A physics-informed variational DeepONet for predicting the crack path in brittle materials

16 August 2021

Papers citing "A physics-informed variational DeepONet for predicting the crack path in brittle materials"

50 / 65 papers shown

Title
Towards Gaussian Process for operator learning: an uncertainty aware resolution independent operator learning algorithm for computational mechanics Sawan Kumar R. Nayek Souvik Chakraborty 36 1 0 17 Sep 2024
Spatio-spectral graph neural operator for solving computational mechanics problems on irregular domain and unstructured grid Subhankar Sarkar Souvik Chakraborty 27 0 0 01 Sep 2024
Data-Driven Stochastic Closure Modeling via Conditional Diffusion Model and Neural Operator Xinghao Dong Chuanqi Chen Jin-Long Wu DiffM AI4CE 41 5 0 06 Aug 2024
Synergistic Learning with Multi-Task DeepONet for Efficient PDE Problem Solving Varun V. Kumar S. Goswami Katiana Kontolati Michael D. Shields George Em Karniadakis AI4CE 71 6 0 05 Aug 2024
Accelerating Phase Field Simulations Through a Hybrid Adaptive Fourier Neural Operator with U-Net Backbone Christophe Bonneville N. Bieberdorf Arun Hegde Mark Asta H. Najm Laurent Capolungo C. Safta AI4CE 46 2 0 24 Jun 2024
RandONet: Shallow-Networks with Random Projections for learning linear and nonlinear operators Gianluca Fabiani Ioannis G. Kevrekidis Constantinos Siettos A. Yannacopoulos 27 11 0 08 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
Gradient Flow Based Phase-Field Modeling Using Separable Neural Networks R. Mattey Susanta Ghosh AI4CE 48 1 0 09 May 2024
A review on data-driven constitutive laws for solids J. Fuhg G. A. Padmanabha N. Bouklas B. Bahmani WaiChing Sun Nikolaos N. Vlassis Moritz Flaschel P. Carrara L. Lorenzis AI4CE AILaw 31 32 0 06 May 2024
Neural Operator induced Gaussian Process framework for probabilistic solution of parametric partial differential equations Sawan Kumar R. Nayek Souvik Chakraborty 40 2 0 24 Apr 2024
A finite operator learning technique for mapping the elastic properties of microstructures to their mechanical deformations Shahed Rezaei Reza Najian Asl S. Faroughi Mahdi Asgharzadeh Ali Harandi Rasoul Najafi Koopas G. Laschet Stefanie Reese Markus Apel AI4CE 42 4 0 28 Mar 2024
Heterogeneous Peridynamic Neural Operators: Discover Biotissue Constitutive Law and Microstructure From Digital Image Correlation Measurements S. Jafarzadeh Stewart Silling Lu Zhang Colton J. Ross Chung-Hao Lee S. M. R. Rahman Shuodao Wang Yue Yu 36 5 0 27 Mar 2024
MPIPN: A Multi Physics-Informed PointNet for solving parametric acoustic-structure systems Chu Wang Jinhong Wu Yanzhi Wang Zhijian Zha Qi Zhou PINN 24 3 0 02 Mar 2024
Diffeomorphism Neural Operator for various domains and parameters of partial differential equations Zhiwei Zhao Changqing Liu Yingguang Li Zhibin Chen Xu Liu AI4CE MedIm 33 3 0 19 Feb 2024
Kolmogorov n-Widths for Multitask Physics-Informed Machine Learning (PIML) Methods: Towards Robust Metrics Michael Penwarden H. Owhadi Robert M. Kirby AI4CE 22 1 0 16 Feb 2024
An operator learning perspective on parameter-to-observable maps Daniel Zhengyu Huang Nicholas H. Nelsen Margaret Trautner 32 11 0 08 Feb 2024
Resolution invariant deep operator network for PDEs with complex geometries Jianguo Huang Yue Qiu 32 0 0 01 Feb 2024
RiemannONets: Interpretable Neural Operators for Riemann Problems Ahmad Peyvan Vivek Oommen Ameya Dilip Jagtap George Karniadakis AI4CE 44 22 0 16 Jan 2024
Peridynamic Neural Operators: A Data-Driven Nonlocal Constitutive Model for Complex Material Responses S. Jafarzadeh Stewart Silling Ning Liu Zhongqiang Zhang Yue Yu AI4CE 32 16 0 11 Jan 2024
Stacked networks improve physics-informed training: applications to neural networks and deep operator networks Amanda A. Howard Sarah H. Murphy Shady E. Ahmed P. Stinis AI4CE 58 17 0 11 Nov 2023
A Physics-Guided Bi-Fidelity Fourier-Featured Operator Learning Framework for Predicting Time Evolution of Drag and Lift Coefficients Amirhossein Mollaali Izzet Sahin Iqrar Raza Christian Moya Guillermo Paniagua Guang Lin 21 2 0 07 Nov 2023
Spectral operator learning for parametric PDEs without data reliance Junho Choi Taehyun Yun Namjung Kim Youngjoon Hong 27 8 0 03 Oct 2023
A peridynamic-informed deep learning model for brittle damage prediction Roozbeh Eghbalpoor A. Sheidaei AI4CE 27 4 0 02 Oct 2023
