Guo Fei, Zhao Xiaoyu, Tu Wenqiong, Liu Cheng, Li Beibei, Ye Jinrui
School of Mechanical and Automotive Engineering, Shanghai University of Engineering Science, Shanghai 201620, China.
School of Automotive and Traffic Engineering, Jiangsu University, Zhenjiang 212013, China.
Materials (Basel). 2023 Feb 27;16(5):1953. doi: 10.3390/ma16051953.
Designing thermal conductivity efficiently is one of the most important study fields for taking the advantages of woven composites. This paper presents an inverse method for the thermal conductivity design of woven composite materials. Based on the multi-scale structure characteristics of woven composites, a multi-scale model of inversing heat conduction coefficient of fibers is established, including a macroscale composite model, mesoscale fiber yarn model, microscale fiber and matrix model. In order to improve computational efficiency, the particle swarm optimization (PSO) algorithm and locally exact homogenization theory (LEHT) are utilized. LEHT is an efficient analytical method for heat conduction analysis. It does not require meshing and preprocessing but obtains analytical expressions of internal temperature and heat flow of materials by solving heat differential equations and combined with Fourier's formula, relevant thermal conductivity parameters can be obtained. The proposed method is based on the idea of optimum design ideology of material parameters from top to bottom. The optimized parameters of components need to be designed hierarchically, including: (1) combing theoretical model with the particle swarm optimization algorithm at the macroscale to inverse parameters of yarn; (2) combining LEHT with the particle swarm optimization algorithm at the mesoscale to inverse original fiber parameters. To identify the validation of the proposed method, the present results are compared with given definite value, which can be seen that they have a good agreement with errors less than 1%. The proposed optimization method could effectively design thermal conductivity parameters and volume fraction for all components of woven composites.
高效设计热导率是发挥编织复合材料优势的最重要研究领域之一。本文提出了一种用于编织复合材料热导率设计的逆方法。基于编织复合材料的多尺度结构特征，建立了一种纤维导热系数反演的多尺度模型，包括宏观复合材料模型、细观纤维纱线模型、微观纤维和基体模型。为了提高计算效率，采用了粒子群优化（PSO）算法和局部精确均匀化理论（LEHT）。LEHT是一种用于热传导分析的高效解析方法。它不需要网格划分和预处理，而是通过求解热微分方程并结合傅里叶公式获得材料内部温度和热流的解析表达式，从而得到相关的热导率参数。所提出的方法基于从顶部到底部对材料参数进行优化设计的思想。组件的优化参数需要分层设计，包括：（1）在宏观尺度上，将理论模型与粒子群优化算法相结合来反演纱线参数；（2）在细观尺度上，将LEHT与粒子群优化算法相结合来反演原始纤维参数。为了验证所提出方法的有效性，将当前结果与给定的确定值进行比较，可以看出它们具有良好的一致性，误差小于1%。所提出的优化方法能够有效地为编织复合材料的所有组件设计热导率参数和体积分数。
