Appointment: Assistant Professor

Research topics:
• Combustion modeling
• Combustion instability
• Computational Fluid Dynamics (CFD)
• Flamelet models
• Fluid-structure interactions
• Gas turbine engines
• High-fidelity simulations
• High-speed air-breathing vehicles
• Large-eddy simulations
• Numerical combustion
• Pollutant emission
• Turbulent non-/reacting flows

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1 to 4 of 4 Results
Related Data for: Accelerating Fluid Simulations with Graph Convolution Network Predicted Flow Fields
Jun 11, 2025 - Airfoils Datasets For Deep Learning (AI4Science)
Lim, Wei Xian; Chan, Wai Lee, 2025, "Related Data for: Accelerating Fluid Simulations with Graph Convolution Network Predicted Flow Fields", https://doi.org/10.21979/N9/9OYSTD, DR-NTU (Data), V1
The field of computational fluid dynamics (CFD) is integral to engineering disciplines, particularly for designing systems that operate under complex fluid flow conditions. Accurate simulation of flow fields is essential for optimizing performance across a variety of applications...
singleAirfoil_Re500_aoa0_JZfixed.pickle
Jun 11, 2025 - Related Data for: Accelerating Fluid Simulations with Graph Convolution Network Predicted Flow Fields
Unknown - 7.8 GB - MD5: c2b4fb160d50a630fce63b721b314f50
DataOpenFOAMRaw
single NACA airfoil flow fields for constant flow conditions of Re=500 and AOA=0 degrees via RANS
singleAirfoil_Re500_aoa5_JZfixed.pickle
Jun 11, 2025 - Related Data for: Accelerating Fluid Simulations with Graph Convolution Network Predicted Flow Fields
Unknown - 7.8 GB - MD5: e82371c6ced9970848359f361c73d611
DataOpenFOAMRaw
single NACA airfoil flow fields for constant flow conditions of Re=500 and AOA=5 degrees via RANS
single_randomFields.pickle
Jun 11, 2025 - Related Data for: Accelerating Fluid Simulations with Graph Convolution Network Predicted Flow Fields
Unknown - 7.1 GB - MD5: 2a2250a06818457e01ed7b596ad76837
DataOpenFOAMRaw
single NACA airfoil flow fields for random flow conditions via RANS
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