Advances in Aerodynamics (Jul 2023)

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

  • Shuhong Tong,
  • Yue Ma,
  • Mingming Guo,
  • Ye Tian,
  • Wenyan Song,
  • Heng Wang,
  • Jialing Le,
  • Hua Zhang

DOI
https://doi.org/10.1186/s42774-023-00151-3
Journal volume & issue
Vol. 5, no. 1
pp. 1 – 25

Abstract

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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.

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