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Physics-informed machine learning

Machine learning used to represent physics-based and/or engineering models

Papers

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Showing 91–100 of 192 papers

TitleStatusHype
Physics-Informed Machine Learning for the Inverse Design of Wave Scattering Clusters—0
Physics-Informed Machine Learning Models for Predicting the Progress of Reactive-Mixing—0
Physics-informed Machine Learning of Parameterized Fundamental Diagrams—0
Physics-Informed Machine Learning of Argon Gas-Driven Melt Pool Dynamics—0
Physics-informed machine learning of redox flow battery based on a two-dimensional unit cell model—0
Physics-informed machine learning of the correlation functions in bulk fluids—0
Physics-Informed Machine Learning On Polar Ice: A Survey—0
Physics Informed Machine Learning (PIML) methods for estimating the remaining useful lifetime (RUL) of aircraft engines—0
Physics-Informed Machine Learning Regulated by Finite Element Analysis for Simulation Acceleration of Laser Powder Bed Fusion—0
Physics-Informed Machine Learning Towards A Real-Time Spacecraft Thermal Simulator—0
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