A Physics-Informed Machine Learning Approach for Solving Heat Transfer Equation in Advanced Manufacturing and Engineering Applications

28 September 2020

Papers citing "A Physics-Informed Machine Learning Approach for Solving Heat Transfer Equation in Advanced Manufacturing and Engineering Applications"

39 / 39 papers shown

Title
Unraveling particle dark matter with Physics-Informed Neural Networks M.P. Bento H.B. Câmara J.F. Seabra 67 0 0 24 Feb 2025
Differentiable Neural-Integrated Meshfree Method for Forward and Inverse Modeling of Finite Strain Hyperelasticity Honghui Du Binyao Guo QiZhi He AI4CE 38 0 0 15 Jul 2024
Physics-Constrained Learning for PDE Systems with Uncertainty Quantified Port-Hamiltonian Models Kaiyuan Tan Peilun Li Thomas Beckers AI4CE 18 3 0 17 Jun 2024
Physics and geometry informed neural operator network with application to acoustic scattering S. Nair Timothy F. Walsh Greg Pickrell Fabio Semperlotti AI4CE 38 2 0 02 Jun 2024
A finite element-based physics-informed operator learning framework for spatiotemporal partial differential equations on arbitrary domains Yusuke Yamazaki Ali Harandi Mayu Muramatsu A. Viardin Markus Apel T. Brepols Stefanie Reese Shahed Rezaei AI4CE 39 12 0 21 May 2024
Densely Multiplied Physics Informed Neural Networks Feilong Jiang Xiaonan Hou Min Xia PINN 19 2 0 06 Feb 2024
Data assimilation and parameter identification for water waves using the nonlinear Schrödinger equation and physics-informed neural networks Svenja Ehlers Niklas A. Wagner Annamaria Scherzl Marco Klein Norbert Hoffmann M. Stender 18 1 0 08 Jan 2024
Opening the Black Box: Towards inherently interpretable energy data imputation models using building physics insight Antonio Liguori Matias Quintana Chun Fu Clayton Miller J. Frisch C. Treeck AI4CE 13 5 0 28 Nov 2023
Probabilistic Physics-integrated Neural Differentiable Modeling for Isothermal Chemical Vapor Infiltration Process Deepak Akhare Zeping Chen R. Gulotty Tengfei Luo Jian-Xun Wang AI4CE 19 5 0 13 Nov 2023
Transfer learning for improved generalizability in causal physics-informed neural networks for beam simulations Taniya Kapoor Hongrui Wang Alfredo Núñez R. Dollevoet AI4CE PINN 19 15 0 01 Nov 2023
A Sequential Meta-Transfer (SMT) Learning to Combat Complexities of Physics-Informed Neural Networks: Application to Composites Autoclave Processing Milad Ramezankhani A. Milani PINN 24 4 0 12 Aug 2023
Learning Specialized Activation Functions for Physics-informed Neural Networks Honghui Wang Lu Lu Shiji Song Gao Huang PINN AI4CE 16 12 0 08 Aug 2023
Group Equivariant Fourier Neural Operators for Partial Differential Equations Jacob Helwig Xuan Zhang Cong Fu Jerry Kurtin Stephan Wojtowytsch Shuiwang Ji AI4CE 58 28 0 09 Jun 2023
Digital Twins in Wind Energy: Emerging Technologies and Industry-Informed Future Directions Florian Stadtmann Adil Rasheed T. Kvamsdal K. Johannessen Omer San ... Håvard Paulshus Tore Rasmussen E. Rishoff Francesco Scibilia John Olav Skogås 25 31 0 16 Apr 2023
CoolPINNs: A Physics-informed Neural Network Modeling of Active Cooling in Vascular Systems N. V. Jagtap M. Mudunuru K. Nakshatrala PINN AI4CE 16 9 0 09 Mar 2023
Solving PDEs with Unmeasurable Source Terms Using Coupled Physics-Informed Neural Network with Recurrent Prediction for Soft Sensors Aina Wang Pan Qin Ximing Sun PINN AI4CE 38 2 0 20 Jan 2023
AirfRANS: High Fidelity Computational Fluid Dynamics Dataset for Approximating Reynolds-Averaged Navier-Stokes Solutions F. Bonnet Jocelyn Ahmed Mazari Paola Cinnella Patrick Gallinari AI4CE 33 54 0 15 Dec 2022
