Efforts to Identify the Most Suitable RANS Turbulence Model for Accurate Conjugate Heat Transfer Prediction in Regenerative Cooled Nozzles

Abstract

This study presents a two-part numerical study aimed at improving the prediction and understanding of regenerative cooling in supersonic nozzles. The first objective was to identify the most appropriate Reynolds-averaged Navier–Stokes turbulence model for accurately predicting conjugate heat transfer. Three turbulence models, Shear Stress Transport, Reynolds stress model (RSM)-ω, and RSM-ω with shear flow corrections (SFC), were tested through comparative analysis and simulations to evaluate their accuracy in predicting the heat flux rate and temperature on the nozzle wall. The results indicate that the RSM-ω turbulence model with shear flow corrections provides the best thermal prediction, achieving an improvement of 28% compared to the next-best model. The second part assesses the impact of key parameters on cooling efficiency. High coolant pressure proves advantageous for extremely hot-gas flow due to increased saturation temperature. Interestingly, the height of the cooling slot has less significance, suggesting other factors should be prioritized in film-cooling system design. The study also investigates the effectiveness of hydrogen coolant in reducing wall gas temperatures and preventing excessive heat that could melt the nozzle material. Transient results show that the gas-side wall temperature increases more rapidly than the coolant side during start-up and cooling the walls takes longer than reaching a steady-state for the hot-gas flow. The simulation results align well with experimental data, validating the accuracy and reliability of the numerical approach.