HyperStudy优化

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HyperStudy软件-结构优化

HyperStudy软件-结构优化

Nodal data(节点数据), element data(单元数据)
二进制文件,内容为模型信息与计算结果
.odb 如果要得到向量中的具体元素的数值,需要使用 resvector() 函数。
A
8
HyperStudy的输出文件
针对不同求解器输出结果所支持的文件类型
Solver
Result
Model volume(模型体积), Mass(质量), Frequency(模态频率), Buckling factor(屈曲因子)
摄动面板下产生的结构的形状)
结构的灵敏度分析、优化 形状优化
A
3
设计变量的定义
二 用于制造工艺优化的设计变量
1)Hyperform可用的设计变量:
• Sheet thickness(钣金厚度) • Friction(摩擦系数) • Forces(载荷) • Shapes(as create by HyperMorph)(通过hypermorph定义的形状)
二进制结果文件
.A00
如果要得到向量中的具体元素的数值,需要使 用 resvector() 函数
HyperStudy 优化
A
1
HyperStudy分析时所支持的求解器:
• Abaqus • ANASYS • LS-DYNA • Nastran • OptiStruct • PAM-CRASH 2G • RADIOSS • HyperForm • MADYMO • ADAMS
A
2
设计变量的定义
A
5
设计变量的定义
三 各求解器所支持的设计变量及对应的参数类型
A
6
HyperStudy的输入文件

给求解器插上优化的翅膀:HyperStudy连接第三方求解器

给求解器插上优化的翅膀:HyperStudy连接第三方求解器
吸能盒优化:响应
Copyright © 2012 Altair Engineering, Inc. Proprietary and Confidential. All rights reserved.
吸能盒优化:响应面
Copyright © 2012 Altair Engineering, Inc. Proprietary and Confidential. All rights reserved.
OptiStruct - 完整的结构分析解决方案
• 静态线性和非线性准静态分析 • 线性热应力分析 • 惯性释放 • 屈曲分析(可带预应力) • 正则模态/复模态(可带预应力) • 频率响应(模态法,直接法) • 瞬态响应(模态法,直接法) • NVH分析 (包括流固耦合) • 谱分析(随机谱、响应谱) • 疲劳分析 • 超单元 • 瞬态和稳态传热分析 • 复材分析 • 转子动力学 •…
OptiStruct设计阶段
完整的有限分析求解器
详细设计
自由形状 形状 尺寸
Gauge9 & 10
Optimization
Gauge1, 2 & 3
Gauge11, 12 & 13 Gauge14 &15
Gauge4
Gauge5
Gauge6 Gauge7
Copyright © 2013 Altair Engineering, Inc. Proprietary and Confidential. All rights reserved.
Copyright © 2012 Altair Engineering, Inc. Proprietary and Confidential. All rights reserved.

基于HyperStudy平台的材料参数优化

基于HyperStudy平台的材料参数优化

基于HyperStudy平台的材料参数优化基于HyperStudy平台的材料参数优化杨萌华为技术有限公司深圳518057摘要:针对当前仿真工作中仿真结果与实际测试结果存在一定差异的问题,本文应用HyperStudy软件的参数优化功能,对镁合金板条的材料参数进行了优化。

确定优化方法后在三点弯折工况下对手机复杂结构件材料参数进行优化,并将优化后材料参数在结构件不同工况下进行了验证。

研究结果表明:通过HyperStudy的材料参数优化方法,获得了更适用于仿真的材料参数,从而有效的解决了仿真结果和实际测试结果之间的差异问题。

关键词:HyperStudy,多参数优化,仿真,曲线匹配0引言仿真中输入材料的拉伸测试数据,来计算试件在其他工况下的行为,仿真计算曲线常与实际测试曲线存在一定差异(如图1所示)。

导致该差异的因素包括:有限元建模的误差、求解器计算的误差、边界条件的误差、材料参数的误差。

将前三个影响因素降至最低的情况下,仍不能实现测试曲线与仿真曲线的匹配,则需优化仿真输入的材料参数,使仿真曲线与测试曲线趋于一致。

本文采用HyperStudy软件,对镁合金板条进行材料参数优化。

确定优化方法后对复杂结构件镁合金支架进行三点弯折工况下的优化。

将优化所得的材料参数代入镁合金支架四点弯折仿真模型和扭转仿真模型进行计算。

并分别将计算所得的“力-位移”曲线与测试曲线对比,验证仿真曲线与测试曲线是否一致。

图1 测试曲线与仿真曲线存在较大差异1有限元分析模型建立本例采用HyperMesh软件建立有限元模型。

试件四点弯折有限元模型如图2所示。

试件长51.4mm,宽10.2mm,厚0.45mm。

仿真求解压头的“力-位移”曲线。

图2 四点弯折工况有限元模型1.1网格与节点仿真模型中压头及支撑杆为刚体,试件所用网格类型及网格数目如表1所示。

表1 四点弯折试件所用网格1.2 材料与属性试件材料为镁合金,密度为0.0018g/mm3,泊松比为0.28,弹性模量E=44.8GPa。

通用优化平台介绍

通用优化平台介绍

四、通用优化平台调用外部求解器流程
任意支持文本输入、输出的求解器都可以被优化平台调用,如SAP2000、 ETABS、GSA等,同时为了提取特定的结果如位移角、轴压比,或者定义特殊的 设计变量如形状参数等,往往要求求解器具有API接口(以上程序均具备)。 定义模板 文件(S2K)
优化 平台
S2K文件
约束:
剪重比>=0.048 位移角<=0.0013 墙轴压比<=0.5
目标:重量最小 迭代28次,重量减小15%
六、通用优化平台优缺点
商业程序,算法可靠、鲁棒性高 优点: 可以有效处理离散变量,以满足截面尺寸模数化的要求
可以调用常用的结构分析软件,从而可以方便的提取结构专 业所关心的响应,如位移角、周期、构件应力、轴压比等,以加 以约束或优化。
Optimal member area: A 1 40.861; A2 32.489; A3 29.715
Hyperstudy A=1 迭代次数 16
LS-OPT A=1 不收敛
Hyperstudy A=7 8
LS-OPT A=7 10
2 、框架剪力墙结构优化 设计变量:梁、柱截面及剪力墙厚度(共15个) 周期<=1.3s
缺点: 迭代次数较准则法多,并且与设计变量个数有关系,因此对设 计变量个数有一定限制 Hyperstudy的优化策略更适合建筑结构专业的优化,运 算次数较LS-OPT要少 Hyperstudy和 LS-OPT比较: LS-OPT的优化策略更适合全局搜索,Hyperstudy是局 部搜索,能否找到全局最优解与初始值有关 LS-OPT支持并行计算,但由于其运算次数非常多,尤其 是设计变量很多的情况下,因此其优化效率仍然较低
结构通用优化平台Hyperstudy/LS-OPT介绍

