, the journal plays a crucial role in advancing economic theory and its real-world applications. As the field of economics continue to evolve and develop, Theoretical Economics Letters remains at the forefront, nurturing innovation and collaboration among researchers worldwide.。

几类特殊图完美匹配数目的递推求法

几类特殊图完美匹配数目的递推求法

第39卷 第2期西南师范大学学报(自然科学版)2014年2月V o l .39 N o .2 J o u r n a l o f S o u t h w e s t C h i n aN o r m a lU n i v e r s i t y (N a t u r a l S c i e n c eE d i t i o n )F e b .2014文章编号:10005471(2014)2000905几类特殊图完美匹配数目的递推求法①唐保祥1, 任 韩21.天水师范学院数学与统计学院,甘肃天水741001;2.华东师范大学数学系,上海200062摘要:匹配计数理论是图论的核心内容之一,此理论有很强的物理学和化学背景.但是,一般图的完美匹配计数问题却是N P 难问题.用划分㊁求和㊁嵌套递推的方法给出了几类图完美匹配数目的显式表达式.关 键 词:完美匹配;线性递推式;特征方程中图分类号:O 157.5文献标志码:A图的完美匹配计数理论已经在多个领域得到应用,也引起了众多数学家㊁物理学家和化学家的广泛关注[1-5].但是,文献[5]在1979年就证明了:一个图的完美匹配计数问题是N P 难问题.因此,要得到一般图的完美匹配数的计算公式是困难的.目前,已有一些文献对一些特殊图的完美匹配计数作了相关的研究[6-10].本文给出了4类图完美匹配数目的计算公式,所给方法是求解一些特殊图类完美匹配数目的比较有效的方法.定义1 若图G 的两个完美匹配M 1和M 2中有一条边不同,则称M 1和M 2是G 的两个不同的完美匹配.定义2 令两条长为n 的路为P 1=u 1u 2 u n +1,P 2=v 1v 2 v n +1.分别连接路P 1与P 2的顶点u i 与v i (i =1,2, ,n +1),所得到的图称为长为n 的梯子,记为T n .分别连接梯子T n 的顶点u 1与v n +1,v 1与u n +1,所得到的图称为长为n 的莫比乌斯梯子,记为M T n .定理1 令2n 个4圈为C i 14:u i 1u i 2u i 3u i 4u i 1,C i 24:v i 1v i 2v i 3v i 4v i 1(i =1,2, ,n ).分别连接圈C i 14与C i 24的顶点u i 4与v i 4,u i 3与v i 1,u i 2与v i 2,再分别连接圈C i 14和C i +1,14的顶点u i 2与u i +1,4,C i 24和C i +1,24的顶点v i 2与v i +1,4.这样所得到的图记为2n S C 4,如图1所示.φ(n )表示图2n S C 4的完美匹配的数目.则φ(n )=10+31020㊃3+()10n +10-31020㊃3-()10n .图1 图2n S C 4证 显然,图2n S C 4有完美匹配.设图2n S C 4的完美匹配集合为M ,图2n S C 4含边u 11u 14,u 11u 12的完美匹配集合分别为M 1,M 2.则M i ⊆M ,M 1ɘM 2=Ø.故M =M 1ɣM 2,φ(n )=|M |=|M 1|+|M 2|.求|M 1|情形1 M 11⊆M 1.∀M 11ɪM 11,u 11u 14,u 12u 13,v 11v 14,v 12v 13ɪM 11,由φ(n )的定义知,|M 11|=φ(n -1).情形2 M 12⊆M 1.∀M 12ɪM 12,u 11u 14,u 12u 13,v 11v 12,v 14v 13ɪM 12,由φ(n )的定义知,|M 12|=①收稿日期:20121031基金项目:国家自然科学基金(11171114).作者简介:唐保祥(1961),男,甘肃天水人,副教授,主要从事图论和组合数学的研究.φ(n -1).情形3 M 13⊆M 1.∀M 13ɪM 13,u 11u 14,u 13v 11,u 12v 12,v 14v 13ɪM 13,由φ(n )的定义知,|M 13|=φ(n -1).情形4 M 14⊆M 1.∀M 14ɪM 14,u 11u 14,u 13v 11,v 14v 13,u 12u 24,v 12v 24,u 21u 22,u 23v 21,v 23v 22ɪM 14,由φ(n )的定义知,|M 14|=φ(n -2).因为M 1=ɣ4i =1M 1i ,M 1i ɘM 1j =Ø(1ɤi <j ɤ4),故|M 1|=3φ(n -1)+φ(n -2).求|M 2|情形1 M 21⊆M 2.∀M 21ɪM 21,u 11u 12,u 14u 13,v 14v 11,v 13v 12ɪM 21,由φ(n )的定义知,|M 21|=φ(n -1).