Power Density Analysis and Multi-Objective Optimization for an Irreversible Dual Cycle

Abstract

Considering the various irreversibility conditions caused by heat transfer and working processes in a dual cycle, the power density performance is optimized by applying finite-time thermodynamics theory, and multi-objective optimization is performed by using NSGA-II. The effects of cut-off ratio, maximum cycle temperature ratio, and various losses by heat transfer and working processes on the relationships between the power density and the compression ratio and between the power density and the thermal efficiency are analyzed. The thermal efficiency and engine size obtained under the conditions of maximum power output and power density are discussed. The results show that for a dual cycle, the heat engine has a smaller size and higher thermal efficiency under the condition of maximum power density. The cycle compression ratio and cut-off ratio are selected as decision variables, and the dimensionless power output, thermal efficiency, dimensionless ecological function, and dimensionless power density are selected as objective functions. Multi-objective optimization is performed with different objective combinations. The deviation indexes under the LINMAP, TOPSIS, and Shannon entropy approaches are discussed, and the number of generations when the genetic algorithm reaches convergence are obtained. The results show that the genetic algorithm converges at the 341st generation for the quadru-objective optimization, at the 488th generation for the tri-objective optimization, and at the 399th generation for the bi-objective optimization. When the bi-objective optimization is performed with dimensionless power output and dimensionless ecological function as the objective functions, the deviation index obtained based on the LINMAP approach is 0.1400, which is better than those obtained for other single- and multi-objective optimizations.

Four-Objective Optimization for an Irreversible Porous Medium Cycle with Linear Variation in Working Fluid’s Specific Heat

“…With the increase in OOs, there are contradictions among different OOs. To select the optimal result under the coexistence of multiple OOs, many scholars have carried out multi-objective optimization (MOO) [ 68 , 69 , 70 , 71 , 72 , 73 , 74 , 75 , 76 , 77 ] by NSGA-II [ 78 ]. Li et al [ 68 ] established a regenerative Brayton cycle model and carried out MOO on the , and dimensionless thermal economic performance.…”

“…Xie et al [ 73 ] performed MOO on the molar flow rate, reactor lengths and inlet temperatures of Braun-type exothermic reactor for ammonia synthesis. Shi et al [ 74 ] and Ge et al [ 75 ] used , , and as OOs and performed MOO for the diesel [ 74 ], dual [ 75 ] and MHD [ 76 ] cycles.…”

Four-Objective Optimizations of a Single Resonance Energy Selective Electron Refrigerator

“…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.…”

“…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.…”

Maximum Profit Output Configuration of Multi-Reservoir Resource Exchange Intermediary

“…Since the 1970s, Finite Time Thermodynamics (FTT) has made great progress in physics and engineering fields [ 1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 ]. Many scholars have researched the optimal performances of thermal and chemical processes and cycles [ 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 ]. A great deal of work has been performed for the optimal configurations of thermal and chemical processes and cycles [ 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 , 53 ], including heat transfer, mass transfer, heat and mass transfer, ...…”