Shear-center shifting in oblique stagnation-point Casson flow over a rotating disk: A hybrid numerical–AI approach

Abstract

Casson fluid flow over a rotating disk is relevant to industrial and biomedical systems involving yield-stress fluids, including blood-handling devices, polymer processing, coating, lubrication, printing, and food processing. In such applications, prediction of shear stress, momentum transfer, and boundary-layer behavior is essential. This study investigates Casson fluid flow over a rotating disk using similarity transformations, which reduce the governing partial differential equations to coupled ordinary differential equations and facilitate numerical analysis. The study examines the effects of the Casson parameter and the obliqueness interaction parameter on velocity characteristics and shear-center behavior. The results show that increasing the Casson parameter reduces yield-stress resistance and enhances momentum diffusion near the disk surface, increasing the axial and radial velocity components. Conversely, the azimuthal velocity decreases because of rotational momentum redistribution. Increasing the Casson parameter shifts the shear center toward the disk surface, indicating weaker shear resistance and a less concentrated shear-stress distribution. To reduce computational cost, we develop radial basis function-based artificial neural network (ANN) from a numerical dataset. The ANN accurately reproduces the nonlinear relationships between the governing parameters and flow characteristics and shows agreement with numerical solutions. Increasing the obliqueness interaction parameter from 1 to 3 causes the shear center to migrate toward the negative and positive image directions for both Newtonian and Casson fluids. The displacement magnitude is approximately 1.75 for the Newtonian fluid and 7.06 for the Casson fluid. Thus, the Casson fluid exhibits nearly four times greater shear-center migration, demonstrating enhanced sensitivity of shear distribution to oblique interaction.