Dr Yuan Fang
Research Fellow,data-Driven Turbulence Modelling
Department of Mechanical Engineering
16 Scholarly works
0 Projects
HIGHLIGHTS
2027
Journal article
Unveiling boundary layer physics in the SPLEEN high-speed LPT with realistic turbulent inflow: A wall-resolved LES benchmark for RANS models
DOI: 10.1016/j.ast.2026.1134122026
Journal article
Machine-Learning Strategies for Transition–Turbulence Modeling for Low-Pressure Turbines With Unsteady Inflow Conditions
DOI: 10.1115/1.40725692026
Journal article
Machine-Learning-Enhanced Four-Equation Model for Predicting Roughness-Induced Transition
DOI: 10.2514/1.j0665412026
Journal article
Enhancing One-Equation Turbulence Models for Delta Wings by Gene Expression Programming
DOI: 10.2514/1.J0659062026
Journal article
Accelerating CFD-driven training of transition and turbulence models for turbine flows by one-shot and real-time transformer integration
DOI: 10.1016/j.compfluid.2025.1069272026
Journal article
The Impact of Transition and Turbulence Modeling on the SPLEEN High-Speed Low-Pressure Turbine Cascade
DOI: 10.1115/1.40694872025
Journal article
Symbolic turbulence model development for complex-geometry flows exploiting language model-based transfer learning
DOI: 10.1063/5.0278635
RECENT SCHOLARLY WORKS
2025
Journal article
A novel data-driven method for augmenting turbulence modeling for unsteady cavitating flows
DOI: 10.1016/j.ijheatfluidflow.2025.1098472025
Journal article
Constraining genetic symbolic regression via semantic backpropagation
DOI: 10.1007/s10710-025-09510-z2025
Journal article
A Reformulation of the Laminar Kinetic Energy Model to Enable Multi-mode Transition Predictions
DOI: 10.1007/s10494-024-00590-y