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- Sun, R., Pan, H., Xiong, H. ., & Tchelepi, H. (2023). Physical-informed deep learning framework for CO2-injected EOR compositional simulation. Engineering Applications of Artificial Intelligence, 126. https://doi.org/10.1016/j.engappai.2023.106742
- Jiang, J. ., Tomin, P. ., & Tchelepi, H. (2023). Accelerated Nonlinear Domain Decomposition Solver for Multi-phase Flow and Transport in Porous Media. Journal of Computational Physics, 112328. https://doi.org/doi.org/10.1016/j.jcp.2023.112328
- N’diaye, M., Hamon, F., & Tchelepi, H. (2023). Comparison of nonlinear field-split preconditioners for two-phase flow in heterogeneous porous media. Computational Geosciences. https://doi.org/10.1007/s10596-023-10200-x
- Kim, Y., & Durlofsky, L. (2023). Convolutional – recurrent neural network proxy for robust optimization and closed-loop reservoir management. Computational Geosciences. https://doi.org/10.1007/s10596-022-10189-9
- Nasir, Y., & Durlofsky, L. (2023). Deep reinforcement learning for optimal well control in subsurface systems with uncertain geology. Journal of Computational Physics. https://doi.org/10.1016/j.jcp.2023.111945
- Weiyu, L., Hamdi, T., & Daniel, T. (2023). Screening of Electrolyte-Anode Buffers to Suppress Lithium Dendrite Growth in All-Solid-State Batteries. IOP Science. https://iopscience.iop.org/article/10.1149/1945-7111/acd0da/meta
- Li, J., Tomin, P., & Tchelepi, H. (2023). Sequential fully implicit newton method for flow and transport with natural black-oil formulation. Computational Geosciences. https://doi.org/10.1007/s10596-022-10186-y
- Jiang, S., & Durlofsky, L. (2023). Use of multifidelity training data and transfer learning for efficient construction of subsurface flow surrogate models. Journal of Computational Physics. https://doi.org/10.1016/j.jcp.2022.111800
- Shovkun, I., & Tchelepi, H. (2022). A Cut-Cell Polyhedral Finite Element Model for Coupled Fluid Flow and Mechanics in Fractured Reservoirs. SPE Journal. https://doi.org/10.2118/203958-PA
- Deucher, R., & Durlofsky, L. (2022). A New Flow-Kinematics-Based Model for Time-Dependent Effective Dispersion in Mixing-Limited Reactions. Water Resources Research. https://doi.org/10.1029/2022WR032156
- Nasir, Y., Volkov, O., & Durlofsky, L. (2022). A two-stage optimization strategy for large-scale oil field development. Optimization and Engineering. https://doi.org/10.1007/s11081-020-09591-y
- Nasir, Y., Volkov, O., & Durlofsky, L. (2022). A two-stage optimization strategy for large-scale oil field development. Optimization and Engineering. https://doi.org/10.1007/s11081-020-09591-y
- Karimi-Fard, M. (2022). An approximate cut-cell discretization technique for flow in fractured porous media. Computational Geosciences. https://doi.org/10.1007/s10596-022-10173-3
- Tang, M., Ju, X., & Durlofsky, L. (2022). Deep-learning-based coupled flow-geomechanics surrogate model for CO2 sequestration. International Journal of Greenhouse Gas Control. https://doi.org/10.1016/j.ijggc.2022.103692
- Zou, A., Ye, T., Volkov, O., & Durlofsky, L. (2022). Effective treatment of geometric constraints in derivative-free well placement optimization. Journal of Petroleum Science and Engineering. https://doi.org/10.1016/j.petrol.2022.110635
- Deucher, R., & Tchelepi, H. (2022). High resolution adaptive implicit method for reactive transport in heterogeneous porous media. Journal of Computational Physics. https://doi.org/10.1016/j.jcp.2022.111391
- Yang, H., Tchelepi, H., & Tartakovsky, D. (2022). Method of Distributions for Two-Phase Flow in Heterogeneous Porous Media. Water Resources Research. https://doi.org/10.1029/2022WR032607
- Ma, Z., Volkov, O., & Durlofsky, L. (2022). Multigroup strategy for well control optimization. Journal of Petroleum Science and Engineering. https://doi.org/10.1016/j.petrol.2022.110448
- Ma, Z., Kim, Y., Volkov, O., & Durlofsky, L. (2022). Optimization of Subsurface Flow Operations Using a Dynamic Proxy Strategy. Mathematical Geosciences. https://doi.org/10.1007/s11004-022-10020-2
- Franceschini, A., Castelletto, N., White, J., & Tchelepi, H. (2022). Scalable preconditioning for the stabilized contact mechanics problem. Journal of Computational Physics. https://doi.org/10.1016/j.jcp.2022.111150