基于差分进化算法的铝合金薄板Chaboche模型参数辨识

Q. Pham, D. Nguyen
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引用次数: 1

摘要

回弹预测是板料成形有限元分析中最具挑战性的问题之一。这一需求要求建立运动硬化模型并进行参数辨识。提出了一种基于微分进化优化方法的Chaboche运动硬化模型参数辨识的原理图策略。为此,对AA6022-T6和AA7075-T76两种铝合金板材进行了拉伸压缩(TC)试验,观察了包青格效应和运动硬化行为。开发了Python代码,将该方法应用于运动硬化模型参数的识别。校正后的材料模型在Abaqus软件中实现,对所研究材料进行v型弯曲和u型弯曲模拟试验。回弹量的预测结果与实验结果吻合较好,验证了所提识别策略的有效性。这是一篇在知识共享署名许可(http://creativecommons.org/licenses/by/4.0/)条款下发布的开放获取文章,该许可允许在任何媒介上不受限制地使用、分发和复制,只要原始作品被适当引用。
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Parameter Identification of Chaboche Model for Aluminum Alloy Sheets Based on Differential Evolution Algorithm
Springback prediction is one of the most challenging in finite element analysis for sheet metal forming processes. The demand requests the development of a kinematic hardening model and parameter identification. This study presents a schematic strategy to identify parameters of Chaboche’s kinematic hardening model based on a differential evolution optimization method. To this goal, several tension-compression (TC) tests were conducted to observe the Bauchinger’s effects and kinematic hardening behaviors of two aluminum alloy sheets: AA6022-T6 and AA7075-T76. A Python code is developed to apply the proposed method in identifying parameters of the kinematic hardening model. The calibrated material models were implemented in Abaqus software to simulate V-bending and U-bending tests for the investigated materials. The predictions for springback amount match well with the experimental measurements, which verifies the effectiveness of the presented identificationstrategy.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium provided the original work is properly cited.
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