Data Mining-Based optimization study on T-shaped multiple groove casing treatment for axial compressor stability

Casing treatment is a highly effective and promising technology for improving compressor stability. The study aims to enrich the casing treatment design method and reveal its mechanism for improving compressor stability and design guidelines. Focusing on Rotor37, we develop a multi-objective optimization platform that combines geometric parameterization, mesh generation, numerical calculations, optimization algorithms, and other relevant components. Five design variables are optimized to maximize stall margin improvement and minimize peak efficiency loss concurrently. The optimal T-shaped multi-groove casing treatment improved the stall margin by 11.49% and reduced peak efficiency loss to 0.13%. Furthermore, the impact of casing treatment on the flow field characteristic is quantified through three kinds of parameters. The quantification analysis demonstrates that the casing treatment enhances stability by improving the axial momentum of the mainstream flow through the radial momentum transport effect and reducing passage blockage. Additionally, Spearman correlation analysis and the Apriori algorithm are employed to investigate the relationships between seven T-shaped muti-groove geometric parameters and five flow field characteristic quantification parameters. The results validate the mechanism of casing treatment for improving compressor stability and obtain nine strongly associated rules. Finally, the linear correlation of the associated rules is evaluated to transform into design guidelines for casing treatment. The guidelines guide the design of T-shaped muti-groove geometry parameters for optimal performance. These guidelines stipulate that a single T-shaped groove should possess a minimum cross-sectional area of 10 mm² and a depth of not less than 5 mm.