基于混合法的碰撞仿真中母材参数的反求优化研究

Research on Reverse Optimization of Base Metal Parameters in Collision Simulation Based on Hybrid Method

  • 摘要: 以试验动态响应数据为基准,基于有限元方法和反求优化方法对碰撞仿真材料参数进行反求优化,是一种有效获取高精度母材材料参数的方法。然而传统基于仿真和优化算法的直接反求法存在效率低的问题。为了提高反求优化效率,本文提出了基于拉丁超立方设计、RBF近似模型以及NSGA-II算法相结合的混合法。以吸能盒的压缩试验数据为基准,对比了两种反求优化方法的精度和效率。研究结果表明,两种反求优化方法都满足工程应用精度。相比于直接法,混合法所需的仿真模型样本数量更少,效率更高。研究可为快速准确获取碰撞仿真的材料参数提供参考。

     

    Abstract: Based on experimental dynamic response data, reverse optimization of collision simulation material parameters using finite element method and reverse optimization method is an effective method for obtaining high-precision base material parameters. However, the traditional direct reverse method based on simulation and optimization algorithms has the problem of low efficiency. In order to improve the efficiency of reverse optimization, this paper proposes a hybrid method based on Latin hypercube design, RBF approximation model, and NSGA-II algorithm. Based on the compression test data of the energy absorbing box, the accuracy and efficiency of two reverse optimization methods were compared. The research results indicate that both reverse optimization methods meet the accuracy requirements for engineering applications. Compared to the direct method, the hybrid method requires fewer simulation model samples and is more efficient. The research can provide reference for quickly and accurately obtaining material parameters for collision simulation.

     

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