An efficient and easy-to-extend Matlab code of the Moving Morphable Component (MMC) method for three-dimensional topology optimization

Du, Zongliang; Cui, Tianchen; Liu, Chang; Zhang, Weisheng; Guo, Yilin; Guo, Xu

doi:10.1007/s00158-022-03239-4

Cited by 41 publications

(10 citation statements)

References 30 publications

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“…Structural topology optimization has been successfully applied to inverse design various topological metamaterials 11,[38][39][40][41][42][43][44]56 . For designing the 3D elastic topological insulators, we adopt the Moving Morphable Component (MMC) method 40,42,52,53,56 , which has the advantages of the explicit geometry description and improved computational efficiency.…”

Section: Description Of the 3d Unit Cells Via The MMC Methodsmentioning

confidence: 99%

“…This is because the topological invariants are discrete variables, which cannot in general effectively handled by the gradient-based algorithms. The Moving Morphable Component (MMC) method could describe 3D unit cells using only a few explicit geometry parameters, and this makes it suitable to guarantee a computationally tractable solution process of the inverse design formulation 52,53 . In general, we summarize three characteristics of a desired optimization framework of the TMs as: (i) effective to identify the topological characters for arbitrary unit cells; (ii) suitable to topological materials in different classes and different physical systems; (iii) efficient to execute the solution procedure.…”

Section: Introductionmentioning

confidence: 99%

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Efficient Design of Helical Higher-Order Topological Insulators in 3d Elastic Medium

Luo

Chen

et al. 2023

Preprint

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Section: Description Of the 3d Unit Cells Via The MMC Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Efficient Design of Helical Higher-Order Topological Insulators in 3d Elastic Medium

Luo

Chen

et al. 2023

Preprint

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“…Afterward, Zhang et al [87,88] applied the MMC-based TO methods to solve multi-material and 3D TO problems. Recently, Du et al [89] provided a 256-line Matlab code (MMC3D256) for 3D problems and also proposed a 218-line Matlab code (MMC218) for 2D problems. They improved the accuracy of sensitive analysis and removed the DOFs that did not belong to the load transmission path.…”

Section: Mmc-based Tomentioning

confidence: 99%

Open-Source Codes of Topology Optimization: A Summary for Beginners to Start Their Research

Wang¹,

Li²,

Long³

et al. 2023

Computer Modeling in Engineering &Amp; Sciences

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Topology optimization (TO), a numerical technique to nd the optimal material layout with a given design domain, has attracted interest from researchers in the eld of structural optimization in recent years. For beginners, opensource codes are undoubtedly the best alternative to learning TO, which can elaborate the implementation of a method in detail and easily engage more people to employ and extend the method. In this paper, we present a summary of various open-source codes and related literature on TO methods, including solid isotropic material with penalization (SIMP), evolutionary method, level set method (LSM), moving morphable components/voids (MMC/MMV) methods, multiscale topology optimization method, etc. Simultaneously, we classify the codes into ve levels, from easy to di cult, depending on their di culty, so that beginners can get started and understand the form of code implementation more quickly.

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“…In the present work, the MMC method is used to describe the valley Hall insulators. In particular, moving morphable components determined by their geometric parameters are set as the basic building blocks to compose the optimal topological insulators (Guo et al, 2014;Zhang et al, 2017;Du et al, 2022). By optimizing those geometry parameters, the configurations of UCs are updated through the moving, morphing, or merging of MMCs.…”

Section: Valley Hall Insulators Described By Moving Morphable Compone...mentioning

confidence: 99%

Optimal design of topological waveguides by machine learning

Chen

Liu

et al. 2022

Front. Mater.

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Topological insulators supply robust edge states and can be used to compose novel waveguides to protect energy propagation against various defects. For practical applications, topological waveguides with a large working bandwidth and highly localized interface mode are desired. In the present work, mechanical valley Hall insulators are described by explicit geometry parameters using the moving morphable component method first. From the geometry parameters, artificial neural networks (ANN) are then well-trained to predict the topological property and the bounds of nontrivial bandgaps. Incorporating those ANN models, mathematical formulation for designing optimal mechanical topological waveguides can be solved efficiently, with an acceleration of more than 10,000 times than the traditional topology optimization approach.

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An efficient and easy-to-extend Matlab code of the Moving Morphable Component (MMC) method for three-dimensional topology optimization

Cited by 41 publications

References 30 publications

Efficient Design of Helical Higher-Order Topological Insulators in 3d Elastic Medium

Efficient Design of Helical Higher-Order Topological Insulators in 3d Elastic Medium

Open-Source Codes of Topology Optimization: A Summary for Beginners to Start Their Research

Optimal design of topological waveguides by machine learning

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