陈卫卫_HyperStudy在新涡桨飞机鸟体本构模型参数反演中的应用

陈卫卫_HyperStudy在新涡桨飞机鸟体本构模型参数反演中的应用

yP +1 = [ y1 , y2 ,, yP , yP +1 ] = [ yP , yP +1 ] …………(5)
T T
相应的基矩阵: X P +1 = X P , X T 相应的回归系数向量为:
[
] ,其中, X
T
= [1, h2 ( xP+1 ),, hN ( xP+1 )]
β P+1 = CP+1 BP+1 = β P + ∆β = β P + K P+1 y P+1 − X β P ………(6)
Key words: parameter inversion, DOE, ARSM, HyperStudy, RADIOSS
1 前言
在新涡桨飞机的研制中,按照适航规章要求需对处于鸟撞区域内的结构进行抗鸟撞设计[1]。结 构抗鸟撞设计主要通过数值仿真分析和实验室试验相结合的方法进行[2,3],而鸟体本构模型与鸟体材 料参数作为鸟撞数值仿真计算的基本性能数据是开展结构抗鸟撞设计分析的基础。鸟体参数反演其 实就是鸟体参数的识别问题,通过修正鸟体模型的材料参数、本构方程的参数以及鸟体离散后的单 元或粒子属性参数等,使得测试点仿真的结果,如应力、应变、位移等,与试验结果差异最小。该 方法避免了传统的人工试凑法依赖于工程师的经验所具有的主观、盲目、耗时等弊端,提高了仿真 精度,省掉了一些试验次数,从而节省设计的费用及缩短周期。 本文针对这一问题, 利用新涡桨飞机平板鸟撞试验的试验数据, 将RADIOSS和HyperStudy相结 合,对鸟体本构模型参数进行了反演与优化,并对优化反演得到的参数进行验证。
3.2 优化目标
鸟撞试验测量结果一般包括结构的位移、应变响应和撞击力等。基于优化的参数反演,通常是 选取能够对理论和试验结果之间的误差进行量化的目标函数, 通过搜索合适参数使目标函数最小化。 选择测试点位移的计算结果与试验结果之间相对误差的平方和为目标函数。

02-OptiStruct&HyperStudy 12.0 新功能roadshow_final

02-OptiStruct&HyperStudy 12.0 新功能roadshow_final

OptiStruct 制造工艺约束
尺寸控制
尺寸控制
挤压约束
离散系数
模式重复
对称
拨模约束
Copyright © 2013 Altair Engineering, Inc. Proprietary and Confidential. All rights reserved.
HyperStudy 功能
Copyright © 2013 Altair Engineering, Inc. Proprietary and Confidential. All rights reserved.
自由尺寸优化——制造约束
• H3D结果中显示制造约束
• 为每个方向的铺层指定厚度约束 和drop off约束 • 添加PLYDRP约束后柔度增加20% • 材料分布更加均匀,单个铺层更加完整
No Drop-Off Constraint
Ply Thickness
Ply Drop-Off Contour Max =20%
HyperStudy 特点
形状优化
与HyperMorph 无缝集成
直接导入参数
自动从HyperMesh, MotionView, HyperForm中 导入设计变量
无缝读取结果
直接读取主流CAE 软件结果: Abaqus,
数据挖掘
相关性分析, SnakeView, 主成
领先技术
一流的实验设计, 响应面构建和 优化方法
Copyright © 2013 Altair Engineering, Inc. Proprietary and Confidential. All rights reserved.
拓扑优化
• 水平集法

基于HyperStudy平台的材料参数优化(完整资料)

基于HyperStudy平台的材料参数优化(完整资料)

基于HyperStudy平台的材料参数优化(完整资料)(可以直接使用,可编辑优秀版资料,欢迎下载)基于HyperStudy平台的材料参数优化基于HyperStudy平台的材料参数优化杨萌华为技术有限公司深圳518057摘要:针对当前仿真工作中仿真结果与实际测试结果存在一定差异的问题,本文应用HyperStudy软件的参数优化功能,对镁合金板条的材料参数进行了优化.确定优化方法后在三点弯折工况下对手机复杂结构件材料参数进行优化,并将优化后材料参数在结构件不同工况下进行了验证.研究结果表明:通过HyperStudy的材料参数优化方法,获得了更适用于仿真的材料参数,从而有效的解决了仿真结果和实际测试结果之间的差异问题。

关键词:Hy perStudy,多参数优化,仿真,曲线匹配0引言仿真中输入材料的拉伸测试数据,来计算试件在其他工况下的行为,仿真计算曲线常与实际测试曲线存在一定差异(如图1所示).导致该差异的因素包括:有限元建模的误差、求解器计算的误差、边界条件的误差、材料参数的误差。

将前三个影响因素降至最低的情况下,仍不能实现测试曲线与仿真曲线的匹配,则需优化仿真输入的材料参数,使仿真曲线与测试曲线趋于一致。

本文采用HyperStudy软件,对镁合金板条进行材料参数优化.确定优化方法后对复杂结构件镁合金支架进行三点弯折工况下的优化。

将优化所得的材料参数代入镁合金支架四点弯折仿真模型和扭转仿真模型进行计算.并分别将计算所得的“力—位移”曲线与测试曲线对比,验证仿真曲线与测试曲线是否一致。

图1 测试曲线与仿真曲线存在较大差异1有限元分析模型建立本例采用HyperMesh软件建立有限元模型。

试件四点弯折有限元模型如图2所示。

试件长51.4mm,宽10。

2mm,厚0.45mm。

仿真求解压头的“力—位移”曲线。

图2四点弯折工况有限元模型1.1网格与节点仿真模型中压头及支撑杆为刚体,试件所用网格类型及网格数目如表1所示.表1四点弯折试件所用网格1.2 材料与属性试件材料为镁合金,密度为0.0018g/mm3,泊松比为0。

杨 明_基于HyperStudy的DOE设计方法

杨  明_基于HyperStudy的DOE设计方法

基于HyperStudy的DOE设计方法杨明赵俊杰艾联(中国)汽车零部件有限公司基于HyperStudy的DOE设计方法杨明赵俊杰(艾联(中国)汽车零部件有限公司)摘 要:借助于Altair公司的HyperStudy模块,对整车中的局部模型做非线性的DOE处理,通过改变结构加强件中的个别部件厚度,比较非线性的分析结果,寻找最佳的设计效果。

关键字:DOE,优化设计,HyperStudyAbstract:Applying the HyperStudy of Altair company, operate nonlinear analysis for part model of whole vehicle with DOE, change some structure strength parts thickness and compare the analysis result in order to find the best optimization design effects.Key words: DOE, Optimize Design, HyperStudy1 概述目前很多设计需要设计者考虑不同的设计参数,通过这些设计参数来确定一个最优的设计方案,伴随其出现的就是DOE的一种设计理念。