情形2 M 22⊆M 2.∀M 22ɪM 22,u 11u 12,u 14u 13,v 11v 12,v 14v 13ɪM 22,由φ(n )的定义知,|M 22|=φ(n -1).情形3 M 23⊆M 2.∀M 23ɪM 23,u 11u 12,u 14v 14,u 13v 11,v 12v 13ɪM 23,由φ(n )的定义知,|M 23|=φ(n -1).因为M 2=M 21ɣM 22ɣM 23,M 2i ɘM 2j =Ø(1ɤi <j ɤ3),故|M 2|=3φ(n -1).综上所述,φ(n )=6φ(n -1)+φ(n -2).(1)易知φ(1)=6,φ(2)=37.线性递推式(1)式的特征方程的根为x =3ʃ10.所以(1)式的通解为φ(n )=10+31020㊃3+()10n +10-31020㊃3-()10n .定理2 长为3的莫比乌斯梯子M T i 3的顶点集为V (M T i 3)={u i 1,u i 2,u i 3,u i 4,v i 1,v i 2,v i 3,v i 4}(i =1,2, ,n ).分别连接图M T i 3与M T i +13的顶点v i 2与u i +1,2,v i 3与u i +1,3(i =1,2, ,n -1).这样得到的图记为2n MT 3,如图2所示.σ(n )表示图2n MT 3的完美匹配的数目.则σ(n )=41+44182㊃9+41æèçöø÷2n +41-44182㊃9-41æèçöø÷2n .证 欲求σ(n ),定义一个图G 1,并求其完美匹配的数目.将长为1的路u 1u 2的端点u 1和u 2分别与图2nMT 3的顶点u 12和u 13各连接一条边,得到的图记为G 1,如图3所示.显然图G 1有完美匹配.α(n )表示图G 1的完美匹配的数目.图2 图2n MT 3图3 图G 1 求α(n ).设图G 1的完美匹配的集合为M ,G 1含边u 1u 2,u 1u 12的完美匹配集合分别为M 1,M 2.则M 1ɘM 2=Ø.所以M =M 1ɣM 2,α(n )=|M |=|M 1|+|M 2|.求|M 1| ∀M 1ɪM 1,因为u 1u 2ɪM 1,所以由σ(n )的定义知,|M 1|=σ(n ).求|M 2|情形1 M 21⊆M 2.∀M 21ɪM 21,u 1u 12,u 2u 13,u 11v 11,u 14v 14ɪM 21,由α(n )的定义知,|M 21|=α(n -1).情形2 M 22⊆M 2.∀M 22ɪM 21,u 1u 12,u 2u 13,u 11v 14,u 14v 11ɪM 22,由α(n )的定义知,|M 21|=α(n -1).因为M 2=M 21ɣM 22,M 21ɘM 22=Ø,故|M 2|=2α(n -1).因此α(n )=σ(n )+2α(n -1).(2) 求σ(n ).显然图2n MT 3有完美匹配.设图G 1的完美匹配的集合为M ,2n MT 3含边u 11v 11,u 11v 14,u 11u 12的完美匹配的集合分别为M 1,M 2,M 3.则M =M 1ɣM 2ɣM 3,M i ɘM j =Ø(1ɤi <j ɤ3).所以01西南师范大学学报(自然科学版) h t t p ://x b b jb .s w u .c n 第39卷σ(n )=|M |=|M 1|+|M 2|+|M 3|.求|M 1|情形1 M 11⊆M 1.∀M 11ɪM 11,u 11v 11,u 12v 12,u 13v 13,u 14v 14ɪM 11,由σ(n )的定义知,|M 11|=σ(n -1).情形2 M 12⊆M 1.∀M 12ɪM 12,u 11v 11,u 12v 12,u 13u 14,v 13v 14ɪM 12,由σ(n )的定义知,|M 12|=σ(n -1).情形3 M 13⊆M 1.∀M 13ɪM 13,u 11v 11,u 12u 13,u 14v 14ɪM 13,由α(n )的定义知,|M 13|=α(n -1).因为M 1=M 11ɣM 12ɣM 13,M 1i ɘM 1j =Ø(1ɤi <j ɤ3),故|M 1|=2σ(n -1)+α(n -1).求|M 2|情形1 M 21⊆M 2.∀M 21ɪM 21,u 11v 14,u 12v 12,u 13v 13,u 14v 11ɪM 21,由σ(n )的定义知,|M 21|=σ(n -1).情形2 M 22⊆M 2.∀M 22ɪM 22,u 11v 14,u 13u 12,u 14v 11ɪM 22,由σ(n )的定义知,|M 22|=α(n -1).因为M 2=M 21ɣM 22,M 21ɘM 22=Ø,故|M 2|=σ(n -1)+α(n -1).求|M 3|情形1 M 31⊆M 3.∀M 31ɪM 31,u 11u 12,v 11v 12,u 13v 13,u 14v 14ɪM 31,由σ(n )的定义知,|M 31|=σ(n -1).情形2 M 32⊆M 3.∀M 32ɪM 32,u 11u 12,u 13u 14,v 11v 12,v 13v 14ɪM 32,由σ(n )的定义知,|M 31|=σ(n -1).因为M 3=M 31ɣM 32,M 31ɘM 32=Ø,故|M 3|=2σ(n -1).