A Method Proposed to Predict Particle Deposition Based on Critical Viscosity Model and Roughness Height Prediction in a Turbine Cascade

Abstract

Abstract Particle deposition is a common phenomenon in a turbine cascade. It can change the surface condition, which influences the flow and heat transfer. It is very important to accurately predict particle deposition and surface condition changes. In this study, a combined particle deposition algorithm is proposed based on the critical viscosity deposition model and roughness height prediction. It couples the influence of surface roughness into the particle deposition. The combined model newly developed is employed for the particle deposition. Its effects in a turbine cascade with the combined model are discussed. The results show the deposition is mainly concentrated on the leading edge of the cascade and the pressure side. Small diameter particles are mainly deposited on the suction side and the large ones are mainly deposited on the pressure side due to inertial effect. The deposition number increases with the particle diameter. As time goes by, more particles deposit on the wall, which builds roughness height and shows a spreading characteristic. Heat transfer is enhanced by the surface roughness and flow characteristics including separation vortex and leakage vortex, in which flow pattern may dominate the effect. In addition, the separation vortex and leakage vortex have a significant effect on the deposition distribution, especially for small diameter particles.