DOE又称试验设计,被广泛的用于各方面的设计工作,目的在于进行试验设计以减少试验次数,并且保证获得充分的信息,从而简化数据处理,节省人力物力和时间。

正确合理的试验设计,可使试验结果的可靠性显著提高,试验设计还可以为寻求参数的优化数值和选择最佳工艺方案指明方向。

HyperStudy的前身是Altair公司HyperWorks系列产品中的StudyWizard,是一个HyperWorks软件包中的一款主要产品。

它主要用于CAE环境下DOE (试验设计),优化,以及随机分析研究。

HyperStudy具有良好的集成性,可以从HyperMesh, HyperForm, 和MotionView软件直接启动同时获取设计参量等,同时可与多种外部求解器合并使用,进行线性和非线性的DOE、优化和随机分析。

OptiStruct及HyperStudy优化与工程应用

OptiStruct及HyperStudy优化与工程应用

第9章 Altair概念设计优化流程与多学科优化工具
9.1仿真驱动设计 9.2概念设计优化流程Altair C123 9.3 C123概念设计优化流程的应用 9.4多学科优化
第10章 HyperStudy简介与理论基础
10.1 HyperStudy简介 10.2 HyperStudy中的方法
第11章建立HyperStudy模型
第15章随机性分析
15.1概念和流程 15.2随机变量定义及采样 15.3结果后处理
第16章 HyperStudy技术专题
16.1 HyperStudy文件管理 16.2使用Verify进行响应面结果验证 16.3自定义求解器 16.4使用高性能计算
读书笔记
读书笔记
这是《OptiStruct及HyperStudy优化与工程应用》的读书笔记模板,可以替换为自己的心得。
第13章响应面拟合
13.1响应面拟合简介 13.2实例:汽车踏板机构响应面拟合 13.3响应面拟合基本概念及算法 13.4工程实例
第14章 HyperStudy优化
14.1 HyperStudy优化简介 14.2多目标优化 14.3多模型与多学科优化 14.4不确定性优化 14.5优化算法 14.6复杂优化问题的解决思路 14.7基于各类求解器的HyperStudy应用
理论基础
第11章建立 HyperStudy模型
第12章试验设计 (DOE)
第13章响应面拟合
第14章 HyperStudy优化
第15章随机性分析
第16章 HyperStudy技术专 题
第1章 OptiStruct简介
1.1 OptiStruct功能概述 1.2帮助文件使用指南 文件内容解释 1.4 OptiStruct优化的一些常用操作 1.5优化控制卡片

HyperStudy——健壮性设计开发的参数化研究和多学科优化工具

HyperStudy——健壮性设计开发的参数化研究和多学科优化工具

HyperStudy——健壮性设计开发的参数化研究和多学科优化工具HyperStudy是一个HyperWorks软件包中的一款主要产品。

它主要用于CAE环境下DOE (试验设计),优化,以及随机分析研究。

HyperStudy的前身是Altair公司HyperWorks系列产品中的StudyWizard。

HyperStudy具有导向式结构易于学习。

适用于研究不同变化条件下设计变量的特性,包括非线形特性。

还能应用在合并不同类型分析的跨学科领域中。

模型易于参数化。

除了传统意义上定义输入资料为设计变量,有限元的形状也能够被参数化。

HyperStudy具有良好的集成性,可以从HyperMesh, HyperForm, 和MotionView软件直接启动同时获取设计参量等。

HyperMorph可用于是形状参数的生成。

同时可与多种外部求解器合并使用,进行线性和非线性的DOE、优化和随机分析。

外部求解器类型∙Abaqus∙Ansys∙XY data∙Dads∙LS-Dyna∙Adams∙Pam-Crash∙Nastran∙Excel data∙Madymo∙Altair OptiStruct∙Simpack∙Altair HyperForm∙Radioss∙Altair MotionSolve∙HyperMesh result fileDOE研究DOE又称试验设计,目的在于进行试验设计以减少试验次数,并且保证获得充分的信息,从而简化数据处理,节省人力物力和时间。

正确合理的试验设计,可使试验结果的可靠性显著提高。

试验设计还可以为寻求参数的优化数值和选择最佳工艺方案指明方向。

试验研究的目标在于研究参数变化对于模型特性的影响,确定哪一种因素对于特定响应最具有影响。

确定输入变量为何值时使得响应接近期望值,或者输出响应的变化性非常小,以及非控制变量的效应最小化。

试验设计能够定义一系列测试用于有目的识别或观察参数变化对输出响应变化。

基于HyperStudy的心血管支架结构优化

基于HyperStudy的心血管支架结构优化

基于HyperStudy的心血管支架结构优化Optimization of Stent Structure based on HyperStudy张雯,刘祥坤1高超2(1上海微创医疗器械(集团)有限公司,上海,201203)(2上海惠骋实业发展有限公司,上海,200436)摘要:血管内支架的力学性能研究对解决在支架植入后的破坏问题非常重要。

使用常规方法研究支架性能会有很大困难,成本昂贵。

随着有限元法的发展,在支架设计和性能检测中有限元已成为不可或缺的工具。

为了提高支架设计的性能和效率,有限元技术及专业CAE软件结合,对冠脉血管支架进行多学科结构优化设计。

本文将支架几何模型转化为参数化有限元模型,建立morph后的形状变量模型,提交HyperStudy 采用多种优化策略进行针对前两种工况的形状优化,并最终进行验证。

关键词:血管支架,多学科结构优化,HyperStudyAbstract:Mechanical properties of intravascular stent is very important in solving the problem of damage after stent implantation. The study of stents properties will be difficult and expensive using traditional methods. With the development of finite element method, the new method has become an indispensable tool in the stent design and performance testing. In order to improve the performance and efficiency of the stent design, multidisciplinary structural optimization with FEM and professional CAE software should be used in coronary stent design. This paper will convert the geometry models into parametric FEM model, establish a shape-variable model, submit to HyperStudy for shape optimization of the first two working conditions, and validate the result.Key words:stents, multidisciplinary structural optimization, HyperStudy1 引言血管内支架放置术已广泛应用于心血管疾病介入性治疗,但支架在植入后的破坏问题还需要研究解决,因此支架的力学性能研究非常重要。

