TY  - JOUR
PY  - 2022//
TI  - Development of the robust design method for crash analysis - visualization of conditions for good quality by using pattern recognition and machine learning -
JO  - Transactions of Society of Automotive Engineers of Japan
A1  - Sugano, Chitoshi
A1  - Tamura, Yoichi
A1  - Komamura, Tatsuya
SP  - 258
EP  - 263
VL  - 53
IS  - 2
N2  - This paper describes a methodology for robust design in crash analysis. We organized a series of robust design processes for crash analysis and showed that it is possible to classify/predict deformation patterns, judge whether they are good or not, identify contributing parameters by applying statistical/machine learning methods in each process. By using a prediction model as a surrogate model, we achieved an extensive search in the design space in a short time.     ===    衝突解析における一連のロバスト設計プロセスを整理し，統計/機械学習を用いた変形パターンの分類/予測，良否判定，寄与因子の特定が可能であることを示した．<p />  <p>Language: ja</p>
LA  - ja
SN  - 0287-8321
UR  - http://dx.doi.org/10.11351/jsaeronbun.53.258
ID  - ref1
ER  -