2022
DOI: 10.3390/e24081074
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Four-Objective Optimization for an Irreversible Porous Medium Cycle with Linear Variation in Working Fluid’s Specific Heat

Abstract: Considering that the specific heat of the working fluid varies linearly with its temperature, this paper applies finite time thermodynamic theory and NSGA-II to conduct thermodynamic analysis and multi-objective optimization for irreversible porous medium cycle. The effects of working fluid’s variable-specific heat characteristics, heat transfer, friction and internal irreversibility losses on cycle power density and ecological function characteristics are analyzed. The relationship between power density and e… Show more

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Cited by 12 publications
(8 citation statements)
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“…Xu et al [ 88 ] used NSGA-II to conduct MOO on four objectives for the Stirling heat engine considering various losses. Zang et al [ 89 ] used the FTT to conduct thermodynamic analysis of the irreversible porous media cycle and utilized NSGA-II to conduct MOO of four objectives: dimensionless ( ), , dimensionless ( ), and dimensionless ( ).…”
Section: Introductionmentioning
confidence: 99%
“…Xu et al [ 88 ] used NSGA-II to conduct MOO on four objectives for the Stirling heat engine considering various losses. Zang et al [ 89 ] used the FTT to conduct thermodynamic analysis of the irreversible porous media cycle and utilized NSGA-II to conduct MOO of four objectives: dimensionless ( ), , dimensionless ( ), and dimensionless ( ).…”
Section: Introductionmentioning
confidence: 99%
“…In order to take different performance indicators into account and obtain the optimal design scheme, Deb et al [ 90 ] proposed the non-dominated sorting genetic algorithm II (NSGA-II), which overcame the three shortcomings of NSGA, including the high computational complexity of non-dominated sorting, the lack of elite strategies, and the need to specify shared parameters. NSGA-II was widely used for the multi-objective optimization (MOO) of various thermodynamic cycles [ 91 , 92 , 93 , 94 , 95 , 96 , 97 , 98 , 99 ]. The Brayton cycle [ 91 ] and Stirling-Otto combined cycle [ 92 ] were optimized by MOO, and the utilized optimization objectives were power output and thermal efficiency; the optimization results were obtained and compared by applying different decision-making approaches.…”
Section: Introductionmentioning
confidence: 99%
“…The Brayton cycle [ 91 ] and Stirling-Otto combined cycle [ 92 ] were optimized by MOO, and the utilized optimization objectives were power output and thermal efficiency; the optimization results were obtained and compared by applying different decision-making approaches. The porous-medium cycle [ 93 ] and Dual cycle [ 94 ] were optimized by MOO and the utilized optimization objectives were power density, power output, ecological function, and thermal efficiency; in addition, the effects of the compression ratio on four optimization objectives were analyzed. The Organic Rankine cycle [ 95 ] was optimized by applying MOO and its performances of pure and mixture working fluids were compared and studied.…”
Section: Introductionmentioning
confidence: 99%
“…With the increase in OOs, there may be conflicts among different OOs. In order to coordinate the conflicts among OOs, some scholars used NSGA-II [ 58 , 59 , 60 , 61 , 62 , 63 , 64 , 65 , 66 , 67 , 68 ] to perform multi-objective optimization (MOO) for various HEG cycles. Ahmadi et al [ 58 ] studied the applicability of the Stirling-Otto combined cycle and performed MOO on and for combined cycle with six decision variables.…”
Section: Introductionmentioning
confidence: 99%