Finite-Volume Physics-Informed U-Net for Flow Field Reconstruction With Sparse Data

Keyphrases

• Finite Volume 100%
• Partial Differential Equations 100%
• U-Net 100%
• Sparse Data 100%
• Physics-informed 100%
• Flow Field Reconstruction 100%
• Finite Volume Method 75%
• Physics-informed Neural Networks 50%
• Neural Network 25%
• Sampling Strategy 25%
• Physical Laws 25%
• Prediction Accuracy 25%
• Hybrid Data 25%
• Neural Network Framework 25%
• Neural Network Model 25%
• Fluid Dynamics 25%
• Computational Domain 25%
• Data Assimilation 25%
• Physics-based Model 25%
• Conservative Form 25%
• Complex Procedure 25%
• Discretize 25%
• Model Capabilities 25%
• Sparse Measurements 25%
• Novel Convolutional Neural Network 25%
• Interface Parameters 25%
• Effective Engagement 25%
• Convective Problems 25%
• Low Accuracy 25%

Engineering

• Flow Distribution 100%
• Partial Differential Equation 100%
• U-Net 100%
• Finite Volume 100%
• Finite Volume Method 75%
• Physics Informed Neural Network 50%
• Convective 25%
• Limitations 25%
• Network Model 25%
• Measurement Data 25%
• Convolutional Neural Network 25%
• Fluid Dynamics 25%
• Computational Domain 25%
• Initial and Boundary Condition 25%

Computer Science

• Partial Differential Equation 100%
• U-Net 100%
• Finite Volume Method 75%
• Physics-Informed Neural Network 50%
• Neural Network 25%
• Prediction Accuracy 25%
• Traditional Method 25%
• Neural Network Model 25%
• Convolutional Neural Network 25%
• Boundary Condition 25%
• Measurement Data 25%
• Initial Condition 25%
• Computational Domain 25%