综上所述,σ(n )=5σ(n -1)+2α(n -1).(3) 由(2)和(3)式可得σ(n )=9σ(n -1)-10σ(n -1).(4)易知σ(1)=7,α(1)=9,由(3)式得σ(2)=53.解线性递推式(4),得σ(n )=41+44182㊃9+41æèçöø÷2n +41-44182㊃9-41æèçöø÷2n . 定理3 令2n 个3圈为C 1i 3:u i 1u i 2u i 3u i 1,C 2i 3:v i 1v i 2v i 3v i 1(i =1,2, ,n ).分别连接圈C 1i 3与C 2i3的顶点u i j 与v i j (j =1,2,3;i =1,2, ,n ),再分别连接3圈C 1i 3与C 1,i +13的顶点u i 2与u i +1,3,C 2i 3与C 2,i +13的顶点v i 3与v i +1,2(i =1,2, ,n -1).这样得到的图记为2n C 6,3,如图4所示.τ(n )表示图2n C 6,3的完美匹配的数目.则τ(n )=13+31326㊃5+13æèçöø÷2n +13-31326㊃5-13æèçöø÷2n .证 欲求τ(n ),定义图G 2,并求其完美匹配的数目.将长为3的路v 2v 1u 1u 2的端点v 2和u 2分别与图2n C6,3的顶点v 12和u 13各连接一条边,得到的图记为G 2,如图5所示.显然图G 2有完美匹配.β(n )表示图G 2的完美匹配的数目.图4 图2n C 6,3图5 图G 2求β(n ).设图G 2的完美匹配的集合为M ,G 2含边u 1u 2,u 1v 1的完美匹配集合分别为M 1,M 2.则M 1ɘM 2=Ø.所以M =M 1ɣM 2,β(n )=|M |=|M 1|+|M 2|.类似于定理2的方法,容易求得:|M 1|=τ(n ),|M 2|=β(n -1).故β(n )=τ(n )+β(n -1).(5)求τ(n ).显然图2n C 6,3有完美匹配.设图2n C 6,3的完美匹配的集合为M .图2n C 6,3含边u 11u 13,u 11v 11,u 11u 12的完美匹配集合分别为M 1,M 2,M 3.则M =M 1ɣM 2ɣM 3,M i ɘM j =Ø(1ɤi <j ɤ3).所以τ(n )=|M |=|M 1|+|M 2|+|M 3|.11第2期 唐保祥,等:几类特殊图完美匹配数目的递推求法容易求得:|M 1|=τ(n -1)+β(n -2),|M 2|=2τ(n -1),|M 3|=τ(n -1).故τ(n )=4τ(n -1)+β(n -2).(6)由(5)和(6)式易得τ(n )=5τ(n -1)-3τ(n -2).(7)易知τ(1)=4,τ(2)=17,故线性递推式(7)的通解为τ(n )=13+31326㊃5+13æèçöø÷2n +13-31326㊃5-13æèçöø÷2n . 定理4 完全4部图K i 1,1,2,2的顶点集V (K i 1,1,2,2)的4分类为{u i 1,u i 2},{v i 1,v i 2},{x i },{yi }(i =1,2, ,n ).分别连接K i 1,1,2,2与K i +11,1,2,2的顶点u i 1与v i +1,2,v i 1与u i +1,2(i =1,2, ,n -1).这样得的图记为2n K 1,1,2,2,如图6所示.g (n )表示图2n K 1,1,2,2的完美匹配的数目,则g (n )=13+31326㊃11+313æèçöø÷2n +13-31326㊃11-313æèçöø÷2n .证 欲求g (n ),定义一个图G 3,并求其完美匹配的数目.将长为1的路u v 的端点u ,v 分别与K 11,1,2,2的顶点v 12,u 12连接一条边,得到的图记为G 3,如图7所示.显然图G 3有完美匹配.γ(n )表示图G 3的完美匹配的数目.图6 图2n K 1,1,2,2图7 图G 3求γ(n ).设图G 3的完美匹配的集合为M ,G 3含边u v ,u v 12的完美匹配的集合分别为M 1,M 2.则M 1ɘM 2=Ø.所以M =M 1ɣM 2,γ(n )=|M |=|M 1|+|M 2|.类似于定理2的方法,容易得到:|M 1|=g (n ),|M 2|=2g (n -1)+γ(n -1).故γ(n )=g (n )+2g (n -1)+γ(n -1).(8) 求g (n ).显然图2n K 1,1,2,2有完美匹配.设图2n K 1,1,2,2的完美匹配的集合为M ,图2n K 1,1,2,2含边v 12u 11,v 12x 1,v 12y 1,v 12u 12的完美匹配的集合分别为M i (i =1,2,3,4).则M i ɘM j =Ø(1ɤi <j ɤ4).故g (n )=|M |=|M 1|+|M 2|+|M 3|+|M 4|.容易得到:|M 1|=3g (n -1),|M 2|=g (n -1)+γ(n -1),|M 3|=g (n -1)+γ(n -1),|M 4|=2g (n -1)+γ(n -1).故g (n )=7g (n -1)+3γ(n -1).(9) 由(8)和(9)式易得g (n )=11g (n -1)-g (n -2).(10)线性递推式(10)的特征方程的根为x =11ʃ3132.易得g (1)=10,γ(1)=13.