HyperStudy 优化案例

HyperStudy 优化案例

DO NOT DISTRIBUTE ALTAIR INTERNAL ONLY CONTACT FATMA KOCER at fatma@Studying Cell Phone Drop Using HyperWorksBuilding Durability into Products during the Design Process A drop test involves orienting an object with respect to an assumed gravitational field and allowing it to drop from some specified height under the influence of gravity onto a flat, rigid surface. It is significant in several industries, such as in the nuclear industry, where the integrity of containers carrying radioactive waste must be insured during accident scenarios. It is also important in the retail electronics industry, where manufacturers produce products such as cell phones that can be dropped while being used and continue to operate.Studying Drop-Test Behavior Conducting drop tests to investigate the impact behavior and identify failure mechanisms of a clam-shell cell phone is generally an expensive and timeconsuming process. Nevertheless, strict drop/impact performance criteria play a decisive role in their design, because they must withstand such unexpected shocks. As a result, in the development of a new cell phone, it is of great importance to asses the general mechanical properties in an early stage, using simulations to avoid timeconsuming design iterations. Drop-test simulations will help improve the components’ impact resistance and anticipate problem areas.X ft dropFigure 1. (Left) Closed-Front Drop Simulation (image is purposely made indistinct); (right) Clam-Shell Phone Cross-Section Showing the Stress Wave Path from Ground to LCD ModulePORON1DO NOT DISTRIBUTE ALTAIR INTERNAL ONLY CONTACT FATMA KOCER at fatma@Figure 2. (Left) PORON Pad Adhered at Flip Housing; (right) Maximum COG Logarithmic (LE) StrainIn cell phones, closed-front drop tests cause more cracks on the liquid crystal display (LCD) than other drop tests, because the stress wave propagates by way of the flip top to the LCD (Fig. 1). In this study, there is a PORON pad on the flip housing (Fig. 2) that serves to minimize the B2B connector disengagement during cell phone drops. PORON is a high-performance material that features a unique cell structure with high levels of density, minuteness and uniformity and is used for dampening vibration and preventing slip. The position of this PORON pad dictates the stress-wave path as stress waves propagate inwards during a closed-front drop test. As a result, its position has a significant influence on internal components, such as Chip-on-Glass (COG), a chip that mounts the LCD driver chip to the contact edge of the LCD glass. As such, during front-drop test simulations, the objective is to minimize the maximum strain on COG. In the earlier design development, analysts used conventional design processes to find the position of the PORON pad adhered to the flip-top housing that would minimize the COG strain. Drop test is a computationally demanding simulation, and, therefore, this work was performed by changing the pad position in 1 mm steps within the design space, and running a series of simulations. Experiencing the tremendous user interaction during this process and the fact that an optimal design is not guaranteed, it was decided to automate the process with HyperStudy in order to perform such work more quickly and efficiently.Finding the Optimum Location In discussing optimization of the location for a PORON pad at the flip housing in a clam shell phone, the position of the pad has significant effect on the stress-wave propagation in closed-front drops. As a result, optimization of its location is crucial to2DO NOT DISTRIBUTE ALTAIR INTERNAL ONLY CONTACT FATMA KOCER at fatma@ the reliability of the vulnerable internal components. The front drops are simulated using explicit analysis in ABAQUS. The finite-element (FE) models for such simulations are approximately 80 MBytes and simulations take approximately 12 hours using the SGI Altix. Typically, the optimum PORON pad position is searched by analysing the results from a previous simulation, creating a new design and running a simulation. Then, the loop is repeated until a satisfactory design is found. This design process not only requires tremendous user interaction, but it is errorprone and does not guarantee optimum design.In this study, PORON pad location is optimized using the HyperWorks suite of tools and ABAQUS. HyperMesh (the FE analysis and computational fluid dynamics preprocessor) is used to prepare the ABAQUS input deck and to create a shape variable for the PORON pad position. HyperStudy (the solver neutral design study, exploration and optimization tool) is used to automate the design process as well as find the optimum design. Both HyperMesh and HyperStudy are part of HyperWorks. As the ABAQUS simulation is a computationally demanding one on this project, it is run in SGI Altix System while HyperWorks is run in the Windows workstation. PBS Professional is used as the workload management system. The challenge in this study is to provide a robust and efficient communication between the two platforms as well as between HyperWorks and ABAQUS.The Study Process As mentioned earlier, the position of the pad adhered at the flip housing is crucial to vulnerable internal components because of its effect on the stress-wave propagation path in a closed-front drop. As a result the objective of this study is to develop a process to find the PORON pad location that minimizes the maximum strain on COG. The design space for the PORON pad can be seen in Figure 3.Design Space3DO NOT DISTRIBUTE ALTAIR INTERNAL ONLY CONTACT FATMA KOCER at fatma@ Figure 3. Design Space for the PORON Pad First, the required material, contact and step definitions of the drop model are entered in HyperMesh, including the already-defined node/element definition. Accordingly, the ABAQUS input file generated in HyperMesh runs in ABQ/Explicit, without any need for user interaction. HyperMesh is also used to create a shape variable for the pad position. HyperMesh includes HyperMorph, a tool for doing parametric mesh-based shape changes (morphing). In the morphing process, domains are created around the FE model. Handles are defined on certain nodes of these domains. By moving a handle, nodes in the associated domain will also move. Each such movement can then be saved as a shape variable (Figure 4). Mesh distortion is minimized by applying smoothing algorithms. Note that node and element numbering are not changed during morphingStart from base analysisParameterize model with HyperMorphDrag handles to generate shape variationsSave shapes as design variableOptimization to find best shapeFigure 4. Shape Optimization ProcessShape variables created in HyperMesh are then exported to HyperStudy. In HyperStudy, the study is set up by identifying how to modify the input deck corresponding to a change in the design (i.e. PORON pad location), how to extract the responses from the simulation output file (i.e. maximum COG strain) and the optimization method. As explicit drop-test simulation cannot easily be handled in the Windows workstation where HyperWorks is running, HyperStudy will be submitting the drop simulations to SGI Altix machine and retrieve the results. PBS Professional is used as the job management tool. Furthermore, three scripts are created to facilitate submitting and monitoring in PBS Professional in the SGI Altix system and result retrieval after each simulation. The submission script resides at the Windows4DO NOT DISTRIBUTE ALTAIR INTERNAL ONLY CONTACT FATMA KOCER at fatma@ workstation with the other two scripts at the SGI server. After defining the problem, a nominal run is manually executed within HyperStudy, using the customized execution script in which the script will transfer input, material file and python script into the SGI Altix compute server. The PBS Professional submission script will then be automatically activated to submit the job. Its progress is continuously checked by the monitoring script at the SGI server. When the job completes, the python script is executed, and the required results are extracted, before being automatically transferred back to the Windows workstation and analysed by HyperStudy. Upon the completion of the nominal run, the optimization will commence. Each run will be executed by way of the same process described earlier, until the convergence as stipulated in the HyperStudy is met. Figure 5 summarizes various steps involved in creating the optimization study in two environments (Windows, Altix) with two tools (HyperWorks and ABAQUS).Create Input FileHyperMesh Define Shape VariablesSet Up Study HyperStudy Submit Simulation SGI AltixRun Simulation Update Design Extract ResponsesNoConverged?YesPost-Process Results5DO NOT DISTRIBUTE ALTAIR INTERNAL ONLY CONTACT FATMA KOCER at fatma@ Figure 5. Optimization Process Steps In HyperStudy, the objective of the optimization study is to minimize the maximum logarithmic strain of COG elements. As this is a computationally demanding simulation and the main purpose here is to establish a design process rather than to perform extensive optimization studies, the number of iterations is limited to 20. In this study, Sequential Response Surface method is used for optimization. In this method, the system responses are approximated by a quadratic polynomial that is determined in each iteration step from the results of the current and earlier iterations. A least-square method is used to define the polynomialFigure 6. (Left) Design History of PORON Pad Location and (right) COG strainFigure 6 shows the iteration history for the design variable and response respectively available at the post-processing window of HyperStudy. In the first two iterations, the shape variable stays at 0.5mm to 0.6mm, but goes down to around 0.1mm to 0.3 mm in later iterations. As seen from Figure 6, the predicted COG strain value is very sensitive to the changes in the PORON pad location, because any small change in the PORON pad location changes the COG strain value by a significant amount. The optimum value of the PORON pad location is found to be 0.162 percent and the corresponding COG strain value is 0.1645 percent. The model can now be updated with the value of optimal PORON pad location in HyperMesh, and the results can be verified with ABAQUS.Good Results in Less Time6DO NOT DISTRIBUTE ALTAIR INTERNAL ONLY CONTACT FATMA KOCER at fatma@ This study illustrates the use of HyperWorks and ABQ/Explicit to search for an optimal position of the PORON pad at flip-top housing, such that the strain of COG is minimized in a closed-front drop. Therein, HyperStudy automates the process and runs optimization with ABQ/Explicit as the FE solver. Though it is common to run a shape/size optimization with HyperStudy, this study shows that it is viable to run a position optimization by defining a position variable in HyperMesh using HyperMorph. This might be useful in views of the demand for such work. The optimization algorithm used in the HyperStudy is sequential-response surface method based on direct analysis runs instead of a DOE response surface, which is more accurate compared to the interpolation of results from a regression function. This approach decreases the user interaction by making use of the optimization algorithm to look for the optimal configuration once it has been properly setup in HyperStudy and HyperMesh. Though the position optimization is performed here, it is possible to have other shape, size and position variables to be defined and run at the same time. For example, the size of the pad, in addition to its location, could also be optimized in this study. Next, the post-processing results provide an overall view of optimization iterations conducted in terms of responses and design variables. By looking at the iteration history, it is possible to grasp how the response varies with respect to the change in design variable. The challenge in this study was the fact that HyperWorks and ABAQUS ran in different environments, as explicit drop-test simulations cannot be easily handled in Windows workstation. Three scripts were written to overcome this challenge and to provide efficient communication between SGI Altix and the workstation. Note that this study is performed to establish an optimal design process for cell phones, but was not meant to be an extensive study of this particular design. As such, further investigation is needed to identify the optimization techniques suitable for the various problems encountered for cellular phone design.7。

