Predicting Equilibrium Bed Morphology of Large-Scale Meandering Rivers Using a Novel LES-Trained Machine Learning Approach

Keyphrases

• Large Eddy Simulation 100%
• Machine Learning Approach 100%
• High-fidelity Simulation 100%
• Bed Shear Stress 100%
• Meandering River 100%
• Bed Morphology 100%
• Convolutional Neural Network 66%
• Bed Elevation 66%
• Neural Network Autoencoder 66%
• Environmental Issues 33%
• Sediment Transport 33%
• Prediction Accuracy 33%
• Bankfull 33%
• Brute Force 33%
• Turbulence 33%
• Geometric Parameters 33%
• Shear Stress Distribution 33%
• Two-way Coupling 33%
• Stress Change 33%
• Stress Equilibrium 33%
• Bed Topography 33%
• Infrastructure Failure 33%
• Equilibrium Morphology 33%
• Morphodynamics 33%
• Induced Deformation 33%
• Large Rivers 33%
• Riverbank 33%
• Flow Conditions 33%
• Bed-morphodynamics 33%
• Novel Machine Learning 33%
• Morphodynamic Process 33%

Engineering

• Learning Approach 100%
• Learning System 100%
• Large Eddy Simulation 100%
• Shear Stress Distribution 66%
• Autoencoder 66%
• Convolutional Neural Network 66%
• Simulation Result 33%
• Flow Condition 33%
• Induced Deformation 33%
• Accurate Prediction 33%
• Geometric Parameter 33%
• Equilibrium Morphology 33%
• Riverbank 33%

Earth and Planetary Sciences

• Machine Learning 100%
• Morphodynamics 100%
• Large Eddy Simulation 100%
• Earth Surface Sediment Transport 33%
• Environmental Issue 33%
• Flow Condition 33%