Topology optimization for metamaterials with negative thermal expansion coefficients using energy-based homogenization

IF 4 2区 工程技术 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Advances in Engineering Software Pub Date : 2024-10-15 DOI:10.1016/j.advengsoft.2024.103794
Yanding Guo , Huafeng Wang , Wei Wang , Chahua Chen , Yi Wang
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Abstract

Since the existing topology designs of negative thermal expansion metamaterials are primarily based on the asymptotic homogenization theory, this paper conducts a topology optimization method of negative thermal expansion metamaterials based on the computationally efficient energy-based homogenization for the first time. In this research, (1) a new effective thermal stress coefficient equation is pioneeringly proposed using energy-based homogenization frame, where its theoretical derivation process is presented as well as its effectiveness and computational efficiency are verified by comparative cases. Additionally, the matlab code is open-sourced for public learning. (2) A topology optimization design of both 2D and 3D metamaterials with negative thermal expansion properties is established innovatively with Discrete Material Optimization (DMO). Its advantages are illustrated compared with the convectional method and its results are validated by Finite Element Method simulations. The new methods have promising applications in the evaluation and optimization of thermal expansion properties of composites.
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利用基于能量的均质化对具有负热膨胀系数的超材料进行拓扑优化
由于现有的负热膨胀超材料拓扑设计主要基于渐近均质化理论,本文首次提出了一种基于计算高效的能量均质化的负热膨胀超材料拓扑优化方法。在这项研究中,(1) 利用基于能量的均质化框架,开创性地提出了一种新的有效热应力系数方程,并介绍了其理论推导过程,同时通过实例对比验证了其有效性和计算效率。此外,matlab 代码已开源,供公众学习。(2) 利用离散材料优化(DMO)创新性地建立了具有负热膨胀特性的二维和三维超材料的拓扑优化设计。与对流式方法相比,该方法的优势显而易见,其结果也得到了有限元法模拟的验证。新方法在评估和优化复合材料的热膨胀特性方面具有广阔的应用前景。
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来源期刊
Advances in Engineering Software
Advances in Engineering Software 工程技术-计算机:跨学科应用
CiteScore
7.70
自引率
4.20%
发文量
169
审稿时长
37 days
期刊介绍: The objective of this journal is to communicate recent and projected advances in computer-based engineering techniques. The fields covered include mechanical, aerospace, civil and environmental engineering, with an emphasis on research and development leading to practical problem-solving. The scope of the journal includes: • Innovative computational strategies and numerical algorithms for large-scale engineering problems • Analysis and simulation techniques and systems • Model and mesh generation • Control of the accuracy, stability and efficiency of computational process • Exploitation of new computing environments (eg distributed hetergeneous and collaborative computing) • Advanced visualization techniques, virtual environments and prototyping • Applications of AI, knowledge-based systems, computational intelligence, including fuzzy logic, neural networks and evolutionary computations • Application of object-oriented technology to engineering problems • Intelligent human computer interfaces • Design automation, multidisciplinary design and optimization • CAD, CAE and integrated process and product development systems • Quality and reliability.
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