基于粒子群优化算法的燃气轮机间冷器结构优化  

Structure Optimization of Gas Turbine Intercooler based on Particle Swarm Optimization Algorithm

作　　者：李明[1] 赵宁波[1] 王强[1] 李淑英[1] 费景洲[1] 

机构地区：[1]哈尔滨工程大学动力与能源工程学院,哈尔滨150001

出　　处：《燃气轮机技术》2016年第1期41-47,共7页Gas Turbine Technology

基　　金：国家自然科学基金项目(批准号:51475100);中央高校基本科研基金项目(批准号:HEUCF140306)

摘　　要：针对间冷循环燃气轮机间冷器结构的高效紧凑性要求,本文提出了一种基于粒子群优化算法的燃气轮机间冷器结构优化方法。以间冷器质量最小为优化目标,选择间冷器换热效率与气侧压力降损失率为约束条件,对间冷器气侧通道板间距、液侧通道板间距、气侧翅片间距、气侧翅片厚度、间冷器长度、间冷器宽度以及气侧通道层数7个参数进行优化。以某型间冷器为例验证该方法的有效性,并与传统的遗传算法优化结果进行对比分析。研究结果表明,在相同的间冷器设计参数和相同的优化变量搜索范围条件下,采用粒子群优化算法得到的间冷器结构更加紧凑,间冷器综合性能更优。In order to meet the need of the heat efficiency and compact structure for gas turbine intercooler,this study discusses the use of particle swarm optimization（ PSO） algorithm for structure optimization of a gas turbine intercooler. The intercooler total weight is considered as the optimization objective function. The heat transfer efficiency required for the heat duty and the pressure drop loss rate of air side are considered as the restrictive conditions. The plate pitch of air and liquid sides,fin pitch,fin thickness,intercooler length,intercooler width and fin layer numbers of air side are taken as the optimization variables. To demonstrate the effectiveness of PSO algorithm,an example is also presented and the results are contrasted with those obtained by genetic algorithm（ GA）. The results show that the structure and performance of intercooler obtained by using PSO algorithm is superior to those obtained by using GA algorithm and preliminary design when the other condition remains the same.

关 键 词：燃气轮机 间冷器 结构优化 粒子群优化算法 遗传算法 

分 类 号：TK472[动力工程及工程热物理—动力机械及工程]