基于遗传算法的三叶孔板换热器优化设计  

Optimal Design of Trefoil-baffle Support Heat Exchanger Based on Genetic Algorithm

作　　者：古新[1] 潘国华[1] 刘敏珊[1] 王永庆[1] 

机构地区：[1]郑州大学热能工程研究中心,河南郑州450002

出　　处：《压力容器》2013年第7期12-17,共6页Pressure Vessel Technology

基　　金：国家自然科学基金(51006092)

摘　　要：通过Matlab软件,用遗传算法对三叶孔板换热器进行了传热性能优化设计研究。基于单目标和多目标遗传算法,选取火积耗散数和总成本作为目标函数,然后编程运算。结果表明:通过优化设计,三叶孔板换热器的有效度增加,泵功减小,热容流量比减小;在相同有效度情况下,多目标函数优化后的泵功比单目标函数减小了近13.7%,说明多目标函数优化比单目标优化的结果更有优越性;多目标函数优化更具有灵活性,其得到的Pareto解可供多角度选择。The heat transfer performance optimization of trefoil - baffle support heat exchanger was carried out,by using genetic algorithm which possess a strong global optimization ability. Based on the single ob- jective and multi -objective genetic algorithm ,the five variables and the constraint conditions were deter- mined to compute the results of the objective functions, entransy dissipation number and total costs, by writing programs. The results show that the effective degree of heat exchanger was increased, the pump power and the rate of heat capacity flow were reduced by optimization design. Pump power of multi - ob- jective optimization was reduced about 13.7% than that of single objective optimization. So multi - objec- tive function optimization has more advantages. Moreover, the Pareto solution has more flexibility than sin- gle objective function optimization,it can be chosen by designer.

关 键 词：三叶孔板换热器 遗传算法 多目标优化 火积耗散数 总成本 

分 类 号：TH122[机械工程—机械设计及理论] TE965[石油与天然气工程—石油机械设备]