HyperStudy软件-结构优化

HyperStudy软件-结构优化
针对不同求解器输出结果所支持的文件类型
Solver
Result
File
Remarks
Nodel displacement (节点位移),
Velocity(速度), Acceleration(加速度)
.T01
Vector contains time history
RADIOSS (block format) element stress、strain
ASCII格式的结果文件,包含分析的注释
.out
二进制结果文件
.res 如果要得到向量中的具体元素的数值,需要使用 resvector() 函数
压缩的二进制结果文件,包含模型与结果信息 .h3d
如果要得到向量中的具体元素的数值,需要使 用 resvector() 函数
实用精品课件PPT
9
HyperStudy的输出文件
strain energy density (应变能密度)
Nodal displacement (节点位移), reaction force(反作用力), element stress,strain (单元应力、应变),
strain energy density (应变能密度)
File
Remarks
摄动面板下产生的结构的形状)
结构的灵敏度分析、优化 形状优化
实用精品课件PPT
3
设计变量的定义
二 用于制造工艺优化的设计变量
1)Hyperform可用的设计变量:
• Sheet thickness(钣金厚度) • Friction(摩擦系数) • Forces(载荷) • Shapes(as create by HyperMorph)(通过hypermorph定义的形状)

HyperStudy 优化案例

HyperStudy 优化案例

DO NOT DISTRIBUTE ALTAIR INTERNAL ONLY CONTACT FATMA KOCER at fatma@Studying Cell Phone Drop Using HyperWorksBuilding Durability into Products during the Design Process A drop test involves orienting an object with respect to an assumed gravitational field and allowing it to drop from some specified height under the influence of gravity onto a flat, rigid surface. It is significant in several industries, such as in the nuclear industry, where the integrity of containers carrying radioactive waste must be insured during accident scenarios. It is also important in the retail electronics industry, where manufacturers produce products such as cell phones that can be dropped while being used and continue to operate.Studying Drop-Test Behavior Conducting drop tests to investigate the impact behavior and identify failure mechanisms of a clam-shell cell phone is generally an expensive and timeconsuming process. Nevertheless, strict drop/impact performance criteria play a decisive role in their design, because they must withstand such unexpected shocks. As a result, in the development of a new cell phone, it is of great importance to asses the general mechanical properties in an early stage, using simulations to avoid timeconsuming design iterations. Drop-test simulations will help improve the components’ impact resistance and anticipate problem areas.X ft dropFigure 1. (Left) Closed-Front Drop Simulation (image is purposely made indistinct); (right) Clam-Shell Phone Cross-Section Showing the Stress Wave Path from Ground to LCD ModulePORON1DO NOT DISTRIBUTE ALTAIR INTERNAL ONLY CONTACT FATMA KOCER at fatma@Figure 2. (Left) PORON Pad Adhered at Flip Housing; (right) Maximum COG Logarithmic (LE) StrainIn cell phones, closed-front drop tests cause more cracks on the liquid crystal display (LCD) than other drop tests, because the stress wave propagates by way of the flip top to the LCD (Fig. 1). In this study, there is a PORON pad on the flip housing (Fig. 2) that serves to minimize the B2B connector disengagement during cell phone drops. PORON is a high-performance material that features a unique cell structure with high levels of density, minuteness and uniformity and is used for dampening vibration and preventing slip. The position of this PORON pad dictates the stress-wave path as stress waves propagate inwards during a closed-front drop test. As a result, its position has a significant influence on internal components, such as Chip-on-Glass (COG), a chip that mounts the LCD driver chip to the contact edge of the LCD glass. As such, during front-drop test simulations, the objective is to minimize the maximum strain on COG. In the earlier design development, analysts used conventional design processes to find the position of the PORON pad adhered to the flip-top housing that would minimize the COG strain. Drop test is a computationally demanding simulation, and, therefore, this work was performed by changing the pad position in 1 mm steps within the design space, and running a series of simulations. Experiencing the tremendous user interaction during this process and the fact that an optimal design is not guaranteed, it was decided to automate the process with HyperStudy in order to perform such work more quickly and efficiently.Finding the Optimum Location In discussing optimization of the location for a PORON pad at the flip housing in a clam shell phone, the position of the pad has significant effect on the stress-wave propagation in closed-front drops. As a result, optimization of its location is crucial to2DO NOT DISTRIBUTE ALTAIR INTERNAL ONLY CONTACT FATMA KOCER at fatma@ the reliability of the vulnerable internal components. The front drops are simulated using explicit analysis in ABAQUS. The finite-element (FE) models for such simulations are approximately 80 MBytes and simulations take approximately 12 hours using the SGI Altix. Typically, the optimum PORON pad position is searched by analysing the results from a previous simulation, creating a new design and running a simulation. Then, the loop is repeated until a satisfactory design is found. This design process not only requires tremendous user interaction, but it is errorprone and does not guarantee optimum design.In this study, PORON pad location is optimized using the HyperWorks suite of tools and ABAQUS. HyperMesh (the FE analysis and computational fluid dynamics preprocessor) is used to prepare the ABAQUS input deck and to create a shape variable for the PORON pad position. HyperStudy (the solver neutral design study, exploration and optimization tool) is used to automate the design process as well as find the optimum design. Both HyperMesh and HyperStudy are part of HyperWorks. As the ABAQUS simulation is a computationally demanding one on this project, it is run in SGI Altix System while HyperWorks is run in the Windows workstation. PBS Professional is used as the workload management system. The challenge in this study is to provide a robust and efficient communication between the two platforms as well as between HyperWorks and ABAQUS.The Study Process As mentioned earlier, the position of the pad adhered at the flip housing is crucial to vulnerable internal components because of its effect on the stress-wave propagation path in a closed-front drop. As a result the objective of this study is to develop a process to find the PORON pad location that minimizes the maximum strain on COG. The design space for the PORON pad can be seen in Figure 3.Design Space3DO NOT DISTRIBUTE ALTAIR INTERNAL ONLY CONTACT FATMA KOCER at fatma@ Figure 3. Design Space for the PORON Pad First, the required material, contact and step definitions of the drop model are entered in HyperMesh, including the already-defined node/element definition. Accordingly, the ABAQUS input file generated in HyperMesh runs in ABQ/Explicit, without any need for