Evaluation of Deep Neural Operator Models toward Ocean Forecasting Ellery Rajagopal Anantha N.S. Babu Tony Ryu P. Haley C. Mirabito Pierre FJ Lermusiaux AI4Cl AI4CE 22 1 0 22 Aug 2023
Deep Neural Operator Driven Real Time Inference for Nuclear Systems to Enable Digital Twin Solutions Kazuma Kobayashi S. B. Alam AI4CE 15 13 0 15 Aug 2023
Sound propagation in realistic interactive 3D scenes with parameterized sources using deep neural operators N. Borrel-Jensen S. Goswami A. Engsig-Karup George Karniadakis C. Jeong AI4CE 41 16 0 09 Aug 2023
Introducing Hybrid Modeling with Time-series-Transformers: A Comparative Study of Series and Parallel Approach in Batch Crystallization Niranjan Sitapure J. Kwon 35 33 0 25 Jul 2023
Tackling the Curse of Dimensionality with Physics-Informed Neural Networks Zheyuan Hu K. Shukla George Karniadakis Kenji Kawaguchi PINN AI4CE 65 88 0 23 Jul 2023
Data-Driven Design for Metamaterials and Multiscale Systems: A Review Doksoo Lee Wei Chen Liwei Wang Yu-Chin Chan Wei Chen AI4CE 27 80 0 01 Jul 2023
CrystalGPT: Enhancing system-to-system transferability in crystallization prediction and control using time-series-transformers Niranjan Sitapure J. Kwon 26 51 0 31 May 2023
A Generative Modeling Framework for Inferring Families of Biomechanical Constitutive Laws in Data-Sparse Regimes Minglang Yin Zongren Zou Enrui Zhang C. Cavinato J. Humphrey George Karniadakis SyDa MedIm AI4CE 53 11 0 04 May 2023
A Bi-fidelity DeepONet Approach for Modeling Uncertain and Degrading Hysteretic Systems Subhayan De P. Brewick 31 0 0 25 Apr 2023
Fourier Neural Operator Surrogate Model to Predict 3D Seismic Waves Propagation F. Lehmann F. Gatti M. Bertin Didier Clouteau AI4CE 31 24 0 20 Apr 2023
Variational operator learning: A unified paradigm marrying training neural operators and solving partial differential equations Tengfei Xu Dachuan Liu Peng Hao Bo Wang 42 4 0 09 Apr 2023
Fourier-MIONet: Fourier-enhanced multiple-input neural operators for multiphase modeling of geological carbon sequestration Zhongyi Jiang Min Zhu Dongzhuo Li Qiuzi Li Yanhua O. Yuan Lu Lu AI4CE 46 50 0 08 Mar 2023
Neural Operator Learning for Long-Time Integration in Dynamical Systems with Recurrent Neural Networks K. Michałowska S. Goswami George Karniadakis S. Riemer-Sørensen AI4CE 15 15 0 03 Mar 2023
Mixed formulation of physics-informed neural networks for thermo-mechanically coupled systems and heterogeneous domains Ali Harandi Ahmad Moeineddin Michael Kaliske Stefanie Reese Shahed Rezaei AI4CE PINN 25 42 0 09 Feb 2023
A neural operator-based surrogate solver for free-form electromagnetic inverse design Yannick Augenstein T. Repän C. Rockstuhl AI4CE 30 28 0 04 Feb 2023
An Enhanced V-cycle MgNet Model for Operator Learning in Numerical Partial Differential Equations Jianqing Zhu Juncai He Qiumei Huang 35 4 0 02 Feb 2023
A Hybrid Deep Neural Operator/Finite Element Method for Ice-Sheet Modeling Qizhi He M. Perego Amanda A. Howard George Karniadakis P. Stinis 17 18 0 26 Jan 2023
Reliable extrapolation of deep neural operators informed by physics or sparse observations Min Zhu Handi Zhang Anran Jiao George Karniadakis Lu Lu 50 91 0 13 Dec 2022
Deep Learning Methods for Partial Differential Equations and Related Parameter Identification Problems Derick Nganyu Tanyu Jianfeng Ning Tom Freudenberg Nick Heilenkötter A. Rademacher U. Iben Peter Maass AI4CE 23 34 0 06 Dec 2022
Physics Informed Neural Network for Dynamic Stress Prediction H. Bolandi Gautam Sreekumar Xuyang Li N. Lajnef Vishnu Boddeti AI4CE 12 23 0 28 Nov 2022
An unsupervised latent/output physics-informed convolutional-LSTM network for solving partial differential equations using peridynamic differential operator A. Mavi A. Bekar E. Haghighat E. Madenci 65 28 0 21 Oct 2022
Solving Coupled Differential Equation Groups Using PINO-CDE Wenhao Ding Qing He Hanghang Tong Qingjing Wang Ping Wang OOD AI4CE 27 4 0 01 Oct 2022
Variationally Mimetic Operator Networks Dhruv V. Patel Deep Ray M. Abdelmalik T. Hughes Assad A. Oberai 55 23 0 26 Sep 2022
DeepGraphONet: A Deep Graph Operator Network to Learn and Zero-shot Transfer the Dynamic Response of Networked Systems Yixuan Sun Christian Moya Guang Lin Meng Yue GNN 50 9 0 21 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 37 0 25 Aug 2022
G2Φnet: Relating Genotype and Biomechanical Phenotype of Tissues with Deep Learning Enrui Zhang B. Spronck J. Humphrey George Karniadakis AI4CE 36 9 0 21 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