基于张量分解的减少顺序模型的构建及其应用于安全气囊部署模拟的应用
Takashi Sasagawa1, Masato Tanaka2
1Toyota Central R&D Laboratories, Inc., 41-1 Yokomichi, Nagakute, Aichi, 480-1192, Japan. sasagawa@mosk.tytlabs.co.jp.
本研究介绍了一种创建复杂模拟的减少顺序模型 (ROM) 的新方法. 该技术有效地模拟了接触和冲击的非线性问题,比传统方法提供了显著的速度改进.
科学领域:
- 计算力学 计算力学 计算力学
- 模型订单减少 模型订单减少
- 科学计算科学计算
背景情况:
- 传统的数值模拟在计算上是昂贵的,特别是对于非线性问题.
- 开发高效的减少顺序模型 (ROM) 对于加速复杂的工程分析至关重要.
- 现有的方法通常需要广泛的参数调整,并与接触/冲击现象作斗争.
研究的目的:
- 为ROM提供一种新的,无参数的构建方法.
- 为了能够有效地建模涉及接触和冲击的非线性问题.
- 为探索设计空间提供更快的替代方案,而不是完全的数值模拟.
主要方法:
- 使用张量分解 (塔克分解) 来对多维数据进行因数分解.
- 应用阿基马-spline插值来预测数据范围内的值.
- 从有限元分析 (FEA) 构建学习张量数据,使用代表性参数集.
主要成果:
- 通过使用有限的学习数据,成功构建了用于气囊撞击模拟的ROM.
- 实现了高的数据压缩比 (超过1000x).
- 证明了对新参数集的安全气囊部署行为的准确预测.
- 实现了响应面和帕雷托边界预测的显著加快 (比FEA快2000倍).
结论:
- 提出的方法有效地构建准确的ROM与接触和冲击的非线性问题.
- 在ROM框架内进行阿基马-spline插入,可以在没有参数调整的情况下进行准确的预测.
- 这种方法为传统的数值模拟提供了一种强大且计算效率高的替代方案.
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