| description abstract | Optimal thermal and ecological performance tests of a solar-driven heat engine system were conducted in various optimization scenarios. For this, thermal and ecological models were developed for the solar-driven heat engine, and three objective functions (including thermal efficiency, output power, and ecological function) were obtained for the proposed system. In the present investigation, thermodynamic analysis and an evolutionary algorithm (EA) were employed to optimize the dimensionless ecological function, thermal efficiency, and dimensionless power of a solar-driven engine system. Four scenarios were conducted for optimization of the solar heat engine. In the first three, a traditional single-objective optimization was employed separately with each objective function, regardless of other objectives. In the fourth scenario, efficiency and power objectives were optimized simultaneously using a nondominated sorting genetic algorithm (GA) called the | |
