翅片管式冷凝器性能分析及多目标优化

Performance analysis and multi-objective optimization of finned-tube condenser

针对翅片管式冷凝器构建稳态分布参数模型,利用试验数据验证模型,换热量误差在±3%以内。利用该模型对不同结构参数下的冷凝器性能进行仿真,分析管径、翅片间距、管间距等对管翅式冷凝器性能以及成本的影响。利用多目标遗传算法(MOGA)优化结构参数,其中综合性能优化的方案中换热量增加0.08%,成本降低0.43%,制冷剂侧压降降低3.71%,空气侧压降降低13.66%。

One steady-state distributed parameter mathematical model of the finned- tube condenser is developed, which is validated by the experimental data, and the differ-ence on the heat transfer capacity is within ± 3 The simulation on the performance of finned-tube condenser under various structural parameters is conducted using this model, and the influence of tube diameter, fin pitch and tube pitch on the performance and the cost is analyzed. The optimized structural parameters are obtained by multi-objective ge-netic algorithm （MOGA ）. The overall optimized plan can increase the heating capacity by 0.08M , and decrease the cost by 0.43% , as well as decrease the pressure drop on refriger-ant side and on air side by 3.71 K and 13.66% respectively.