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Modeling and combined application of the modified NSGA-II and TOPSIS to optimize a refrigerant-to-air multi-pass louvered fin-and-flat tube condenser

机译:改进的NSGA-II和TOPSIS的建模和组合应用,以优化制冷剂-空气多通百叶窗式翅片和扁管冷凝器

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In the present work, the performance of a refrigerant-to-air multi-pass louvered fin-and-flat tube condenser is optimized without changing the condenser dimensions include length, width and depth. In order to achieve this aim, a one dimensional finite element model is developed to predict the condenser performance. The developed model is then used for optimization procedure after validating by the experimental data. The modified NSGA-II approach is applied to maximize heat transfer rate (Q) and minimize entropy generation number (N-s), refrigerant pressure drop (Delta P-ref and air pressure drop (Delta P-air) as the objective functions. The non-dominated optimum design points are then plotted and trade-off optimum points are obtained using the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and Nearest to the Ideal Point (NIP) method. Comparing the results of four-objective optimization with the results of separately run three and two-objective optimization problems reveals that Q and N-s can be used interchangeably. An independent two-objective optimization of Q and Delta P-ref results in heat transfer rate increase of about 4% and refrigerant pressure drop reduction of about 85%. In addition, the calculations show that in this case the effectiveness of the optimized condenser increases 3.3% in comparison with the base line condenser. Also, the results of sensitivity analysis of change in the optimum heat transfer rate and refrigerant pressure drop with change in the decision variables are reported. (C) 2016 Elsevier Ltd. All rights reserved.
机译:在当前工作中,在不改变冷凝器尺寸(包括长度,宽度和深度)的情况下,优化了制冷剂-空气多路百叶窗式翅片和扁管冷凝器的性能。为了达到这个目的,开发了一个一维有限元模型来预测冷凝器的性能。经过实验数据验证后,将开发的模型用于优化程序。修改后的NSGA-II方法用于最大化传热率(Q)和最小化熵产生数(Ns),制冷剂压降(Delta P-ref和空气压降(Delta P-air))作为目标函数。然后绘制以最优控制为主的最佳设计点,并使用“与理想解决方案相似的优先顺序”(TOPSIS)和“最接近理想点”(NIP)的方法获得折衷的最佳点。分别运行的三个和两个目标优化问题的结果表明,Q和Ns可以互换使用,一个独立的Q和Delta P-ref的两个目标优化导致传热率提高约4%,制冷剂压力下降降低了约85%。此外,计算结果表明,在这种情况下,与基准电容器相比,优化电容器的效率提高了3.3%。报告了最佳传热率和制冷剂压降随决策变量变化的变化分析。 (C)2016 Elsevier Ltd.保留所有权利。

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