Using physics-informed generative adversarial networks to perform super-resolution for multiphase fluid simulations

Keyphrases

• Super-resolution 100%
• Network Model 100%
• Turbulent Fluidization 100%
• Multiphase Fluid 100%
• Upsampling 100%
• Generative Adversarial Networks 100%
• Physics-informed 100%
• Fluid Simulation 100%
• High-resolution 50%
• Super-resolution Algorithm 50%
• Machine Learning Techniques 50%
• Engineering Design 50%
• System Performance 50%
• Phase Fraction 50%
• Machine Learning 50%
• Computationally Intensive 50%
• Computational Cost 50%
• Product Performance 50%
• Fluid Flow Simulation 50%
• Loss Function 50%
• Computational Fluid Dynamics Simulation 50%
• Fluid Phase 50%
• Fluid Flow Problems 50%
• Multiphase Fluid Flow 50%
• Physical Prototyping 50%
• Machine Learning Applications 50%
• Engineering Design Practice 50%
• Image Super-resolution 50%

Chemical Engineering

• Fluid Flow 100%
• Learning System 100%