Intelligent inverse design of phononic crystals based on machine learning coupled with localized collocation meshless method

IF 3.6 3区 材料科学 Q2 ENGINEERING, MECHANICAL
Wenhui Chu, Zhuojia Fu, S. S. Nanthakumar, Wenzhi Xu, Xiaoying Zhuang
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Abstract

The development of phononic crystals provides a possible solution for the precise control of acoustic/elastic waves. Designing phononic crystals with a target characteristic has become a research hotspot in recent years. Nevertheless, the precision with which the acoustic and mechanical waves can be altered remains a major challenge for existing inverse design methods. The rapidly growing machine learning methods revolutionize the design of these materials. As an important branch of machine learning, reinforcement learning is being attempted to solve mechanical problems more intelligently through the interaction of environment and agent. In this paper, we adopt machine learning to successfully design 2D phononic crystals with expected band structure. We firstly applied the meshless generalized finite difference method in solving the dispersion equation for a periodic structure. Then, in order to widen the first-order bandgap width over a desired frequency range, we employ the reinforcement learning algorithm modified by particle swarm optimization to effectively estimate the shape parameters. The parallel technology saves computational costs remains independent of the initial state and target, in addition to being effective and stable. This improved reinforcement learning based interaction design scheme can easily accommodate several other reverse engineering problems.

Abstract Image

基于机器学习与局部配置无网格法的声子晶体智能反设计
声子晶体的发展为声学/弹性波的精确控制提供了可能的解决方案。设计具有靶特性的声子晶体已成为近年来的研究热点。然而,改变声波和机械波的精度仍然是现有逆设计方法的主要挑战。快速发展的机器学习方法彻底改变了这些材料的设计。强化学习作为机器学习的一个重要分支,正试图通过环境和智能体的相互作用来更智能地解决机械问题。在本文中,我们采用机器学习成功地设计了具有预期带结构的二维声子晶体。首次将无网格广义有限差分法应用于求解周期结构的色散方程。然后,为了在期望的频率范围内扩大一阶带隙宽度,我们采用粒子群优化改进的强化学习算法来有效地估计形状参数。并行技术不仅节省了计算成本,而且不依赖于初始状态和目标,而且有效稳定。这种改进的基于强化学习的交互设计方案可以很容易地解决其他几个逆向工程问题。
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来源期刊
International Journal of Mechanics and Materials in Design
International Journal of Mechanics and Materials in Design ENGINEERING, MECHANICAL-MATERIALS SCIENCE, MULTIDISCIPLINARY
CiteScore
6.00
自引率
5.40%
发文量
41
审稿时长
>12 weeks
期刊介绍: It is the objective of this journal to provide an effective medium for the dissemination of recent advances and original works in mechanics and materials'' engineering and their impact on the design process in an integrated, highly focused and coherent format. The goal is to enable mechanical, aeronautical, civil, automotive, biomedical, chemical and nuclear engineers, researchers and scientists to keep abreast of recent developments and exchange ideas on a number of topics relating to the use of mechanics and materials in design. Analytical synopsis of contents: The following non-exhaustive list is considered to be within the scope of the International Journal of Mechanics and Materials in Design: Intelligent Design: Nano-engineering and Nano-science in Design; Smart Materials and Adaptive Structures in Design; Mechanism(s) Design; Design against Failure; Design for Manufacturing; Design of Ultralight Structures; Design for a Clean Environment; Impact and Crashworthiness; Microelectronic Packaging Systems. Advanced Materials in Design: Newly Engineered Materials; Smart Materials and Adaptive Structures; Micromechanical Modelling of Composites; Damage Characterisation of Advanced/Traditional Materials; Alternative Use of Traditional Materials in Design; Functionally Graded Materials; Failure Analysis: Fatigue and Fracture; Multiscale Modelling Concepts and Methodology; Interfaces, interfacial properties and characterisation. Design Analysis and Optimisation: Shape and Topology Optimisation; Structural Optimisation; Optimisation Algorithms in Design; Nonlinear Mechanics in Design; Novel Numerical Tools in Design; Geometric Modelling and CAD Tools in Design; FEM, BEM and Hybrid Methods; Integrated Computer Aided Design; Computational Failure Analysis; Coupled Thermo-Electro-Mechanical Designs.
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