TY  - JOUR
PY  - 2016//
TI  - Crash performance prediction and knowledge discovery from crash simulation using data mining
JO  - Transactions of Society of Automotive Engineers of Japan
A1  - Ono, Masamoto
A1  - Kageyama, Yusuke
A1  - Iyama, Jun
A1  - Hara, Satoshi
A1  - Rudy, Raymond
A1  - Ide, Tsuyoshi
SP  - 913
EP  - 918
VL  - 47
IS  - 4
N2  - The extensive use of computer-aided design (CAE) is a standard approach in car crash simulation. As high-performance computation gets more available at a reasonable cost, it is becoming possible to produce huge amount of intermediate data such as the displacement of individual nodes. However, little is known about how to extract useful insights from the intermediate data. This paper proposes a data mining approach to CAE-based crash simulation. Using a dimensionality reduction technique, we demonstrate that the proposed method can automatically extract useful features from the data.<p /> <p>Language: ja</p>
LA  - ja
SN  - 0287-8321
UR  - http://dx.doi.org/10.11351/jsaeronbun.47.913
ID  - ref1
ER  -