Results 281 to 290 of about 28,522,762 (408)

Transfer Learning in Physics‐Informed Neurals Networks: Full Fine‐Tuning, Lightweight Fine‐Tuning, and Low‐Rank Adaptation

open access: yesInternational Journal of Mechanical System Dynamics, EarlyView.
ABSTRACT AI for PDEs has garnered significant attention, particularly physics‐informed neural networks (PINNs). However, PINNs are typically limited to solving specific problems, and any changes in problem conditions necessitate retraining. Therefore, we explore the generalization capability of transfer learning in the strong and energy forms of PINNs ...
Yizheng Wang   +6 more
wiley   +1 more source

Numerical Simulation of Transient Heat Conduction With Moving Heat Source Using Physics Informed Neural Networks

open access: yesInternational Journal of Mechanical System Dynamics, EarlyView.
ABSTRACT In this article, the physics informed neural networks (PINNs) is employed for the numerical simulation of heat transfer involving a moving source under mixed boundary conditions. To reduce computational effort and increase accuracy, a new training method is proposed that uses a continuous time‐stepping through transfer learning.
Anirudh Kalyan, Sundararajan Natarajan
wiley   +1 more source

ANN‐Based Green's Function Approach for Reservoir Geomechanics

open access: yesInternational Journal for Numerical and Analytical Methods in Geomechanics, EarlyView.
ABSTRACT Green's functions have been a tool to analyze important reservoir geomechanics effects like subsidence, compaction, well closure, and permeability variation. However, the classical Green's function is related to linear elastic, homogenous, and geometrically simplified media.
Matheus L. Peres   +2 more
wiley   +1 more source

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