A data-driven approach to scale bridging in system thermal-hydraulic simulation

Keyphrases

• Data-driven Approach 100%
• Thermal-hydraulic Simulation 100%
• System Thermal-hydraulics 100%
• Scale Bridging 100%
• Coarse Mesh 100%
• Safety Analysis 66%
• Mesh Size 66%
• Physical Features 66%
• Local Patterns 66%
• Data-driven Model 66%
• Prototypic 33%
• System Level 33%
• Computational Efficiency 33%
• System Modeling 33%
• Reactor Systems 33%
• Computational Simulation 33%
• Machine Learning 33%
• Model Code 33%
• Training Data 33%
• Computer Code 33%
• System of Interest 33%
• Mixed Convection 33%
• Risk-informed 33%
• Multiscale Data 33%
• Plant Condition 33%
• Simulation Error 33%
• Mesh Effect 33%
• Fast Running 33%
• Model Errors 33%
• Boundary Layer 33%
• High-fidelity numerical Simulation 33%
• Physical Systems 33%
• Model Scalability 33%
• Verification & Validation 33%
• System Simulation 33%
• Validation Data 33%
• Machine Learning Algorithms 33%
• Testing Data 33%
• Curve Fitting 33%
• Simulation Accuracy 33%
• Advanced Machine Learning 33%
• Stumbling 33%
• Scale Issues 33%

Engineering

• Bridging 100%
• Coarse Mesh 100%
• Thermal/Hydraulic Simulation 100%
• Similarity 66%
• Safety Analysis 66%
• Mesh Size 66%
• Multiscale 33%
• Model Parameter 33%
• Metrics 33%
• Computational Efficiency 33%
• Boundary Condition 33%
• Learning System 33%
• Mixed Convection 33%
• Reactor System 33%
• Fitting Curve 33%
• Real Plant 33%
• Physical System 33%
• Boundary Layer 33%
• Global Scale 33%
• Machine Learning Algorithm 33%

Chemical Engineering

• Learning System 100%
• Scalability 50%
• Mixed Convection 50%