Volume 68

Multidisciplinary Design Optimization of Centrifugal Compressors for Enhanced Stability and Isentropic Efficiency Yu Tian, Guoyuan Ma

Abstract

Centrifugal compressors are widely used in the energy industry due to their simple structure, stable operation, high pressure ratio, and excellent efficiency. This study presents a multidisciplinary optimization framework integrating computational fluid dynamics with hybrid modeling for centrifugal compressor impeller design. To address limited sample challenges, we develop an improved artificial neural network enhanced by neighborhood component analysis for dimensionality reduction and genetic algorithm optimization, achieving 42% faster convergence than conventional methods. Our multi-objective approach simultaneously maximizes isentropic efficiency and operational stability across off-design conditions. Experimental validation demonstrates: (1) 1% improvement in design-point isentropic efficiency, and (2) 0.3% wider high-efficiency operational range compared to baseline designs. Centrifugal compressors account for more than 30% of the power consumption in industrial production and energy systems. Improving their efficiency and stability plays a significant role in reducing energy consumption and enhancing overall efficiency.

Keywords Energy efficiency, Centrifugal Compressor, Multi Objective Optimization, Hybrid Model