Automatic identification of macroscopic constitutive parameters for polycrystalline materials based on computational homogenisation

IF 1.5 4区 工程技术 Q3 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Guilherme Fonseca Gonçalves, Rui Pedro Cardoso Coelho, Igor André Rodrigues Lopes
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引用次数: 0

Abstract

Purpose

The purpose of this research is to establish a robust numerical framework for the calibration of macroscopic constitutive parameters, based on the analysis of polycrystalline RVEs with computational homogenisation.

Design/methodology/approach

This framework is composed of four building-blocks: (1) the multi-scale model, consisting of polycrystalline RVEs, where the grains are modelled with anisotropic crystal plasticity, and computational homogenisation to link the scales, (2) a set of loading cases to generate the reference responses, (3) the von Mises elasto-plastic model to be calibrated, and (4) the optimisation algorithms to solve the inverse identification problem. Several optimisation algorithms are assessed through a reference identification problem. Thereafter, different calibration strategies are tested. The accuracy of the calibrated models is evaluated by comparing their results against an FE2 model and experimental data.

Findings

In the initial tests, the LIPO optimiser performs the best. Good results accuracy is obtained with the calibrated constitutive models. The computing time needed by the FE2 simulations is 5 orders of magnitude larger, compared to the standard macroscopic simulations, demonstrating how this framework is suitable to obtain efficient micro-mechanics-informed constitutive models.

Originality/value

This contribution proposes a numerical framework, based on FE2 and macro-scale single element simulations, where the calibration of constitutive laws is informed by multi-scale analysis. The most efficient combination of optimisation algorithm and definition of the objective function is studied, and the robustness of the proposed approach is demonstrated by validation with both numerical and experimental data.

基于计算均质化自动识别多晶材料的宏观构成参数
研究目的本研究的目的是在利用计算均质化分析多晶 RVE 的基础上,为校准宏观构成参数建立一个稳健的数值框架。设计/方法/途径该框架由四个构件组成:(1) 多尺度模型,由多晶 RVE 组成,其中晶粒采用各向异性晶体塑性建模,计算均质化将各尺度连接起来;(2) 一组加载案例,用于生成参考响应;(3) 冯-米塞斯弹塑性模型,用于校准;(4) 优化算法,用于解决逆识别问题。通过参考识别问题对几种优化算法进行了评估。之后,对不同的校准策略进行了测试。在最初的测试中,LIPO 优化器表现最佳。校准后的结构模型获得了良好的结果精度。与标准宏观模拟相比,FE2 模拟所需的计算时间增加了 5 个数量级,这表明该框架适合于获得高效的微观力学信息构成模型。研究了优化算法和目标函数定义的最有效组合,并通过数值和实验数据的验证证明了所提方法的稳健性。
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来源期刊
Engineering Computations
Engineering Computations 工程技术-工程:综合
CiteScore
3.40
自引率
6.20%
发文量
61
审稿时长
5 months
期刊介绍: The journal presents its readers with broad coverage across all branches of engineering and science of the latest development and application of new solution algorithms, innovative numerical methods and/or solution techniques directed at the utilization of computational methods in engineering analysis, engineering design and practice. For more information visit: http://www.emeraldgrouppublishing.com/ec.htm
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