Explicit Topology Optimization Based on the Joint-Driven Moving Morphable Components

IF 2.7 3区 工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY International Journal for Numerical Methods in Engineering Pub Date : 2025-01-07 DOI:10.1002/nme.7650
Jiaqi Xu, Chuhui He, Chang Liu, Xu Guo
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引用次数: 0

Abstract

The moving morphable component (MMC) topology optimization method has garnered increasing attention recently due to its ability to provide explicit geometric parameters of optimized structures and seamless integration with CAD systems. However, the classical MMC method may encounter instability during the iterative process due to the excessively free movement of components and geometric defects caused by the incomplete fusion of components. This article proposes a novel joint-driven MMC (JMMC) method to address these issues. The core idea involves introducing a set of joint components to control and constrain the movement and deformation of the ordinary components. These ordinary components are interconnected through the joint components, guiding their movement and deformation within the design domain to facilitate structural layout changes, and the sizes of both ordinary and joint components can also be simultaneously optimized to alter the structural topology. Compared to the classical MMC method, the JMMC method retains the advantages of fewer design variables, explicit geometric information of structural boundaries, and seamless CAD integration while effectively mitigating iterative instability and avoiding the “dirty geometry” issues caused by incomplete component fusion. Numerical examples demonstrate the effectiveness and robustness of the proposed method.

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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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