Performance Optimal Design of Aircraft Engine Based on Multi-Objective Genetic Algorithms
Lijun Li, Yin Zeyong · Journal of Aerospace Power · 2006
Multi-objective optimization concepts,linked with a Pareto genetic algorithm-Non-dominated Sorting Genetic Algorithm(NSGA Ⅱ),are applied to the preliminary design phase to automate the conceptual design process.Engine cycle selected for study was a mixed-stream,low-bypass turbofan.The robust analysis codes for the thermodynamic engine cycle,flowpath and weight estimation analyses were integrated to find higher quality design.The results showed that NSGA Ⅱ has better robustness and convergence than general multi-objective optimization methods,and could generate uniformly a Pareto optimal set in the design space.From this set,decision maker can choose the best overall optimum aircraft engine preliminary design.