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NSF-ALPHA Supported Publications
2024
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Kulkarni, C.S. and P.F.J. Lermusiaux, 2024. Persistent Lagrangian Material Coherence in Fluid and Ocean Flows Using Flow Map Composition. Ocean Modelling, sub-judice.
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Feppon, F. and P.F.J. Lermusiaux, 2024. Rigid Sets and Coherent Sets in Realistic Ocean Flows. Nonlinear Processes in Geophysics, sub-judice. doi:10.5194/npg-2022-1
2020
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Lermusiaux, P.F.J., C. Mirabito, P.J. Haley, Jr., W.H. Ali, A. Gupta, S. Jana, E. Dorfman, A. Laferriere, A. Kofford, G. Shepard, M. Goldsmith, K. Heaney, E. Coelho, J. Boyle, J. Murray, L. Freitag, and A. Morozov, 2020. Real-time Probabilistic Coupled Ocean Physics-Acoustics Forecasting and Data Assimilation for Underwater GPS. In: OCEANS '20 IEEE/MTS, 5-30 October 2020, pp. 1-9. doi:10.1109/IEEECONF38699.2020.9389003
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Serra, M., P. Sathe, I. Rypina, A. Kirincich, S.D. Ross, P.F.J. Lermusiaux, A. Allen, T. Peacock, and G. Haller, 2020. Search and Rescue at Sea Aided by Hidden Flow Structures. Nature Communications 11, 1-7. doi:10.1038/s41467-020-16281-x
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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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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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.
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Mirhi, M., 2019. Design of Interactive Maps for Ocean Dynamics Data. ME thesis, Massachusetts Institute of Technology, Department of Mechanical Engineering, February 2019.
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Dutt, A., 2018. High Order Stochastic Transport and Lagrangian Data Assimilation. SM Thesis, Massachusetts Institute of Technology, Department of Mechanical Engineering, February 2018.
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Feppon, F., 2017. Riemannian Geometry of Matrix Manifolds for Lagrangian Uncertainty Quantification of Stochastic Fluid Flows. SM Thesis, Massachusetts Institute of Technology, Center for Computational Engineering, February 2017.
