| Citation: | MA Yue, GUO Mingming, SUN Bolun, et al. High-dimensional multi-objective optimization of aero-engine based on POD-PCE-Kriging model[J]. Journal of Aerospace Power, 2023, 38（7）：1604-1614 doi: 10.13224/j.cnki.jasp.20220740
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In view of the traditional aero-engine combustor design process with long calculation cycle, high processing test and cost which restricts the engine design cycle, based on the aero-engine combustor model, POD-PCE-Kriging (proper orthogonal decomposition-polynomial chaotic expansion-Kriging) model and particle swarm optimization (PSO) algorithms were combined to construct the combustion performance surrogate model and carry out multi-objective optimization design. Through the test, the predicted results of POD-PCE-Kriging model were compared with the calculated results of one-dimensional program, and the root mean square errors of the predicted values of combustion efficiency and total pressure loss were 0.0063% and 0.1227%, respectively. Optimization search was carried out for the design variables, and the obtained Pareto optimal solution set was analyzed to provide physical insight into the design of advanced aero-engine combustor to meet the performance specifications, which can quickly and accurately obtain the design parameters to meet the optimal performance and accelerate the development cycle of aero-engine.
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