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Safety part design optimisation based on the finite elements method and a genetic algorithm

机译:基于有限元和遗传算法的安全零件设计优化

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摘要

This paper deals with a numerical approach for improving the mechanical properties of a safety belt anchor by optimizing its shape and the manufacturing process by using a multi-objective genetic algorithm (NSGA-2). This kind of automotive component is typically manufactured in three stages: blanking, rounding of the edges by punching and finally bending (90°). This study focuses only on the rounding and bending processes. The numerical model is linked to the genetic algorithm (GA) in order to optimize the shape of the part and the process parameters. This is implemented by using ABAQUS© script files developed in the Python programming language and CATIA© script files in VBScript. The algorithm modifies the part’s design parameters in the CAD system, imports the model in STEP format into ABAQUS CAE and starts the Finite Elements Analysis (FEA) automatically. The material behaviour is modelled using a specific Lemaitre material damage formulation implemented in ABAQUS© via a FORTRAN user subroutine. The influence of two process parameters (the die radius and the rounding punch radius) and five shape parameters on the component behaviour is investigated. The search for the optimum component design depends on three objective functions which are (i) the material damage state at the end of the forming process, (ii) the von Mises stress field and (iii) the maximum von Mises stress in the folded zone. A global optimisation is finally performed in order to improve the ultimate unbending load and the volume of the safety part. This work has two major areas of innovation: (a) the improvement of the genetic algorithm NSGA-2; and (b) the development of an integrated numerical procedure including “Computer aided design” and “mechanical finite element simulation” controlled by the genetic algorithm.
机译:本文采用一种数值方法,通过使用多目标遗传算法(NSGA-2)优化安全带锚的形状和制造工艺来改善安全带锚的机械性能。这种汽车部件通常分三个阶段制造:落料,通过冲压使边缘变圆并最终弯曲(90°)。这项研究仅集中于倒圆和弯曲过程。数值模型链接到遗传算法(GA),以优化零件的形状和工艺参数。这是通过使用以Python编程语言开发的ABAQUS©脚本文件和VBScript中的CATIA©脚本文件来实现的。该算法在CAD系统中修改零件的设计参数,以STEP格式将模型导入ABAQUS CAE,并自动启动有限元分析(FEA)。材料行为是通过FORTRAN用户子例程使用ABAQUS©中实现的特定Lemaitre材料损坏公式来建模的。研究了两个工艺参数(模具半径和倒圆角半径)和五个形状参数对零件性能的影响。寻找最佳零件设计取决于三个目标函数:(i)成形过程结束时的材料损坏状态;(ii)von Mises应力场;(iii)折叠区的最大von Mises应力。最后进行全局优化,以改善极限弯曲负荷和安全部件的体积。这项工作有两个主要的创新领域:(a)遗传算法NSGA-2的改进; (b)开发一种综合数值程序,包括由遗传算法控制的“计算机辅助设计”和“机械有限元模拟”。

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