改进粒子群算法在管壳式换热器优化设计中的应用

Application of IPSO Algorithm to Optimal Design of Shell-and-Tube Heat Exchangers

以管壳式换热器每年的总费用作为目标函数,采用含随机扰动算子的改进粒子群算法(IPOS)对其进行了优化.在优化设计模型中,采用Bell-Delaware法描述壳侧流体,优化变量选择管程数、换热管内径和外径及间距、管布置方式、封头类型、流体分配方式、密封条数、壳程压降和管程压降.对采用IPOS算法得到的优化结果与相关文献的结果进行了比较.结果表明:IPOS算法具有全局收敛、计算精度高、稳定性好的特点,并能获得约束条件下管壳式换热器的最优设计方案.

Taking the total annual cost of shell-and-tube heat exchanger as a target function,the improved particle swarm optimization（IPSO） algorithm with stochastic perturbation operator was used to optimize the target function.In the optimized design model,Bell-Delaware method was applied for the description of the shell-side fluid,while major parameters selected for optimization,such as the number of tube-passes,inner and external tube diameters, tube pitch,tube layout,head type,fluid allocation,number of sealing strips as well as shell-side and tube-side pressure drops.Comparison was made between the optimized results obtained by IPSO algorithm and the results from relevant reference.Results show that the IPSO algorithm has features of global convergence,high accuracy and good stability,with which optimal design program can be obtained for shell-and-tube heat exchangers under bound conditions.