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.

中文翻译：

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不可逆双循环的功率密度分析和多目标优化

考虑双循环中传热和工作过程引起的各种不可逆条件，应用有限时间热力学理论对功率密度性能进行优化，并利用NSGA-II进行多目标优化。分析了截止比、最大循环温度比、各种传热损失和工作过程对功率密度与压缩比、功率密度与热效率关系的影响。讨论了在最大功率输出和功率密度条件下获得的热效率和发动机尺寸。结果表明，对于双循环，热机在最大功率密度条件下体积更小，热效率更高。选取循环压缩比和截止比作为决策变量，选取无量纲功率输出、热效率、无量纲生态函数和无量纲功率密度作为目标函数。使用不同的目标组合执行多目标优化。讨论了LINMAP、TOPSIS和Shannon熵方法下的偏差指标，得到了遗传算法收敛时的代数。结果表明，遗传算法收敛于四目标优化的第341代，三目标优化的第488代和双目标优化的第399代。