所以由(9)式得g (2)=109.故线性递推式(10)的通解为g (n )=13+31326㊃11+313æèçöø÷2n +13-31326㊃11-313æèçöø÷2n .参考文献:[1]C Y V I NSJ ,G U TMA NI .K e k u l éS t r u c t u r e s i nB e n z e n n o i dH y d r o c a r b o n s [M ].B e r l i n :S p r i n ge rP r e s s ,1988.[2] C I U C U M.E n u m e r a t i o no fP e rf e c t M a t c h i ng s i nG r a ph swi t hR e f l e c t i v eS y mm e t r y [J ].JC o m b i nT h e o r y :S e rA ,1997,77(1):87-97.[3] J O C K U S C H W.P e r f e c tM a t h i n g s a n dP e r f e c t S q u a r e s [J ].JC o m b i nT h e o r y :S e rA ,1994,67(3):100-115.[4] L O V ÁS ZL ,P L UMM E R M.M a t c h i n g T h e o r y [M ].N e w Y o r k :N o r t h -H o l l a n dP r e s s ,1986.21西南师范大学学报(自然科学版) h t t p ://x b b jb .s w u .c n 第39卷[5] V A L I A N T L G.T h eC o m p l e x s i t y o fC o m p u t i n g t h eP e r m a n e n t [J ].T h e o r e t i c a lC o m p u t eS c i e n c e ,1979,8(2):189-201.[6] Y A N W e i -g e n ,Z HA N GF u -j i .E n u m e r a t i o n o f P e r f e c tM a t c h i n g s o f aT y p e o f C a r t e s i a nP r o d u c t s o f R a p h s [J ].D i s c r e t e A p p l i e d M a t h e m a t i c s ,2006,154:145-157.[7] 唐保祥,任 韩.2类偶图完美匹配的数目[J ].西南大学学报:自然科学版,2012,34(10):91-95.[8] 唐保祥,李 刚,任 韩.3类图完美匹配的数目[J ].浙江大学学报:理学版,2011,38(4):16-19.[9] 唐保祥,任 韩.2类图完美匹配的数目[J ].西南师范大学学报:自然科学版,2011,36(5):16-21.[10]唐保祥,任 韩.4类图完美匹配的计数[J ].武汉大学学报:理学版,2012,58(5):441-446.O nR e c u r s i v eM e t h o d f o rF i n d i n g S e v e r a l T y pe s P a r t i c u l a rG r a p h s t h eN u m b e r o fP e rf e c tM a t c h i n gs T A N GB a o -x i a n g 1, R E N H a n 21.S c h o o l o fM a t h e m a t i c sa n dS t a t i s t i c s ,T i a n s h u i N o r m a l U n i v e r s i t y ,T i a n s h u i G a n s u 741001,C h i n a ;2.D e p a r t m e n t o fM a t h e m a t i c s ,E a s t C h i n aN o r m a l U n i v e r s i t y ,S h a n gh a i 200062,C h i n a A b s t r a c t :M a t c h i n g c o u n t i n g t h e o r y i s a t t h e c o r eo f g r a p h t h e o r y ,s i n c e i t o r i g i n s f r o m b o t h p h ys i c s a n d c h e m i s t r y .H o w e v e r ,t h e p r o b l e mo f c o u n t i n g t h en u m b e r o f p e r f e c tm a t c h i n g s f o r g e n e r a l g r a p h s i sN P -h a r d .I nt h i s p a p e r ,b y a p p l y i n g d i f f e r e n