A new variant of renormalization group turbulence model for flows in axial compressor cascade

This study introduces a modified Renormalization Group (RNG) k–ε turbulence model for axial compressor cascades, designed to improve the prediction of total pressure loss coefficient and wake profiles. Built on the theoretical foundation of Yakhot and Orszag's RNG theory, the model incorporates a locally adaptive η0 coefficient, enabling it to better capture flow physics across varying near-wall resolutions and wall treatment approaches. The model is called RNG Fc model and was validated using experimental data from The Advisory Group for Aerospace Research and Development (AGARD) Working Group 18 (WG18), focusing on the V2 and V103 compressor cascades under on design and off-design conditions. Comparative analyses vs original RNG k–ε and shear stress transport k–ω models demonstrate that the presented model achieves superior accuracy in total pressure loss calculations and wake predictions at various inlet Mach numbers. The model's performance remains consistent across different computational grids, including low y+ and high y+ structures, and is compatible with both scalable wall functions and enhanced wall treatments. Notably, the modified model exhibits computational efficiency and numerical stability, making it a promising tool for industrial applications. This work highlights the potential of the RNG Fc model as a robust and cost-effective alternative for turbulence modeling in axial compressor cascade analyses, offering significant improvements over traditional Reynolds averaged Navier–Stokes models.