user interaction. HyperMesh is also used to create a shape variable for the pad position. HyperMesh includes HyperMorph, a tool for doing parametric mesh-based shape changes (morphing). In the morphing process, domains are created around the FE model. Handles are defined on certain nodes of these domains. By moving a handle, nodes in the associated domain will also move. Each such movement can then be saved as a shape variable (Figure 4). Mesh distortion is minimized by applying smoothing algorithms. Note that node and element numbering are not changed during morphingStart from base analysisParameterize model with HyperMorphDrag handles to generate shape variationsSave shapes as design variableOptimization to find best shapeFigure 4. Shape Optimization ProcessShape variables created in HyperMesh are then exported to HyperStudy. In HyperStudy, the study is set up by identifying how to modify the input deck corresponding to a change in the design (i.e. PORON pad location), how to extract the responses from the simulation output file (i.e. maximum COG strain) and the optimization method. As explicit drop-test simulation cannot easily be handled in the Windows workstation where HyperWorks is running, HyperStudy will be submitting the drop simulations to SGI Altix machine and retrieve the results. PBS Professional is used as the job management tool. Furthermore, three scripts are created to facilitate submitting and monitoring in PBS Professional in the SGI Altix system and result retrieval after each simulation. The submission script resides at the Windows4DO NOT DISTRIBUTE ALTAIR INTERNAL ONLY CONTACT FATMA KOCER at fatma@ workstation with the other two scripts at the SGI server. After defining the problem, a nominal run is manually executed within HyperStudy, using the customized execution script in which the script will transfer input, material file and python script into the SGI Altix compute server. The PBS Professional submission script will then be automatically activated to submit the job. Its progress is continuously checked by the monitoring script at the SGI server. When the job completes, the python script is executed, and the required results are extracted, before being automatically transferred back to the Windows workstation and analysed by HyperStudy. Upon the completion of the nominal run, the optimization will commence. Each run will be executed by way of the same process described earlier, until the convergence as stipulated in the HyperStudy is met. Figure 5 summarizes various steps involved in creating the optimization study in two environments (Windows, Altix) with two tools (HyperWorks and ABAQUS).Create Input FileHyperMesh Define Shape VariablesSet Up Study HyperStudy Submit Simulation SGI AltixRun Simulation Update Design Extract ResponsesNoConverged?YesPost-Process Results5DO NOT DISTRIBUTE ALTAIR INTERNAL ONLY CONTACT FATMA KOCER at fatma@ Figure 5. Optimization Process Steps In HyperStudy, the objective of the optimization study is to minimize the maximum logarithmic strain of COG elements. As this is a computationally demanding simulation and the main purpose here is to establish a design process rather than to perform extensive optimization studies, the number of iterations is limited to 20. In this study, Sequential Response Surface method is used for optimization. In this method, the system responses are approximated by a quadratic polynomial that is determined in each iteration step from the results of the current and earlier iterations. A least-square method is used to define the polynomialFigure 6. (Left) Design History of PORON Pad Location and (right) COG strainFigure 6 shows the iteration history for the design variable and response respectively available at the post-processing window of HyperStudy. In the first two iterations, the shape variable stays at 0.5mm to 0.6mm, but goes down to around 0.1mm to 0.3 mm in later iterations. As seen from Figure 6, the predicted COG strain value is very sensitive to the changes in the PORON pad location, because any small change in the PORON pad location changes the COG strain value by a significant amount. The optimum value of the PORON pad location is found to be 0.162 percent and the corresponding COG strain value is 0.1645 percent. The model can now be updated with the value of optimal PORON pad location in HyperMesh, and the results can be verified with ABAQUS.Good Results in Less Time6DO NOT DISTRIBUTE ALTAIR INTERNAL ONLY CONTACT FATMA KOCER at fatma@ This study illustrates the use of HyperWorks and ABQ/Explicit to search for an optimal position of the PORON pad at flip-top housing, such that the strain of COG is minimized in a closed-front drop. Therein, HyperStudy automates the process and runs optimization with ABQ/Explicit as the FE solver. Though it is common to run a shape/size optimization with HyperStudy, this study shows that it is viable to run a position optimization by defining a position variable in HyperMesh using HyperMorph. This might be useful in views of the demand for such work. The optimization algorithm used in the HyperStudy is sequential-response surface method based on direct analysis runs instead of a DOE response surface, which is more accurate compared to the interpolation of results from a regression function. This approach decreases the user interaction by making use of the optimization algorithm to look for the optimal configuration once it has been properly setup in HyperStudy and HyperMesh. Though the position optimization is performed here, it is possible to have other shape, size and position variables to be defined and run at the same time. For example, the size of the pad, in addition to its location, could also be optimized in this study. Next, the post-processing results provide an overall view of optimization iterations conducted in terms of responses and design variables. By looking at the iteration history, it is possible to grasp how the response varies with respect to the change in design variable. The challenge in this study was the fact that HyperWorks and ABAQUS ran in different environments, as explicit drop-test simulations cannot be easily handled in Windows workstation. Three scripts were written to overcome this challenge and to provide efficient communication between SGI Altix and the workstation. Note that this study is performed to establish an optimal design process for cell phones, but was not meant to be an extensive study of this particular design. As such, further investigation is needed to identify the optimization techniques suitable for the various problems encountered for cellular phone design.7。