t i a t i o n ,s u mm a t i o na n dr e -r e c u r s i o nc a l c u l a t i o n ,t h es e v e r a l c o u n t i n g f o r m u l a s o f t h e p e r f e c tm a t c h i n g f o r f o u r s p e c i f i c t y p e s o f g r a ph s h a v eb e e n g i v e n .K e y wo r d s :p e r f e c tm a t c h i n g ;l i n e a r r e c u r r e n c e r e l a t i o n ;c h a r a c t e r i s t i c e q u a t i o n 责任编辑 廖 坤31第2期 唐保祥,等:几类特殊图完美匹配数目的递推求法。

基于模态分析理论的结合部动刚度辨识

基于模态分析理论的结合部动刚度辨识

基于模态分析理论的结合部动刚度辨识董冠华;殷勤;刘蕴;殷国富【摘要】Accurate identification of the dynamic information is an important prerequisite for the combination of structural dynamics modeling.In this paper,the method of the dynamic stiffness identification was studied based on the theory of modal analysis.Firstly,we constructed a generalized dynamics model containing the dynamicinformation,discussed the characteristics of the joint dynamics from the theory of modal analysis influencing between the natural frequency and the combination structure and established the relationship between them.Furthermore,we built an ideal finite element model by the mass and spring-damper and identified the joint stiffness by the natural frequency obtained by numerical analysis.The maximum error between the identification and the theoretical value was 1.92%.At last,we applied modal test on bolt joints,the measured natural frequency of the typical mode of vibration in normal and tangential direction as the index,through the MATLAB-ANSYS integration platform to identify the bolt joint stiffness.Moreover,the obtained results were input to the finite element model.The maximum error between the predicted value and measured value was 3.01%.The numerical value and the test value were allideal,demonstrating the feasibility of the method.At the same time,the dynamic stiffness identified by the measured natural frequency of the typical mode of vibration was a very good predictor of other order naturalfrequency distribution of the bolt connection structure,demonstrating that the bolt in a larger pretightening force;dynamic characteristics met the linear assumption.%结合部动力学特性对机械系统动力学性能具有显著影响,结合部动力学信息的准确辨识是组合结构动力学建模的重要前提.