Design Optimization of 1.5-Stage Transonic Compressor Based on BPNN Surrogate Model and NSGA-II

Author:

Li Xinlong1234,Jin Yun1234,Liu Shuaipeng1234,Geng Shaojuan1234,Zhang Xiaoyu1234,Zhang Hongwu1234

Affiliation:

1. Advanced Gas Turbine Laboratory, Institute of Engineering Thermophysics, Chinese Academy of Sciences, Beijing 100190, China

2. Innovation Academy for Light-Duty Gas Turbine, Chinese Academy of Sciences, Beijing 100190, China

3. Key Laboratory of Advanced Energy and Power, Chinese Academy of Sciences, Beijing 100190, China

4. School of Engineering Science, University of Chinese Academy of Sciences, Beijing 100049, China

Abstract

To achieve multi-objective aerodynamics design optimization for a 1.5-stage transonic compressor, a design platform incorporating blade parameterization methods, a BPNN surrogate model, and the NSGA-II optimization method was developed. The stagger angle distribution of three blade rows was selected as the optimization variable, with isentropic efficiency at the new design condition and stall margin set as the goal functions. Results demonstrated that, without altering the blade profile shape and endwall contour, the flow rate at design condition increased by 7.1%, stall margin increased by 1.8%, isentropic efficiency decreased by 0.0087, and total pressure ratio experienced a slight increase. The flow field at different conditions before and after optimization was compared and analyzed. The analysis indicated that the tangential velocity of rotor outlet becomes the determining factor for the compressor’s work capacity. The relative Mach number at the rotor inlet emerged as the key parameter affecting shock wave intensity and shock wave/boundary layer interaction, which directly influenced the efficiency of the rotor passage. At near stall condition, the stator vane root’s stagger angle is crucial for the compressor’s performance.

Funder

National Science and Technology Major Project

APC

Publisher

MDPI AG

Subject

Electrical and Electronic Engineering,Industrial and Manufacturing Engineering,Control and Optimization,Mechanical Engineering,Computer Science (miscellaneous),Control and Systems Engineering

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