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

20 May 2021

Papers citing "Physics-informed neural networks (PINNs) for fluid mechanics: A review"

46 / 96 papers shown

Title
Temporal Consistency Loss for Physics-Informed Neural Networks Sukirt Thakur M. Raissi H. Mitra A. Ardekani PINN 33 10 0 30 Jan 2023
Super-Resolution Analysis via Machine Learning: A Survey for Fluid Flows Kai Fukami K. Fukagata Kunihiko Taira AI4CE 14 104 0 26 Jan 2023
Physics-informed Neural Networks with Periodic Activation Functions for Solute Transport in Heterogeneous Porous Media Salah A. Faroughi Ramin Soltanmohammad Pingki Datta S. K. Mahjour S. Faroughi 18 22 0 17 Dec 2022
Physics-Constrained Generative Adversarial Networks for 3D Turbulence D. Tretiak A. Mohan Daniel Livescu GAN AI4CE PINN 16 2 0 01 Dec 2022
Physics-informed Neural Networks with Unknown Measurement Noise Philipp Pilar Niklas Wahlström PINN 23 6 0 28 Nov 2022
Machine Learning for Smart and Energy-Efficient Buildings Hari Prasanna Das Yu-Wen Lin Utkarsha Agwan Lucas Spangher Alex Devonport Yu Yang Ján Drgoňa A. Chong S. Schiavon C. Spanos HAI AI4CE 31 19 0 27 Nov 2022
A Physics-informed Diffusion Model for High-fidelity Flow Field Reconstruction Dule Shu Zijie Li A. Farimani DiffM AI4CE 35 124 0 26 Nov 2022
DS-GPS : A Deep Statistical Graph Poisson Solver (for faster CFD simulations) Matthieu Nastorg Marc Schoenauer Guillaume Charpiat T. Faney J. Gratien M. Bucci 14 2 0 21 Nov 2022
Physics-Guided, Physics-Informed, and Physics-Encoded Neural Networks in Scientific Computing Salah A. Faroughi N. Pawar C. Fernandes Maziar Raissi Subasish Das N. Kalantari S. K. Mahjour PINN AI4CE 27 49 0 14 Nov 2022
Physics-informed neural networks for gravity currents reconstruction from limited data Mickaël G. Delcey Y. Cheny S. Richter PINN AI4CE 19 11 0 03 Nov 2022
Physics-Informed CNNs for Super-Resolution of Sparse Observations on Dynamical Systems Daniel Kelshaw Georgios Rigas Luca Magri AI4CE 37 17 0 31 Oct 2022
Thermodynamics-informed neural networks for physically realistic mixed reality Quercus Hernandez Alberto Badías Francisco Chinesta Elías Cueto PINN AI4CE 22 16 0 24 Oct 2022
A Dimension-Augmented Physics-Informed Neural Network (DaPINN) with High Level Accuracy and Efficiency Weilong Guan Kai-Ping Yang Yinsheng Chen Zhong Guan PINN AI4CE 18 12 0 19 Oct 2022
Machine learning in bioprocess development: From promise to practice L. M. Helleckes J. Hemmerich W. Wiechert E. Lieres A. Grünberger 21 47 0 04 Oct 2022
On Physics-Informed Neural Networks for Quantum Computers Stefano Markidis PINN 32 18 0 28 Sep 2022
Accelerating hypersonic reentry simulations using deep learning-based hybridization (with guarantees) Paul Novello Gaël Poëtte D. Lugato S. Peluchon P. Congedo AI4CE 19 7 0 27 Sep 2022
Inverse modeling of nonisothermal multiphase poromechanics using physics-informed neural networks Daniel Amini E. Haghighat R. Juanes PINN AI4CE 25 32 0 07 Sep 2022
MRF-PINN: A Multi-Receptive-Field convolutional physics-informed neural network for solving partial differential equations Shihong Zhang Chi Zhang Bo Wang AI4CE 24 3 0 06 Sep 2022
NeuralUQ: A comprehensive library for uncertainty quantification in neural differential equations and operators Zongren Zou Xuhui Meng Apostolos F. Psaros George Karniadakis AI4CE 32 36 0 25 Aug 2022
$Physics-informed neural networks for diffraction tomography$ Physics-informed neural networks for diffraction tomography Amirhossein Saba Carlo Gigli Ahmed B. Ayoub D. Psaltis MedIm AI4CE 19 31 0 28 Jul 2022
Thermodynamics of learning physical phenomena Elías Cueto Francisco Chinesta AI4CE 25 22 0 26 Jul 2022
Physics-Informed Neural Networks for Shell Structures Jan-Hendrik Bastek D. Kochmann AI4CE 16 51 0 26 Jul 2022
Human Trajectory Prediction via Neural Social Physics Jiangbei Yue Tianyi Zhou He-Nan Wang AI4CE 24 100 0 21 Jul 2022
Momentum Diminishes the Effect of Spectral Bias in Physics-Informed Neural Networks G. Farhani Alexander Kazachek Boyu Wang 19 6 0 29 Jun 2022
