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首页> 外文期刊>Applied thermal engineering: Design, processes, equipment, economics >A comprehensive thermo-economic analysis, optimization and ranking of different microturbine plate-fin recuperators designs employing similar and dissimilar fins on hot and cold sides with NSGA-II algorithm and DEA model
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A comprehensive thermo-economic analysis, optimization and ranking of different microturbine plate-fin recuperators designs employing similar and dissimilar fins on hot and cold sides with NSGA-II algorithm and DEA model

机译:具有NSGA-II算法和DEA模型的热和冷侧面采用类似和不同翅片的综合热经济分析,优化和排名。

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This study aims to perform a comprehensive thermo-economic analysis, optimization and ranking of cross and counter-flow plate-fin recuperators employing rectangular, triangular, offset strip and louver fins. The analysis is mainly conducted for two recuperator structures: (i) fins' configurations on both hot and cold sides are the same; (ii) fins on hot side and cold side are dissimilar in configuration. Considering effective practical optimization constraints and design parameters, Non-dominated Sorting Genetic Algorithm (NSGA-II) is used to maximize the recuperator effectiveness and minimize its total cost, simultaneously. Pareto-optimal fronts are presented to specify the desirable recuperator designs satisfying the constraints. Afterwards, in order to accurately and reliably rank the optimal designs based on significant factors including recuperator effectiveness, total cost, volume, mass and pressure drop, Data Envelopment Analysis (DEA) model is utilized. According to the ranking results achieved from the DEA model, the counter-flow recuperator employing louver fins on the cold side and rectangular fins on the hot side has the best performance among the investigated recuperator structures for which the values of effectiveness, cost, pressure drop, volume and mass are equal to 0.814359, 326688.3 $, 0.716857 kPa, 0.40834 m(3), 419.3277 kg, respectively. (C) 2017 Elsevier Ltd. All rights reserved.
机译:本研究旨在对采用矩形,三角形,偏移条和百叶窗翅片进行综合热经济分析,优化和排序,交叉和反流板翅片恢复器。分析主要用于两个恢复器结构:(i)散热侧的散热侧的配置是相同的; (ii)热侧和冷侧的翅片在配置中不相似。考虑有效的实际优化约束和设计参数,非主导的分类遗传算法(NSGA-II)用于最大化恢复器效率,并同时最小化其总成本。据提示帕累托 - 最佳前端以指定满足约束的理想恢复器设计。之后,为了基于包括恢复器有效性,总成本,体积,质量和压降,利用数据包络分析(DEA)模型,准确和可靠地对最佳设计进行排名。根据DEA模型实现的排名结果,在热侧的冷侧和矩形翅片上采用百叶窗翅片的反流式恢复器在调查的恢复器结构中具有最佳性能,其有效性,成本,压降值,体积和质量等于0.814359,326688.3 $,0.716857 KPA,0.40834 m(3),419.3277 kg。 (c)2017 Elsevier Ltd.保留所有权利。

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