MS014B Accelerating scientific discovery for dynamical systems with physics-informed machine learning II
MS Corresponding Organizer: Dr. Romit Maulik ( Argonne National Laboratory , United States )Scheduled presentations:
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ψ − flow: A Novel Physics-Constrained Architecture to Enforce Incompressibility and Boundary Conditions for Fast and Accurate Flow Predictions
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Physics-Informed Neural Network with Turbulent Flow over Fluid Saturated Porous Media
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Operator Learning via Neural Networks with Kernel-Weighted Corrective Residuals
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Data-Driven Structural Health Monitoring of Beam Elements Using Machine Learning Techniques
