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DRI-CALYPSO Supported Publications
2023
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Foucart, C., A. Charous, and P.F.J. Lermusiaux, 2023. Deep Reinforcement Learning for Adaptive Mesh Refinement. Journal of Computational Physics 491, 112381. doi:10.1016/j.jcp.2023.112381
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Aravind, H.M., V. Verma, S. Sarkar, M.A. Freilich, A. Mahadevan, P.J. Haley Jr., P.F.J. Lermusiaux, and M.R. Allshouse, 2023. Lagrangian Surface Signatures Reveal Upper-Ocean Vertical Displacement Conduits Near Oceanic Density Fronts. Ocean Modelling 181, 102136. doi:10.1016/j.ocemod.2022.102136
2022
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Ali, W.H., Y. Gao, C. Foucart, M. Doshi, C. Mirabito, P.J. Haley, and P.F.J. Lermusiaux, 2022. High-Performance Visualization for Ocean Modeling. In: OCEANS '22 IEEE/MTS Hampton Roads, 17–20 October 2022, pp. 1–10. doi:10.1109/OCEANS47191.2022.9977075
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Garcia-Jove, M., B. Mourre, N.D. Zarokanellos, P.F.J. Lermusiaux, D.L. Rudnick, J. Tintoré, 2022. Frontal Dynamics in the Alboran Sea: 2. Processes for Vertical Velocities Development. Journal of Geophysical Research: Oceans 127(3): e2021JC017428. doi:10.1029/2021JC017428
2019
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Lermusiaux, P.F.J., M. Doshi, C.S. Kulkarni, A. Gupta, P.J. Haley, Jr., C. Mirabito, F. Trotta, S.J. Levang, G.R. Flierl, J. Marshall, T. Peacock, and C. Noble, 2019. Plastic Pollution in the Coastal Oceans: Characterization and Modeling. In: OCEANS '19 MTS/IEEE Seattle, 27-31 October 2019, doi: 10.23919/OCEANS40490.2019.8962786
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Doshi, M.M., C.S. Kulkarni, W.H. Ali, A. Gupta, P.F.J. Lermusiaux, P. Zhan, I. Hoteit, and O.M. Knio, 2019. Flowmaps and Coherent Sets for Characterizing Residence Times and Connectivity in Lagoons and Coral Reefs: The Case of the Red Sea. In: OCEANS '19 MTS/IEEE Seattle, 27-31 October 2019, doi:10.23919/OCEANS40490.2019.8962643
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Ali, W.H., M.H. Mirhi, A. Gupta, C.S. Kulkarni, C. Foucart, M.M. Doshi, D.N. Subramani, C. Mirabito, P.J. Haley, Jr., and P.F.J. Lermusiaux, 2019. SeaVizKit: Interactive Maps for Ocean Visualization. In: OCEANS '19 MTS/IEEE Seattle, 27-31 October 2019, doi:10.23919/OCEANS40490.2019.8962794
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Kulkarni, C.S. and P.F.J. Lermusiaux, 2019. Advection without Compounding Errors through Flow Map Composition. Journal of Computational Physics, 398, 108859. doi:10.1016/j.jcp.2019.108859
MIT THESES
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Foucart, C., 2023. High-order Discontinuous Galerkin Methods and Deep Reinforcement Learning with Application to Multiscale Ocean Modeling. Ph.D. Thesis, Massachusetts Institute of Technology, Department of Mechanical Engineering and Center for Computational Science and Engineering, September 2023.
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Saravanakumar, A.K., 2023. Towards Coupled Nonhydrostatic-Hydrostatic Hybridizable Discontinuous Galerkin Method. SM Thesis, Massachusetts Institute of Technology, Center for Computational Science and Engineering, June 2023.
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Gkirgkis, K.A., 2021. Stochastic Ocean Forecasting with the Dynamically Orthogonal Primitive Equations. SM Thesis, Massachusetts Institute of Technology, Mechanical Engineering, June 2021.
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Kulkarni, C.S., 2021. Prediction, Analysis, and Learning of Advective Transport in Dynamic Fluid Flows. PhD Thesis, Massachusetts Institute of Technology, Department of Mechanical Engineering and Center for Computational Science and Engineering, February 2021.
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Doshi, M., 2021. Energy-Time Optimal Path Planning in Strong Dynamic Flows. SM Thesis, Massachusetts Institute of Technology, Center for Computational Science and Engineering, February 2021.
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Foucart, C., 2019. Efficient Matrix-Free Implementation and Automated Verification of Hybridizable Discontinuous Galerkin Finite Element Methods. SM Thesis, Massachusetts Institute of Technology, Mechanical Engineering, June 2019.
