Large‐scale elasto‐plastic topology optimization

IF 2.7 3区 工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY International Journal for Numerical Methods in Engineering Pub Date : 2024-08-04 DOI:10.1002/nme.7583
Gunnar Granlund, Mathias Wallin
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Abstract

This work presents large‐scale elasto‐plastic topology optimization for design of structures with maximized energy absorption and tailored mechanical response. The implementation uses parallel computations to address multi million element three‐dimensional problems. Design updates are generated using the gradient‐based method of moving asymptotes and the material is modeled using small strain, nonlinear isotropic hardening wherein the coaxiality between the plastic strain rate and stress is exploited. This formulation renders an efficient state solve and we demonstrate that the adjoint sensitivity scheme resembles that of the state update. Furthermore, the KKT condition is enforced directly into the path dependent adjoint sensitivity analysis which eliminates the need of monitoring the elasto‐plastic switches when calculating the gradients and provides a straight forward framework for elasto‐plastic topology optimization. Numerical examples show that structures discretized using several millions degrees of freedom and loaded in multiple load steps can be designed within a reasonable time frame.
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大规模弹塑性拓扑优化
这项研究提出了大规模弹塑性拓扑优化技术,用于设计具有最大能量吸收和定制机械响应的结构。实施过程使用并行计算来解决数百万个元素的三维问题。设计更新采用基于梯度的移动渐近线方法生成,材料采用小应变、非线性各向同性硬化建模,其中利用了塑性应变率和应力之间的同轴性。这种计算方法可以高效地进行状态求解,我们还证明了邻接灵敏度方案与状态更新方案的相似性。此外,KKT 条件是直接在路径相关的辅助灵敏度分析中强制执行的,这就消除了在计算梯度时监测弹塑性开关的需要,并为弹塑性拓扑优化提供了一个直接向前的框架。数值示例表明,使用数百万自由度离散和多负载步骤加载的结构可以在合理的时间内完成设计。
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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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