HyperStudy优化(共37张)

HyperStudy优化(共37张)
5. 创建DOE分析时,Controlled factors中的DOE Class选择Run Matrix,并相应选择先前得到 的.txt文件。
第14页,共37页。
Size Optimization 尺寸优化
一 在excel表格基础上进行优化
B: 在excel表格中输入设计变量,同时(tóngshí)有响应的计算方法,以此作为优化的依据。
HyperStudy的输出文件
针对不同求解器输出结果所支持的文件类型
Solver
Result
File
Remarks
Model volume(模型体积), Mass(质量),
Frequency(模态频率(pínlǜ)),
Buckling factor(屈曲因子)
OptiStruct
Radioss
(Bulk format)
设计变量的定义
一 通过hypermesh可以定义为设计变量(biànliàng)的参数:
可为设计变量的参数名称
Shell thickness (壳单元料厚) Spring stiffness (弹簧刚度)
Concentrated mass (集中质量) Composite ply thickness (复合结构的组成结构板厚) Composite ply angle(复合结构中各组成结构间的角度)
Nodal position(节点位置) reaction force(反作用力)
Keyword file Vector contains x,y or z component of the node.
spcforc
SPC反作用力。该文件存放力、力矩。
第11页,共37页。
运行控制
Solver(求解器)

LS-DYNA和HyperStudy结合做优化

LS-DYNA和HyperStudy结合做优化

Figure 1 Definitions of regions on the golf club head. An equally important design criterion is the shape of the club head. The club head has to be pleasing in the eyes of the consumer as well as traditional and plain in shape in the eyes of the USGA. An additional constraint limiting the overall volume of the club head to 460 cm3 has been proposed and amended in 2001 and 2002, respectively, by the USGA. With all of the preceding in mind, the overall shape is important for the performance and aesthetics of club head design. A two-piece golf ball model was created in LS-INGRID with solid elements modeling both the cover and core. The rubber core was modeled using the *MAT_MOONEY_RIVLIN_RUBBER material property and the Surlyn®-like cover (that is, neither polyurethane or synthetic balata) was modeled using the *MAT_PLASTIC_KINEMATIC material property. Material properties for these models were determined experimentally. Consistent with the USGA’s test method, the club head (without grip or shaft) starts at rest in the analysis. The ball was given an initial velocity of 55.9 m/s (125 mph) and impacted into the unconstrained club head. Care was taken to properly align the club head so as to optimize the ball’s rebound velocity. The *DEFORMABLE_TO_RIGID_AUTOMATIC option in LSDYNA was utilized both before and after the contact between the ball and club head to reduce the runtime and facilitate the extraction of the output velocity of the ball using the rbdout file from LS-DYNA.

COMSOL Multiphysics 多物理场仿真优化分析

COMSOL Multiphysics 多物理场仿真优化分析

COMSOL Multiphysics 多物理场仿真优化分析中国大陆以及港澳地区领先的仿真分析软件和项目咨询解决方案供应商中仿科技与Altair公司联合发布了COMSOL Mul t iphysics结合HyperWorks的多物理场仿真分析优化案例。

这些案例为广大COMSOL 用户提供用于改进设计、进行“What if”研究、试验数据的相关性研究、优化复杂的多学科设计问题以及评价设计的可靠性和鲁棒性等优化功能。

经过大量的合作测试验证,双方共同认为COMSOL+HyperStudy的优化方案将为COMSOL 用户创造极大的价值,部分创新案例如下:案例1 偶极天线设计优化射频模块(RF Module)- 高频电磁天线阻抗是一个重要的参数,决定了传输电路的性能。

阻抗匹配和低电抗分量对于实际操作很重要,它们能通过合适的设计或匹配电路得到。

模型中通过COMSOL 结合HyperStudy,优化了偶极天线的长度和直径,使得输入阻抗和指定值相匹配。

模型数据库>RF Module>RF and MicrowaveEngineering>Shape optimize dipole antenna模型文件antenna.m原始设计情况:偶极天线尺寸参数l 和k 决定了天线的阻抗值,参数初始值l=0.5,k=0.01,阻抗值为94Ω,与设计要求值74Ω相差很远。

设计变量:偶极天线尺寸的长度参数l,直径参数k,其中参数变量取值范围0.4<l<0.6, 0.001<k<0.1设计约束:直径参数k<l/10优化目标:使得阻抗值尽可能接近设计要求值74Ω。

利用COMSOL Multiphysics与HyperStudy结合进行模型优化,目标阻抗值最终达到73.21Ω。

得到相应的天线尺寸长度和直径(l=0.4536539, k=0.0218773)。

下图为阻抗迭代收敛曲线。

案例2 齿轮优化基于COMSOL Multiphysics结构力学模块(Structural Mechanics Module)将齿轮固定在轴上的方法之一就是过盈配合。

基于UG模型的散热片CFD优化设计

基于UG模型的散热片CFD优化设计

14.7.10 实例:基于UG模型的散热片CFD优化设计初始的散热片如图Z14-39所示,设计文件为UG零件,基于SimLab进行CFD 的前处理,采用AcuSolve分析最高温度和风道压差,最后利用HyperStudy对模型进行优化设计。

图Z14-39 散热片模型UG文件中的可变参数有两个,散热片的翅片数和厚度。

利用SimLab驱动UG,发出指令让UG重新生成几何文件;然后在SimLab中完成自动网格划分和CFD工况的设置工作,并输出求解文件;接下来提交AcuSolve求解;最后使用后处理程序acuTrans提取散热片最高温度和风道压力损失。

HyperStudy优化的流程框图如图Z14-40所示。

图Z14-40 散热片优化流程框图从流程图可以看到,单个计算过程可以分成三步。

第一步:驱动几何更改并生成CFD计算文件输入文件:ht.prt和Macro.py文件。

ht.prt是UG几何文件,其中已经包含参数。

Macro.py文件是SimLab自动处理脚本,该脚本包含了以下几个步骤:几何导入、驱动UG进行几何参数更改以重新生成几何、自动网格划分、自动AcuSolve添加、导出inp计算文件。

●运行命令如下,其中,-auto表示要运行自动化脚本,-nographics表示运行时不启动SimLab图形界面。

<安装路径>/SimLab2019.3/bin/win64/SimLab.bat -auto Macro.py -nographics●输出文件:SIMLAB.DIR文件夹包含模型信息,fin.inp求解文件。

第二步:AcuSolve求解计算●输入文件:第一步生成的fin.inp和文件夹SIMLAB.DIR。

调用AcuSolve求解器对输入文件进行求解。

●运行命令如下,其中-pb fin表示求解项目名称fin,-np表示使用的CPU个数为4。

<安装路径>/acusolve/win64/bin/acuRun.bat -pb fin -np 4●输出文件:fin.1.log结果文件和ACUSIM.DIR文件夹。

