Fourier-MIONet: Fourier-enhanced multiple-input neural operators for multiphase modeling of geological carbon sequestration
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DOI: 10.1016/j.ress.2024.110392
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- Alireza Yazdani & Lu Lu & Maziar Raissi & George Em Karniadakis, 2020. "Systems biology informed deep learning for inferring parameters and hidden dynamics," PLOS Computational Biology, Public Library of Science, vol. 16(11), pages 1-19, November.
- Rehme, Michael F. & Franzelin, Fabian & Pflüger, Dirk, 2021. "B-splines on sparse grids for surrogates in uncertainty quantification," Reliability Engineering and System Safety, Elsevier, vol. 209(C).
- Shujie Ma & Peter X.-K. Song, 2015. "Varying Index Coefficient Models," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 110(509), pages 341-356, March.
- Kröker, Ilja & Oladyshkin, Sergey, 2022. "Arbitrary multi-resolution multi-wavelet-based polynomial chaos expansion for data-driven uncertainty quantification," Reliability Engineering and System Safety, Elsevier, vol. 222(C).
- Kandel, Rajesh & Baroud, Hiba, 2024. "A data-driven risk assessment of Arctic maritime incidents: Using machine learning to predict incident types and identify risk factors," Reliability Engineering and System Safety, Elsevier, vol. 243(C).
- Fan, Shiqi & Yang, Zaili, 2024. "Accident data-driven human fatigue analysis in maritime transport using machine learning," Reliability Engineering and System Safety, Elsevier, vol. 241(C).
- Das, Sourav & Tesfamariam, Solomon, 2024. "Reliability assessment of stochastic dynamical systems using physics informed neural network based PDEM," Reliability Engineering and System Safety, Elsevier, vol. 243(C).
- Wu, Hao & Xu, Yanwen & Liu, Zheng & Li, Yumeng & Wang, Pingfeng, 2023. "Adaptive machine learning with physics-based simulations for mean time to failure prediction of engineering systems," Reliability Engineering and System Safety, Elsevier, vol. 240(C).
- Song, Chaolin & Xiao, Rucheng & Zhang, Chi & Zhao, Xinwei & Sun, Bo, 2024. "Simulation-free reliability analysis with importance sampling-based adaptive training physics-informed neural networks: Method and application to chloride penetration," Reliability Engineering and System Safety, Elsevier, vol. 246(C).
- Liu, Yang & Wang, Dewei & Sun, Xiaodong & Liu, Yang & Dinh, Nam & Hu, Rui, 2021. "Uncertainty quantification for Multiphase-CFD simulations of bubbly flows: a machine learning-based Bayesian approach supported by high-resolution experiments," Reliability Engineering and System Safety, Elsevier, vol. 212(C).
- Benjamin Fan & Edward Qiao & Anran Jiao & Zhouzhou Gu & Wenhao Li & Lu Lu, 2023. "Deep Learning for Solving and Estimating Dynamic Macro-Finance Models," Papers 2305.09783, arXiv.org.
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Keywords
Geological carbon sequestration; Multiphase flow in porous media; Deep neural operator; Fourier-MIONet; Computational cost; Out-of-distribution;All these keywords.
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