基于模态分析理论对结合部动刚度辨识方法进行了深入研究:首先,建立了包含结合部动力学信息的广义动力学模型,从模态分析理论出发,讨论了结合部动力学特性对组合结构固有频率的影响,建立了两者的映射关系;进而,采用质量单元与弹簧阻尼单元建立了理想的动力学有限元模型,通过模态分析所得的固有频率对结合部刚度进行辨识,辨识值与理论值之间最大误差为1.92%;最后,对螺栓连接组合结构进行了模态试验,以所测得的法向及切向典型振型对应固有频率为指标,通过搭建的MATLAB-ANSYS集成平台对螺栓结合部刚度进行辨识,并将所辨识的结合部刚度录入有限元模型,栓接结构固有频率的有限元预测值与实测值之间最大误差率为3.01%;数值模拟试验与现场模态试验的辨识效果均较为理想,验证了方法的可行性.同时,以栓接结构典型振型对应固有频率为指标辨识的结合部动力学刚度信息很好预测其他各阶固有频率的分布,表征和印证了栓接结构在较大预紧力作用下,螺栓结合部非线性动力学特性得到了抑制,满足线性条件假设.【期刊名称】《振动与冲击》【年(卷),期】2017(036)020【总页数】7页(P125-131)【关键词】动力学;结合部;刚度;模态分析【作者】董冠华;殷勤;刘蕴;殷国富【作者单位】四川大学制造科学与工程学院,成都610065;四川大学制造科学与工程学院,成都610065;四川大学制造科学与工程学院,成都610065;四川大学制造科学与工程学院,成都610065【正文语种】中文【中图分类】TH113复杂机械系统均是由不同零部件相互组合而成。

3类特殊图完美匹配数的计算公式

3类特殊图完美匹配数的计算公式

3类特殊图完美匹配数的计算公式唐保祥;任韩【摘要】图的完美对集计数问题已经被证实是NP-难问题,因此要得到一般图的完美对集的数目是非常困难的.该问题在蛋白质结构预测、晶体物理学、计算机科学和量子化学中都有重要的应用,对此问题的研究具有非常重要的理论价值和现实意义.用划分,求和,再递推的方法分别给出了图3-nT4,5-nT6和2-2nQ2×2的完美匹配数目的计算公式,为图的完美匹配问题的应用提供了理论支持.%Perfect matching counting problems graph has been proven to be NP-hard.To get the number of perfectly matched general graph is very difficult.The issue has important applications in protein structure prediction,crystal physics,quantum chemistry and computer science.The research on this issue has very important theoretical and practical significance.The counting formula of the perfect matching for graphs 3-nT4,5-nT6and 2-2nQ2×2 are obtained by applying differentiation,summation and re-recursion.This provides the theory support for the application of perfect matching in graph.【期刊名称】《中山大学学报(自然科学版)》【年(卷),期】2017(056)003【总页数】5页(P36-40)【关键词】完美匹配;梯子;递推式;棋盘【作者】唐保祥;任韩【作者单位】天水师范学院数学与统计学院,甘肃天水 741001;华东师范大学数学系,上海 200062【正文语种】中文【中图分类】O157.5图的完美匹配计数理论的研究成果已经在化学、物理学和计算机科学中得到应用,图的完美匹配的理论在很多领域有广泛应用,例如:积和式在计算机科学,特别是计算复杂性理论中有重要的地位,二分图的完美匹配的数目可以方便地表示为计算积和式的值;它也是组合数学的思想源泉,因此受到众多学者的关注[1-14],本文给出了3类图完美匹配数目的计算公式,文中所给方法,适合相同结构重复出现的很多类图完美匹配数的求解。

Theories of International Migration国际移民理论幻灯片PPT

Theories of International Migration国际移民理论幻灯片PPT
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The New Economics of Migration
Proposition: Migration decisions are not made by isolated individual
actors, but by larger units of related people typically families or households not only to maximize their income but also to minimize risks and constraints.
conceptualize causal processes of how international migration is “initiated” and “maintained” or “perpetuated”.
