基于快速傅立叶变换的微极弹性塑性解算器

IF 2.9 3区 工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY International Journal for Numerical Methods in Engineering Pub Date : 2025-01-03 DOI:10.1002/nme.7651
Noah M. Francis, Ricardo A. Lebensohn, Fatemeh Pourahmadian, Rémi Dingreville
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引用次数: 0

摘要

本文提出了一种微力学谱公式,用于获得弹塑性微极复合材料的全场均质响应。利用基于热力学的微极弹塑性本构方程推导出封闭形式的径向-返回映射,以确定将广义应力状态返回屈服面所需的塑性应变增量,并用数值解的方法验证了算法的实现。然后,尺寸相关的材料响应和微塑性被显示为可以在这个微极弹塑性框架中有效模拟的特征。该公式的计算效率可以在合理的计算时间内生成大型数据集。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Micropolar Elastoplasticity Using a Fast Fourier Transform-Based Solver

This work presents a micromechanical spectral formulation for obtaining the full-field and homogenized response of elastoplastic micropolar composites. A closed-form radial-return mapping is derived from thermodynamics-based micropolar elastoplastic constitutive equations to determine the increment of plastic strain necessary to return the generalized stress state to the yield surface, and the algorithm implementation is verified using the method of numerically manufactured solutions. Then, size-dependent material response and micro-plasticity are shown as features that may be efficiently simulated in this micropolar elastoplastic framework. The computational efficiency of the formulation enables the generation of large datasets in reasonable computing times.

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来源期刊
CiteScore
5.70
自引率
6.90%
发文量
276
审稿时长
5.3 months
期刊介绍: The International Journal for Numerical Methods in Engineering publishes original papers describing significant, novel developments in numerical methods that are applicable to engineering problems. The Journal is known for welcoming contributions in a wide range of areas in computational engineering, including computational issues in model reduction, uncertainty quantification, verification and validation, inverse analysis and stochastic methods, optimisation, element technology, solution techniques and parallel computing, damage and fracture, mechanics at micro and nano-scales, low-speed fluid dynamics, fluid-structure interaction, electromagnetics, coupled diffusion phenomena, and error estimation and mesh generation. It is emphasized that this is by no means an exhaustive list, and particularly papers on multi-scale, multi-physics or multi-disciplinary problems, and on new, emerging topics are welcome.
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