All Outputs (6)

XCALibre.jl: A Julia XPU unstructured finite volume Computational Fluid Dynamics library (2025)
Journal Article
Medina, H., Ellis, C. D., Mazin, T., Osborn, O., Ward, T., Ambrose, S., Aleksandrova, S., Rothwell, B., & Eastwick, C. (2025). XCALibre.jl: A Julia XPU unstructured finite volume Computational Fluid Dynamics library. The Journal of Open Source Software, 10(107), Article 7441. https://doi.org/10.21105/joss.07441

Understanding the behaviour of fluid flow, such as air over a wing, oil lubrication in gas turbines, or cooling air flow in a combustor or turbine is crucial in many engineering applications, from designing aircraft and automotive components to optim... Read More about XCALibre.jl: A Julia XPU unstructured finite volume Computational Fluid Dynamics library.

Vector-based neural network turbulent heat flux closures in near-wall cooling jet flows (2025)
Journal Article
Ellis, C. D., & Xia, H. (2025). Vector-based neural network turbulent heat flux closures in near-wall cooling jet flows. International Journal of Heat and Mass Transfer, 244, Article 126893. https://doi.org/10.1016/j.ijheatmasstransfer.2025.126893

Near-wall jet cooling flows are difficult to model using industrially appropriate CFD methods such as Reynolds-Averaged Navier–Stokes (RANS) approaches. Previous work has addressed the Reynolds stress closure and simple approaches to improve the turb... Read More about Vector-based neural network turbulent heat flux closures in near-wall cooling jet flows.

LES informed data-driven models for RANS simulations of single-hole cooling flows (2024)
Journal Article
Ellis, C. D., & Xia, H. (2024). LES informed data-driven models for RANS simulations of single-hole cooling flows. International Journal of Heat and Mass Transfer, 235, Article 126150. https://doi.org/10.1016/j.ijheatmasstransfer.2024.126150

A LES-informed data-driven approach for improved predictions of the turbulent heat flux vector has been sought for film and effusion cooling flow applications. Random forest and shallow neural networks have been used to train a spatially varying coef... Read More about LES informed data-driven models for RANS simulations of single-hole cooling flows.

Modelling and Simulation of Effusion Cooling—A Review of Recent Progress (2024)
Journal Article
Xia, H., Chen, X., & Ellis, C. D. (2024). Modelling and Simulation of Effusion Cooling—A Review of Recent Progress. Energies, 17(17), Article 4480. https://doi.org/10.3390/en17174480

Effusion cooling is often regarded as one of the critical techniques to protect solid surfaces from exposure to extremely hot environments, such as inside a combustion chamber where temperature can well exceed the metal melting point. Designing such... Read More about Modelling and Simulation of Effusion Cooling—A Review of Recent Progress.

Data-driven turbulence anisotropy in film and effusion cooling flows (2023)
Journal Article
Ellis, C., & Xia, H. (2023). Data-driven turbulence anisotropy in film and effusion cooling flows. Physics of Fluids, 35(10), Article 105114. https://doi.org/10.1063/5.0166685

Film and effusion cooling flows contain complex flow that classical Reynolds-averaged Navier–Stokes (RANS) models struggle to capture. A tensor-basis neural network is employed to provide an anisotropic model that can reproduce the Reynolds stress fi... Read More about Data-driven turbulence anisotropy in film and effusion cooling flows.

Impact of inflow turbulence on large‐eddy simulation of film cooling flows (2022)
Journal Article
Ellis, C., & Xia, H. (2022). Impact of inflow turbulence on large‐eddy simulation of film cooling flows. International Journal of Heat and Mass Transfer, 195, Article 123172. https://doi.org/10.1016/j.ijheatmasstransfer.2022.123172

The paper investigates the impact of industrially appropriate inflow turbulence on the turbulent state, mixing capability and surface coolant distribution of film cooling flow using LES. Near-wall and freestream turbulence, corresponding to turbulent... Read More about Impact of inflow turbulence on large‐eddy simulation of film cooling flows.