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பைடு நூலகம்
The Purpose of a Thorough Review on Theories of International Migration
Structural demands of developed countries
Market and cultural penetration from the core to peripherals
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Neoclassical Economics: Combining Macro and Micro
Neoclassical economics (micro)
Individual
New Economics
Household
Dual Labor Market World systems theory
Structural (Internal) Structural (International)
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arXiv:hep-ph/9212241v2 10 Dec 1992
Theoretical Implications of the Combined Solar Neutrino Observations
S.A. Bludman, N. Hata, D.C. Kennedy, P.G. Langacker Department of Physics, University of Pennsylvania, Philadelphia, PA 19104∗
Constraints on the core temperature of the Sun and on neutrino-oscillation parameters are obtained by comparing the combined Homestake, Kamiokande, SAGE and GALLEX solar neutrino data with Standard Solar Models (SSM) and with non-standard solar models parameterized by a phenomenological central temperature (Tc). If the Sun is 2% cooler or 3% warmer than predicted by SSMs, the MSW parameters we determine are consistent with different grand unified theories.
3. MSW Fits With Non-Standard Core Temperatures
If, indeed, Tc = 15.67 × 106K, as obtained, for example, in the latest Bahcall-Pinsonneault SSM with helium diffusion, then both the small and large neutrino mixing angle fits in Fig. 1 differ significantly from the corresponding (CKM) quark mixing angles. If, together with MSW oscillations, we allow a non-standard core temperature, Fig. 2 shows that the experiments themselves at 90% C.L. determine the core temperature: relative to the theoretical value, Tc = 1.03+−00..0035 for the non-adiabatic fit, Tc = 1.05+−00..0017 for the large-angle fit, both consistent with all SSMs.
Fig. 3 shows that for central temperatures within 7-9 (2-3) times the theoretical uncertainty quoted by Bahcall and Ulrich (TurckChi`eze et al), the neutrino parameters can fit in regions preferred by different grand unified theories (GUTs): A 2% cooler Sun practically excludes the Cabibbo-angle solution θ = θuc, but extends ∆m2, sin2 2θ to values θ = θut implied by the supersymmetric SO(10) GUT; a 3 − 4% warmer Sun practically excludes the θ = θut solution, but extends the allowed parameter space to values θ = θuc suggested by intermediate-scale SO(10) GUT and for which the ντ may be cosmologically significant. Superstring-inspired models are consistent with all parameter fits.
between the non-adiabatic and large-angle solutions allowed by present experiments.
1. Purely Astrophysical (Cooler Sun) Explanation for the Observed Solar Neutrino Deficit is Most Unlikely
Not only is a simultaneous fit of the Homestake and Kamiokande data incompatible with any temperature in the Sun at > 99.99% C.L., but the central GALLEX value by itself quires a 14% cooler Sun and is already excluded at 65% C.L.
∗Supported in part by DOE Contract No. DOE-AC02-76ERO-3071
2
4. Neutrino Spectral Distortion
In the large-angle MSW solution, the νe suppression is approximately energy-independent. For the energies to be detected at the Sudbury Neutrino Observatory or Super-Kamiokande, the non-adiabatic solution suppresses low-energy νe more than high- energy neutrinos. Consequently, such observations can confirm the MSW effect and, by distinguishing between the two spectral shapes predicted in Fig. 4, can choose
2. Matter-Amplified Electron-Neutrino Oscillations in the Sun
If we assume this simplest particle physics interpretation for a persistent solar neutrino deficit, then the data and the SSM constrain the MSW parameters (neutrino masses, vacuum mixing angles) to lie in either of two small regions: non-adiabatic oscillations with ∆m2 = (3 − 12) meV2, sin2 2θ = (0.4 − 1.5) × 10−2, or large mixing-angle oscillations with ∆m2 = (3 − 40) meV2, sin2 2θ = 0.5 − 0.9. (Fig. 1) The non-adiabatic solution gives the considerably better fit. Together with Homestake and Kamiokande, the GALLEX experiment constrains ∆m2 = (3 − 40) meV2, which suggests that lowenergy pp neutrinos are not oscillating appreciably. The vacuum mixing angles fitted are sensitive to the Sun’s central temperature.
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