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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 76–100 of 192 papers

TitleStatusHype
Physics-informed machine learning for composition-process-property alloy design: shape memory alloy demonstration—0
A Physics-Informed Machine Learning Approach for Solving Heat Transfer Equation in Advanced Manufacturing and Engineering Applications—0
A Physics-Informed Machine Learning Approach for Solving Distributed Order Fractional Differential Equations—0
A Physics-informed Machine Learning-based Control Method for Nonlinear Dynamic Systems with Highly Noisy Measurements—0
A Physics-Informed Machine Learning for Electricity Markets: A NYISO Case Study—0
A Physics-Informed Machine Learning Framework for Safe and Optimal Control of Autonomous Systems—0
A Physics-Informed Machine Learning Model for Porosity Analysis in Laser Powder Bed Fusion Additive Manufacturing—0
A physics-informed machine learning model for reconstruction of dynamic loads—0
A Physics-informed machine learning model for time-dependent wave runup prediction—0
Physics-Informed Machine Learning for Smart Additive Manufacturing—0
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
Physics-informed Modularized Neural Network for Advanced Building Control by Deep Reinforcement Learning—0
Physics-informed neural networks for pathloss prediction—0
A Metalearning Approach for Physics-Informed Neural Networks (PINNs): Application to Parameterized PDEs—0
Residual-based physics-informed transfer learning: A hybrid method for accelerating long-term CFD simulations via deep learning—0
Scalable Neural Dynamic Equivalence for Power Systems—0
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