Results 231 to 240 of about 13,405 (259)

Physics-informed machine learning for reliability and systems safety applications: State of the art and challenges

Reliability Engineering and System Safety, 2023
Pingfeng Wang
exaly  

Physics-informed neural networks (PINNs) for fluid mechanics: a review

Acta Mechanica Sinica/Lixue Xuebao, 2022
Shengze Cai, Zhicheng Wang, Minglang Yin
exaly  

A comprehensive study of non-adaptive and residual-based adaptive sampling for physics-informed neural networks

Computer Methods in Applied Mechanics and Engineering, 2023
Chenxi Wu, Min Zhu, Qinyang Tan
exaly  

BOUNDARY-ENFORCED PHYSICS-INFORMED NEURAL NETWORKS

Deterministic Lateral Displacement (DLD) devices are vital tools in microfluidics, enabling size-based, label-free separation of cells and particles. These devices play an essential role in cancer diagnostics by effectively isolating circulating tumor cells (CTCs) from blood samples.
openaire   +1 more source

A physics-informed neural network for creep-fatigue life prediction of components at elevated temperatures

Engineering Fracture Mechanics, 2021
Jian-Guo Gong
exaly  

Physics informed neural networks for continuum micromechanics

Computer Methods in Applied Mechanics and Engineering, 2022
Alexander Henkes, Henning Wessels
exaly  

Physics-informed multi-LSTM networks for metamodeling of nonlinear structures

Computer Methods in Applied Mechanics and Engineering, 2020
Ruiyang Zhang, Yang Liu, Hao Sun
exaly  

A physics-informed machine learning approach for solving heat transfer equation in advanced manufacturing and engineering applications

Engineering Applications of Artificial Intelligence, 2021
Navid Zobeiry
exaly  

A physics-informed deep learning framework for inversion and surrogate modeling in solid mechanics

Computer Methods in Applied Mechanics and Engineering, 2021
Ehsan Haghighat, Maziar Raissi, Adrian Moure   +2 more
exaly  

Adaptive activation functions accelerate convergence in deep and physics-informed neural networks

Journal of Computational Physics, 2020
Ameya D Jagtap, Kenji Kawaguchi
exaly