Multi-objective optimization and configurations comparison of closed-air Brayton cycle

Abstract

The microreactor power system is distinguished by its efficiency, compactness, and remarkable environmental adaptability. In this study, closed-air Brayton cycle (CABC) is proposed as the microreactor thermoelectric conversion system, and thermodynamic model of CABC with different configurations are established. The design of cycle parameters and component structures is accomplished through a combined system-component design approach. To obtained the optimal system design, the genetic algorithm and nondominated sorting genetic algorithm II are separately employed for single-objective and multi-objective optimization. In accordance with the results of multi-objective optimization, the intercooling reheat recuperative cycle attains the highest cycle efficiency at 35.4% and a power to mass ratio of 59.1 kW t−1. Conversely, the reheat recuperative cycle achieves the highest power density at 179.6 kW m−3 and its simpler structure renders it the optimal configuration for CABC. In comparison to single-objective optimization, the design results of multi-objective optimization exhibit a more balanced performance across three key indicators, signifying a superior overall performance of the optimized design scheme.