Physics-informed Deep Learning for Flow Modelling and Aerodynamic Optimization

Engineering

• Deep Learning 100%
• Surrogate Model 100%
• Optimisation Problem 80%
• Flow Field 40%
• Tasks 20%
• Objective Function 20%
• Dimensionality 20%
• Angle-of-Attack 20%
• Gradient-Based Algorithm 20%
• Computational Domain 20%
• Airfoil 20%
• Design Parameter 20%
• Starting Point 20%
• Geometric Feature 20%
• Lift to Drag Ratio 20%
• Optimal Angle 20%

Chemical Engineering

• Neural Network 100%
• Deep Learning 100%
• Constrained Optimization 25%