用于寻源导热反问题的自适应蚁群算法研究  

Study of Self-Adaptive Ant Colony Optimization for Heat Source Search in Inverse Heat Conduction Problems

作　　者：张涛[1] 卢玫[1] 李博汉[1] 陶亮[1] 

机构地区：[1]上海理工大学能源与动力工程学院,上海200093

出　　处：《应用数学和力学》2014年第7期823-830,共8页Applied Mathematics and Mechanics

基　　金：国家自然科学基金(51176126)~~

摘　　要：建立以蚁群算法(ant colony optimization,ACO)为基础的二维稳态导热反问题的求解模型.模型根据边界测点的测量信息与计算所得到的测点温度进行比较,将导热反问题转化为一个优化问题.对蚁群算法进行改进,利用不同路径构造方法的自适应蚁群算法对热源强度、热源位置进行反演,得到较为精确的反演结果.结果表明,所采用的蚁群算法和针对不同反演参数的路径构造方法具有较强的稳定性,能够较好反演热源强度及热源位置.A model based on ant colony optimization （ACO） was presented for the solution of two-dimensional stable inverse heat conduction problems （IHCP）. According to comparison be- tween the measured information at boundary points and the calculated temperature at those points, the IHCP was transformed to an optinu＇zation problem. By means of different path con- struction methods the ACO was improved as a serf-adaptive algorithm to inversely calculate the heat-source intensity and location with high precision. The results show that the present serf-a- daptive ACO with the path construction methods for different inversion parameters is robust and accurate for the search of location and intensity of the heat source.

关 键 词：热传导 反问题 寻源 蚁群算法 

分 类 号：TK124[动力工程及工程热物理—工程热物理] O369[动力工程及工程热物理—热能工程]