肋片板式蒸发冷凝器传热性能及优化研究  

Optimization and research on the performance of heat transer and flow resistance in internal fin-plate evaporative condenser

作　　者：陆刘记 张胜利 侯俊峰 王正伟 杨光露 刘旭 韩勇 刘勇 吴学红 Lu Liuji;Zhang Shengli;Hou Junfeng;Wang Zhengwei;Yang Guanglu;Liu Xu;Han Yong;Liu Yong;Wu Xuehong(School of Energy and Power Engineering,Zhengzhou University of Light Industry,Zhengzhou 450002,China;Anyang Tobacco Factory,China Tobacco Henan Industrial Co.,Ltd.,AnYang 461001,China;Nanyang Tobacco Factory,China Tobacco Henan Industrial Co.,Ltd.,Nanyang 473007,China)

机构地区：[1]郑州轻工业大学能源与动力工程学院,郑州450002 [2]河南中烟工业有限责任公司许昌卷烟厂,许昌461001 [3]河南中烟工业有限责任公司南阳卷烟厂,南阳473007

出　　处：《低温与超导》2022年第1期27-32,75,共7页Cryogenics and Superconductivity

基　　金：国家自然科学基金(51476149);河南省科技攻关项目(202102210311,212102210231);河南中烟工业有限责任公司科技项目(AW202118,AW202119)资助。

摘　　要：提出一种肋片板式蒸发冷凝器,主要研究肋片间距和肋片高度对工质强化传热和阻力性能的影响。计算与优化结果表明:肋片高度从12 mm增大到20 mm时,出口温度降低8.98 K,压降却增大三倍;肋片间距从40 mm增大到7 mm,温度下降1 K左右,压降减小27 Pa。应用多目标遗传算法,将"出口温度低,压降小"作为优化目标函数,研究肋片板式蒸发冷凝器的结构优化,得到优化结果的Pareto front分布,同时得到肋片间距和肋片高度分别为69.275 mm和15.71 mm,为板式蒸发冷凝器的改进和发展提供一定的指导意义。A fin-plate evaporative condenser was presented and the influences of fin spacing P and fin height e on heat transfer enhancement and pressure drop performance of refrigerant were studied. The results show that When the height of the fin(e) increases from 12 mm to 20 mm, the outlet temperature decreases by 8.98 K, but the pressure drop increases by 3 times. When the fin spacing(P) increases from 40 mm to 70 mm, the pressure drop decreases by 27 Pa while the temperature decreases by about 1 K. The multi-objective genetic algorithm was applied to study the structure optimization of fin plate evaporative condenser with low outlet temperature and small pressure drop as the objective function. The distribution of Pareto front for the optimized results was obtained, and the optimal structures of fin spacing and fin height were obtained.It can provide certain valuable for the improvement and development of plate evaporative condenser.

关 键 词：蒸发式冷凝器 传热性能 阻力性能 遗传算法 PARETO优化 

分 类 号：TK124[动力工程及工程热物理—工程热物理]