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Optimization of aero-engine combustion chambers with the assistance of Hierarchical-Kriging surrogate model based on POD downscaling method.

Authors :
Tong, Shuhong
Ma, Yue
Guo, Mingming
Tian, Ye
Song, Wenyan
Wang, Heng
Le, Jialing
Zhang, Hua
Source :
Advances in Aerodynamics; 7/3/2023, Vol. 5 Issue 1, p1-25, 25p
Publication Year :
2023

Abstract

In view of the long calculation cycle, high processing test and cost of the traditional aero-engine combustion chamber design process, which restricts the engine optimization design cycle, this paper innovatively proposes a surrogate model for the performance of aero-engine combustion chambers based on the POD-Hierarchical-Kriging method. Through experiments, the predicted results of the POD-Hierarchical-Kriging model are compared and analyzed with the calculated results of the one-dimensional program, and the root mean square error of the predicted values of combustion efficiency and total pressure loss is 0.0064% and 0.1995%, respectively. The accuracy of the POD-Hierarchical-Kriging model is compared with the cubic polynomial model, the basic Kriging model and the Hierarchical-Kriging model. It verifies the feasibility and accuracy of the POD-Hierarchical-Kriging model for the prediction of performance of aero-engine combustion chambers. The global sensitivity analysis method is applied to obtain the influence effect of design variables on the performance. Then, a multi-objective optimization method based on the NSGA-II algorithm is studied, and finally the optimal set of Pareto solutions is obtained and analyzed, which can be used to guide the optimal design of aero-engine combustion chambers and accelerate the progress of aero-engine development. [ABSTRACT FROM AUTHOR]

Details

Language :
English
Volume :
5
Issue :
1
Database :
Complementary Index
Journal :
Advances in Aerodynamics
Publication Type :
Academic Journal
Accession number :
164660557
Full Text :
https://doi.org/10.1186/s42774-023-00151-3