基于遗传算法的热管多目优化设计  

Optimal Design of Heat Pipe Based on the Multi-object Genetic Algorithm

作　　者：黄晓明[1] 施坤[1] 杨婧[1] 黄晓[2] 季辰吉[1] 

机构地区：[1]华中科技大学能源与动力工程学院,武汉430074 [2]加拿大卡尔顿大学机械与航空航天工程学院

出　　处：《制冷学报》2011年第2期14-18,共5页Journal of Refrigeration

基　　金：国家自然科学基金资助项目(50876035);中国博士后科学基金资助项目(20070420903)~~

摘　　要：热管作为一种高效热传输设备,被广泛应用于许多领域。对高效热管的优化设计,通常会涉及到多个目标参数,传统的设计方法往往无法同时有效地优化多个目标。首先通过对热管建立热网络分析模型和热传输极限模型,给出了热管多目标优化问题的数学描述。其次设计了基于遗传算法的多目标优化算法,并通过多个算例证实了该算法的有效性及优越性。由于数学问题的提出是基于热管的基本原理,因此该算法具有可推广性,可用于多种形式的热管设计。Heat pipes have been used widely in many engineering fields due to their higher rate of heat transfer.However,the design of heat pipes often involves selection of multiple parameters and the conventional design algorithms are not efficient in optimizing these parameters simultaneously.In this paper,the thermal network model and heat transfer limit model of a typical heat pipe were built.Based on them,the optimal problem of the heat pipe is defined mathematically.Then a multi-object optimization algorithm based on the genetic algorithm is introduced to solve this problem.The results of several case studies based on this algorithm are discussed.Its effectiveness and superiority are clearly demonstrated.Since the models are built on the basic heat pipe analysis theory,the algorithm can be easily extended to solve the optimal problem of many types of heat pipe.

关 键 词：热工学 热管 传热率 热阻 优化设计 多目标遗传算法 

分 类 号：TB657[一般工业技术—制冷工程] TK172.4[动力工程及工程热物理—热能工程]