翅片管式冷凝器性能分析及多目标优化
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  • 英文篇名:Performance analysis and multi-objective optimization of finned-tube condenser
  • 作者:郭梦茹 ; 蔡姗姗 ; 陈焕新 ; 应必业 ; 唐小波 ; 白韦 ; 古汤汤
  • 英文作者:Guo Mengru;Cai Shanshan;Chen Huanxin;Ying Biye;Tang Xiaobo;Bai Wei;Gu Tangtang;Huazhong University of Science and Technology;Ningbo AUX Air Conditioner Co.,Ltd.;
  • 关键词:冷凝器 ; 性能 ; 多目标遗传算法
  • 英文关键词:condenser;;performance;;multi-objective genetic algorithm(MOGA)
  • 中文刊名:ZLDT
  • 英文刊名:Refrigeration and Air-Conditioning
  • 机构:华中科技大学;宁波奥克斯空调有限公司;
  • 出版日期:2018-04-28
  • 出版单位:制冷与空调
  • 年:2018
  • 期:v.18
  • 基金:国家自然科学基金(51076048)
  • 语种:中文;
  • 页:ZLDT201804020
  • 页数:6
  • CN:04
  • ISSN:11-4519/TB
  • 分类号:101-106
摘要
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 difference 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 genetic algorithm( MOGA). The overall optimized plan can increase the heating capacity by 0. 08%,and decrease the cost by 0. 43%,as well as decrease the pressure drop on refrigerant side and on air side by 3. 71% and 13. 66% respectively.
引文
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