A mixed formulation for physics-informed neural networks as a potential solver for engineering problems in heterogeneous domains: comparison with finite element method Shahed Rezaei Ali Harandi Ahmad Moeineddin Bai-Xiang Xu Stefanie Reese 21 112 0 27 Jun 2022
Physical Activation Functions (PAFs): An Approach for More Efficient Induction of Physics into Physics-Informed Neural Networks (PINNs) J. Abbasi Paal Ostebo Andersen PINN AI4CE 25 14 0 29 May 2022
DH-GAN: A Physics-driven Untrained Generative Adversarial Network for 3D Microscopic Imaging using Digital Holography Xiwen Chen Hongya Wang Abofazl Razi M. Kozicki C. Mann DiffM 17 1 0 25 May 2022
Bi-fidelity Modeling of Uncertain and Partially Unknown Systems using DeepONets Subhayan De Matthew J. Reynolds M. Hassanaly Ryan N. King Alireza Doostan AI4CE 26 37 0 03 Apr 2022
Calibrating constitutive models with full-field data via physics informed neural networks Craig M. Hamel K. Long S. Kramer AI4CE 27 28 0 30 Mar 2022
Physics-informed neural network solution of thermo-hydro-mechanical (THM) processes in porous media Daniel Amini E. Haghighat R. Juanes PINN AI4CE 19 23 0 03 Mar 2022
Rotationally Equivariant Super-Resolution of Velocity Fields in Two-Dimensional Fluids Using Convolutional Neural Networks Y. Yasuda R. Onishi 19 5 0 22 Feb 2022
Physics-informed neural networks for solving parametric magnetostatic problems Andrés Beltrán-Pulido Ilias Bilionis D. Aliprantis 24 34 0 08 Feb 2022
Physics-informed neural networks for non-Newtonian fluid thermo-mechanical problems: an application to rubber calendering process Thi Nguyen Khoa Nguyen T. Dairay Raphael Meunier Mathilde Mougeot PINN AI4CE 81 29 0 31 Jan 2022
Scientific Machine Learning through Physics-Informed Neural Networks: Where we are and What's next S. Cuomo Vincenzo Schiano Di Cola F. Giampaolo G. Rozza Maizar Raissi F. Piccialli PINN 26 1,179 0 14 Jan 2022
Hierarchical Learning to Solve Partial Differential Equations Using Physics-Informed Neural Networks Jihun Han Yoonsang Lee AI4CE 22 10 0 02 Dec 2021
Physics-Informed Neural Operator for Learning Partial Differential Equations Zong-Yi Li Hongkai Zheng Nikola B. Kovachki David Jin Haoxuan Chen Burigede Liu Kamyar Azizzadenesheli Anima Anandkumar AI4CE 62 382 0 06 Nov 2021
Physics informed neural networks for continuum micromechanics Alexander Henkes Henning Wessels R. Mahnken PINN AI4CE 16 139 0 14 Oct 2021
Simulating progressive intramural damage leading to aortic dissection using an operator-regression neural network Minglang Yin Ehsan Ban B. Rego Enrui Zhang C. Cavinato J. Humphrey George Karniadakis AI4CE 26 52 0 25 Aug 2021
IDRLnet: A Physics-Informed Neural Network Library Wei Peng Jun Zhang Weien Zhou Xiaoyu Zhao W. Yao Xiaoqian Chen PINN AI4CE 33 15 0 09 Jul 2021
Physics-Guided Deep Learning for Dynamical Systems: A Survey Rui Wang Rose Yu AI4CE PINN 39 64 0 02 Jul 2021
Parallel Physics-Informed Neural Networks via Domain Decomposition K. Shukla Ameya Dilip Jagtap George Karniadakis PINN 101 274 0 20 Apr 2021
Physics-informed neural networks with hard constraints for inverse design Lu Lu R. Pestourie Wenjie Yao Zhicheng Wang F. Verdugo Steven G. Johnson PINN 39 494 0 09 Feb 2021
An overview on deep learning-based approximation methods for partial differential equations C. Beck Martin Hutzenthaler Arnulf Jentzen Benno Kuckuck 30 146 0 22 Dec 2020
$NVIDIA SimNet^{TM}: an AI-accelerated multi-physics simulation framework$ NVIDIA SimNet^{TM}: an AI-accelerated multi-physics simulation framework O. Hennigh S. Narasimhan M. A. Nabian Akshay Subramaniam Kaustubh Tangsali M. Rietmann J. Ferrandis Wonmin Byeon Z. Fang S. Choudhry PINN AI4CE 93 126 0 14 Dec 2020
B-PINNs: Bayesian Physics-Informed Neural Networks for Forward and Inverse PDE Problems with Noisy Data Liu Yang Xuhui Meng George Karniadakis PINN 183 759 0 13 Mar 2020
hp-VPINNs: Variational Physics-Informed Neural Networks With Domain Decomposition E. Kharazmi Zhongqiang Zhang George Karniadakis 125 508 0 11 Mar 2020