合肥工业大学学报（自然科学版）
閤肥工業大學學報（自然科學版）
합비공업대학학보（자연과학판）
JOURNAL OF HEFEI UNIVERSITY OF TECHNOLOGY(NATURAL SCIENCE)
2014年
2期
145-149
,共5页
iSIGHT设计软件%薄壁直梁件%抗撞性%响应面模型%多目标优化%稳健性优化
iSIGHT設計軟件%薄壁直樑件%抗撞性%響應麵模型%多目標優化%穩健性優化
iSIGHT설계연건%박벽직량건%항당성%향응면모형%다목표우화%은건성우화
iSIGHT design software%thin-walled column%crashworthiness%response surface model (RSM )%multi-objective optimization%robust optimization
文章以iSIGHT设计软件为优化平台，集成Hypermesh和LS-DYNA ，构建并实现了薄壁直梁件抗撞性多目标优化设计流程，在此基础上，运用拉丁超立方试验设计方法生成样本数据，采用响应面方法构建近似模型且其精度满足耐撞性设计要求；以比吸能SEA最大及碰撞峰值力 Fmax最小为目标函数，采用多目标遗传算法NSGA-Ⅱ对响应面近似模型进行多目标优化设计，获取 Pareto最优化解集，选取6个Pareto解进行有限元仿真验证。结果表明：近似模型方法能很好地取代实际仿真过程进行优化，且计算效率较高，基于6σ的多目标稳健性优化方法与确定性优化方法相比，稳健性优化结果提高了设计变量的可靠性和多目标函数的综合稳健性。
文章以iSIGHT設計軟件為優化平檯，集成Hypermesh和LS-DYNA ，構建併實現瞭薄壁直樑件抗撞性多目標優化設計流程，在此基礎上，運用拉丁超立方試驗設計方法生成樣本數據，採用響應麵方法構建近似模型且其精度滿足耐撞性設計要求；以比吸能SEA最大及踫撞峰值力 Fmax最小為目標函數，採用多目標遺傳算法NSGA-Ⅱ對響應麵近似模型進行多目標優化設計，穫取 Pareto最優化解集，選取6箇Pareto解進行有限元倣真驗證。結果錶明：近似模型方法能很好地取代實際倣真過程進行優化，且計算效率較高，基于6σ的多目標穩健性優化方法與確定性優化方法相比，穩健性優化結果提高瞭設計變量的可靠性和多目標函數的綜閤穩健性。
문장이iSIGHT설계연건위우화평태，집성Hypermesh화LS-DYNA ，구건병실현료박벽직량건항당성다목표우화설계류정，재차기출상，운용랍정초립방시험설계방법생성양본수거，채용향응면방법구건근사모형차기정도만족내당성설계요구；이비흡능SEA최대급팽당봉치력 Fmax최소위목표함수，채용다목표유전산법NSGA-Ⅱ대향응면근사모형진행다목표우화설계，획취 Pareto최우화해집，선취6개Pareto해진행유한원방진험증。결과표명：근사모형방법능흔호지취대실제방진과정진행우화，차계산효솔교고，기우6σ적다목표은건성우화방법여학정성우화방법상비，은건성우화결과제고료설계변량적가고성화다목표함수적종합은건성。
Choosing iSIGHT as an optimization platform ,the Hypermesh and LS-DYNA were integrat-ed to construct the procedure of the multi-objective optimization for the crashworthiness of thin-walled column .On this basis ,Latin hypercube design method was used to generate sample data ,and the re-sponse surface model(RSM) was used to fit the sample data and create approximate model .The accu-racy of RSM met the requirements of the crashworthiness design .A multi-objective optimization de-sign on RSM was implemented by multi-objective genetic algorithm NSGA-Ⅱ ,and the objectives were to maximize the SEA and to minimize the collision peak force Fmax .The Pareto optimal solution set was obtained ,and six Pareto solutions were selected and verified by finite element simulation .The re-sults showed that the approximate model could well replace the real process of simulation in optimiza-tion and could greatly improve the efficiency of optimization .Finally ,a multi-objective robust optimi-zation method based on 6σwas proposed .The robust optimal results improved the reliability of the de-sign variables and the comprehensive robustness of the multi-objective functions comparing to the cer-tain optimal results .
