一类新的双层纺织材料厚度设计反问题

Abstract

本文基于低温环境下平行圆柱孔结构的纺织材料热湿传递稳态模型，研究了一类双层纺织材料厚度设计反问题。首先给出了一个双层纺织材料热湿传递稳态模型，并采用有限差分方法求解该问题。然后，根据服装热湿舒适性指标，将纺织材料内层厚度看成一个未知量，提出了一类双层纺织材料厚度设计反问题，将该反问题归结为一个最大概率最小模问题，采用罚函数法将该约束优化问题转换为无约束的优化问题，并采用粒子群算法求解。数值结果说明了双层纺织材料厚度设计反问题提法的合理性，以及粒子群算法的有效性和鲁棒性。 This paper studies a new inverse problem of estimating bi-layer textile fabrics thickness based on a steady-state heat and moisture transfer model. We first present a heat and moisture transfer model for bi-layer textile materials with boundary conditions and solve them by finite difference method. According to the requirement of clothing’s thermal and moisture comfort, we formulate the inverse heat and moisture transfer problem that estimate the thickness of inner fabric as a minimum norm problem with a maximum probability constraint model. We use a static penalty method to convert the constrained problem into an equivalent unconstrained minimization problem and obtain the solution for the optimization problem by a stochastic search method, known as particle swarm optimization algorithm. Numerical experiments show that our new model is quiet acceptable, and the proposed numerical method’s validity and robustness.