Interpretability and accessibility of machine learning in selected food processing, agriculture and health applications N. Ranasinghe A. Ramanan S. Fernando P. N. Hameed D. Herath T. Malepathirana P. Suganthan M. Niranjan Saman K. Halgamuge 13 2 0 30 Nov 2022
Partial Differential Equations Meet Deep Neural Networks: A Survey Shudong Huang Wentao Feng Chenwei Tang Jiancheng Lv AI4CE AIMat 29 18 0 27 Oct 2022
CP-PINNs: Data-Driven Changepoints Detection in PDEs Using Online Optimized Physics-Informed Neural Networks Zhi-Ling Dong Pawel Polak PINN 21 1 0 18 Aug 2022
PhyGNNet: Solving spatiotemporal PDEs with Physics-informed Graph Neural Network Longxiang Jiang Liyuan Wang Xinkun Chu Yonghao Xiao Hao Zhang AI4CE 15 12 0 07 Aug 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
Faster Optimization on Sparse Graphs via Neural Reparametrization Nima Dehmamy C. Both J. Long Rose Yu 13 0 0 26 May 2022
Physics guided neural networks for modelling of non-linear dynamics Haakon Robinson Suraj Pawar Adil Rasheed Omer San PINN AI4TS AI4CE 16 34 0 13 May 2022
Self-scalable Tanh (Stan): Faster Convergence and Better Generalization in Physics-informed Neural Networks Raghav Gnanasambandam Bo Shen Jihoon Chung Xubo Yue Zhenyu Zhen Kong LRM 37 12 0 26 Apr 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
Temperature Field Inversion of Heat-Source Systems via Physics-Informed Neural Networks Xu Liu Wei Peng Zhiqiang Gong Weien Zhou W. Yao 27 54 0 18 Jan 2022
A generic physics-informed neural network-based framework for reliability assessment of multi-state systems Taotao Zhou Xiaoge Zhang E. Droguett A. Mosleh AI4CE 25 31 0 01 Dec 2021
Residual fourier neural operator for thermochemical curing of composites Gengxiang Chen Yingguang Li Xu Liu Qinglu Meng Jing Zhou Xiaozhong Hao AI4CE 19 7 0 15 Nov 2021
CAN-PINN: A Fast Physics-Informed Neural Network Based on Coupled-Automatic-Numerical Differentiation Method P. Chiu Jian Cheng Wong C. Ooi M. Dao Yew-Soon Ong PINN 31 207 0 29 Oct 2021
Physics-informed neural network simulation of multiphase poroelasticity using stress-split sequential training E. Haghighat Daniel Amini R. Juanes PINN AI4CE 23 95 0 06 Oct 2021
Physics-informed Convolutional Neural Networks for Temperature Field Prediction of Heat Source Layout without Labeled Data Xiaoyu Zhao Zhiqiang Gong Yunyang Zhang Wen Yao Xiaoqian Chen OOD AI4CE 77 91 0 26 Sep 2021
Learning in Sinusoidal Spaces with Physics-Informed Neural Networks Jian Cheng Wong C. Ooi Abhishek Gupta Yew-Soon Ong AI4CE PINN SSL 18 77 0 20 Sep 2021
Physics-informed Neural Network for Nonlinear Dynamics in Fiber Optics Xiaotian Jiang Danshi Wang Qirui Fan Min Zhang Chao Lu A. Lau AI4CE PINN 16 79 0 01 Sep 2021
Applying physics-based loss functions to neural networks for improved generalizability in mechanics problems Samuel J. Raymond David B. Camarillo PINN AI4CE 39 12 0 30 Apr 2021
A Machine Learning Framework for Real-time Inverse Modeling and Multi-objective Process Optimization of Composites for Active Manufacturing Control K. D. Humfeld Dawei Gu Geoffrey A. Butler K. Nelson N. Zobeiry AI4CE 11 43 0 22 Apr 2021
Theory-Guided Machine Learning for Process Simulation of Advanced Composites N. Zobeiry A. Poursartip AI4CE 11 5 0 30 Mar 2021
Physics-Informed Neural Network for Modelling the Thermochemical Curing Process of Composite-Tool Systems During Manufacture S. Niaki E. Haghighat Trevor Campbell Xinglong Li R. Vaziri AI4CE 13 203 0 27 Nov 2020
Integrating Scientific Knowledge with Machine Learning for Engineering and Environmental Systems J. Willard X. Jia Shaoming Xu M. Steinbach Vipin Kumar AI4CE 91 388 0 10 Mar 2020