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strain energy density (应变能密度)
File
Remarks
ASCII格式的结果文件,包含分析的注释
.out
二进制结果文件
.res 如果要得到向量中的具体元素的数值,需要使用 resvector() 函数
压缩的二进制结果文件,包含模型与结果信息 .h3d
如果要得到向量中的具体元素的数值,需要使 用 resvector() 函数
Exemple:HS-1070(The objective is to find the cross-sectional dimensions, width, and height of a beam that minimizes the beam volume while keeping the tip deflection below 0.35 mm. )如右图示
Nodal data(节点数据), element data(单元数据)
二进制文件,内容为模型信息与计算结果
.odb 如果要得到向量中的具体元素的数值,需要使用 resvector() 函数。
HyperStudy的输出文件
针对不同求解器输出结果所支持的文件类型
Solver
Result
Model volume(模型体积), Mass(质量), Frequency(模态频率), Buckling factor(屈曲因子)
5. 创建DOE分析时,Controlled factors中的DOE Class选择Run Matrix,并相应选择先前得到的.txt文件。
Size Optimization 尺寸优化
一 在excel表格基础上进行优化
B: 在excel表格中输入设计变量,同时有响应的计算方法,以此作为优化的依据。
HyperStudy的输出文件
针对不同求解器输出结果所支持的文件类型
Solver
Result
Nodel displacement (节点位移), Velocity(速度), Acceleration(加速度)
RADIOSS (block format) element stress、strain
(单元应力、应变)
Nodal data(节点数据), element data(单元数据)
Nastran
Model,mass(模型质量)
Nodel data(节点数据), Element data(单元数据) Frequency(模态频率)
File
Remarks
.T01
Vector contains time history
1. 创建HyperStudy可以评估的矩阵输入。 打开excel文件,选择tools菜单下的加载宏命令, 将宏命令hw_hst_genpdd.xla加载入,如果没有, 则在Altair的安装目录下\templates\hst\ 找到 hw_hst_genpdd.xla,并加载即可。
2. 创建Model时,选择spreadsheet作为创建的Model的 类型,并且前一步中加载入宏命令的excel表格作 为Model的输入。
HyperStudy 优化
HyperStudy分析时所支持的求解器:
• Abaqus • ANASYS • LS-DYNA • Nastran • OptiStruct • PAM-CRASH 2G • RADIOSS • HyperForm • MADYMO • ADAMS
设计变量的定义
一 通过hypermesh可以定义为设计变量的参数:
Input file (输入文件类型)
RADIOSS (Bulk Data Format)
.fem 文件
Optistruct Nastran Ls-DYNA
.fem 文件 .bdf 文件 /.dat 文件
.key 文件
Solver input arguments(运行参数)
$file -both
$file / $file –scr C:\temp $file
1. 打开excel表格,并将其另存为.txt格式的文本文件(制表符分隔)。
2. 创建model时,model type选择HyperStudy。
由于Excel中已经列出了设计变量与相应的设计结果,因此前 面建模时不需要进行初始计算,而仅在response中设置相应 的响应结果即可。
3. 创建response响应时,建立名称为index的响应用来表示设计的 次数,其Response experssion可表示为 “convert(getenv(“STUDY_RUN_NUMBER”))-1”
结构的灵敏度分析、优化 形状优化
设计变量的定义
二 用于制造工艺优化的设计变量
1)Hyperform可用的设计变量:
• Sheet thickness(钣金厚度) • Friction(摩擦系数) • Forces(载荷) • Shapes(as create by HyperMorph)(通过hypermorph定义的形状)
Nodal position(节点位置) reaction force(反作用力)
Keyword file Vector contains x,y or z component of the node.
spcforc
SPC反作用力。该文件存放力、力矩。
运行控制
Solver(求解器)
RADIOSS (Block Format)
d3hsp
Model energies(模型能量)
LS-DYNA
Nodal displacement (节点位移), Velocity(速度), Acceleration(加速度)
Element stress、strain (单元应力、应变)
Nodal data(节点数据), Element data(单元数据)
设计变量的定义
三 各求解器所支持的设计变量及对应的参数类型
HyperStudy的输入文件
HyperStudy 认可的入文件为:
• Study files (.xml) • Model files (.tpl, .hm, .hf,.mdl,.xls) • Preference files(preference.mvw)——求解器脚本文件
glstat nodout elout d3plot
ASCII文件,存放全局数据,模型大部分类型的能量 通过该文件输出。 该文件存放历史数据。 ASCII文件,存放节点数据。
文件存放历史数据。 ASCII文件,存放单元(梁、壳)数据。 文件存放历史数据。
如果要得到向量中的具体元素的数值,需要使用 resvector() 函数
3. 创建设计变量l时,通过Add Model Parameter命令, 在excel表格中选择设计变量(Design Variable)和响 应(Response)。
Shape Optimization 形状优化
形状优化的变量
形状优化的设计变量是结构的形状,因此在创建设计变量时需要先定义形状。通常使用HyperMorph定义用于形状 优化的设计变量——形状。
OptiStruct
Radioss (Bulk format)
Nodal displacement (节点位移), reaction force(反作用力), element stress,strain (单元应力、应变),
strain energy density (应变能密度)
Nodal displacement (节点位移), reaction force(反作用力), element stress,strain (单元应力、应变),

HyperStudy的输出文件
针对不同求解器输出结果所支持的文件类型
Solver
Abaqus
Result
File
Remarks
Model mass(质量),
center of gravity(重心)
moments of inertia(转动惯量) .dat Frequency(模态频率)
Nodal number(节点数),
4. 创建结果response响应时,响应矢量Vector的Vector resourece file选择reference file类型的文件,并且选择前面得到的.txt格 式的文本文件。Type和Request采用默认的Unknown和 Block1,Component则根据该矢量的作用选择表格中相应数据 表示的列(column x)
可为设计变量的参数名称 Shell thickness (壳单元料厚)
应用范围 结构的灵敏度分析、优化
Spring stiffness (弹簧刚度) Concentrated mass (集中质量)
简化车身模型中,接头对车身的灵敏度及优化 结构的灵敏度分析、优化
Composite ply thickness (复合结构的组成结构板厚)
2)HyperXtrude可用的设计变量 :
• Control points of the bearing profile curve(轴承轮廓曲线的控制点) • Shapes (as created by HyperMorph)(通过hypermorph定义的形状)
设计变量的定义
三 各求解器所支持的设计变量及对应的参数类型
尺寸优化的变量
尺寸优化时,和尺寸相关的属性都可以作为尺寸优化的变量。常用的尺寸优化设计变量有: 1)结构料厚thickness 2)集中质量mass
Size Optimization 尺寸优化
一 在excel表格基础上进行优化
A 设计变量与结果在excel表格中已经给出,以此作为优化的依据。
1. 目的是创建一个近似值,然后对这个近似值进行优化。 2. 该表格包含五列数据,如右图所示。第一列表示设计的次数,第二和第三列表示每个设计的两个 设计变量,第四和第五列表示先前DOE分析所得到的结果。
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