Enhancing Predictive Accuracy of Turbulent Subcooled Flow Boiling Using LES

The high heat transfer rates required in many cooling systems can often only be achieved through subcooled boiling flows in heated wall regions, with boiling providing the heat transfer rates required to maintain system integrity. Understanding the mechanism of boiling in systems with turbulent subcooled flows is essential for enhancing the predictive capabilities for nuclear thermal hydraulic systems. This study investigates two boiling models coupled with large eddy simulations employing a dynamic subgrid-scale eddy viscosity model. One boiling model utilises a mechanistic force balance approach to predict bubble dynamics: accounting for the bubble growth and detachment processes affected by micro-layer evaporation, heat transfer from the superheated liquid, and condensation on the bubble cap due to the subcooled liquid. The other model employs a reduced correlation-based approach to determine bubble departure diameter and frequency, aiming to improve the applicability of the force balance method while reducing computational and calibration requirements. To evaluate the performance of these models, validation is conducted against experimental data for vertically upward subcooled boiling flows using water and refrigerant R12. These datasets encompass a wide range of operating conditions, ensuring a robust and comprehensive assessment of model accuracy. Results indicate that both models achieve satisfactory predictive accuracy across all tested conditions, demonstrating improvements over equivalent Reynolds-Averaged Navier-Stokes-based approaches. Although the mechanistic model provides superior precision in predicting bubble dynamics, this enhanced accuracy comes at the cost of increased computational demand, making the correlation-based approach a viable alternative for engineering applications requiring reduced computational expense. These findings contribute to the ongoing development of high-fidelity boiling models for nuclear thermal hydraulic simulations, offering valuable insights for future research and industrial applications.