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IN-BDA Supported Publications
2024
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Charous, A. and P.F.J. Lermusiaux, 2024. Range-Dynamical Low-Rank Split-Step Fourier Method for the Parabolic Wave Equation. Journal of the Acoustical Society of America 156(4): 2903-2920. doi:10.1121/10.0032470
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Ali, W.H., and P.F.J. Lermusiaux, 2024b. Dynamically Orthogonal Narrow-Angle Parabolic Equations for Stochastic
Underwater Sound Propagation. Part II: Applications. Journal of the Acoustical Society of America 155(1), 656-672. doi:10.1121/10.0024474
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Ali, W.H., and P.F.J. Lermusiaux, 2024a. Dynamically Orthogonal Narrow-Angle Parabolic Equations for Stochastic Underwater Sound Propagation. Part I: Theory and Schemes. Journal of the Acoustical Society of America 155(1), 640-655. doi:10.1121/10.0024466
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Charous, A. and P.F.J. Lermusiaux, 2024. Stable Rank-adaptive Dynamically Orthogonal Runge-Kutta Schemes. SIAM Journal on Scientific Computing 46(1), A529-A560. doi:10.1137/22M1534948
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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
2023
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Gupta, A. and P.F.J. Lermusiaux, 2023. Bayesian Learning of Coupled Biogeochemical-Physical Models. Progress in Oceanography 216, 103050. doi:10.1016/j.pocean.2023.103050
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Charous, A. and P.F.J. Lermusiaux, 2023. Dynamically Orthogonal Runge–Kutta Schemes with Perturbative Retractions for the Dynamical Low-Rank Approximation. SIAM Journal on Scientific Computing 45(2): A872-A897. doi:10.1137/21M1431229
2022
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Humara, M.J., W.H. Ali, A. Charous, M. Bhabra, and P.F.J. Lermusiaux, 2022. Stochastic Acoustic Ray Tracing with Dynamically Orthogonal Differential Equations. In: OCEANS '22 IEEE/MTS Hampton Roads, 17–20 October 2022, pp. 1–10. doi:10.1109/OCEANS47191.2022.9977252
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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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Jana, S., A. Gangopadhyay, P.J. Haley, Jr., and P.F.J. Lermusiaux, 2022. Sound Speed Variability over Bay of Bengal from Argo Observations (2011-2020). In: OCEANS 2022 Chennai, February 21-24, 2022, pp. 1-8. doi:10.1109/OCEANSChennai45887.2022.9775509
2021
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Charous, A. and P.F.J. Lermusiaux, 2021. Dynamically Orthogonal Differential Equations for Stochastic and Deterministic Reduced-Order Modeling of Ocean Acoustic Wave Propagation. In: OCEANS '21 IEEE/MTS San Diego, 20-23 September 2021, pp. 1-7. doi:10.23919/OCEANS44145.2021.9705914
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Lu, P., and P.F.J. Lermusiaux, 2021. Bayesian Learning of Stochastic Dynamical Models. Physica D 427: 133003. doi:10.1016/j.physd.2021.133003
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Pan, Y., P.J. Haley, Jr., and P.F.J. Lermusiaux, 2021. Interactions of Internal Tides with a Heterogeneous and Rotational Ocean. Journal of Fluid Mechanics 920, A18. doi:10.1017/jfm.2021.423
2019
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Gupta, A., P.J. Haley, D.N. Subramani, and P.F.J. Lermusiaux, 2019. Fish Modeling and Bayesian Learning for the Lakshadweep Islands. In: OCEANS '19 MTS/IEEE Seattle, 27-31 October 2019, doi: 10.23919/OCEANS40490.2019.8962892
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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.S. Bhabra, P.F.J. Lermusiaux, A. March, J.R. Edwards, K. Rimpau, and P. Ryu, 2019. Stochastic Oceanographic-Acoustic Prediction and Bayesian Inversion for Wide Area Ocean Floor Mapping. In: OCEANS '19 MTS/IEEE Seattle, 27-31 October 2019, doi:10.23919/OCEANS40490.2019.8962870
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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
MIT THESES
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Doshi, M., 2024. High-Dimensional Optimal Path Planning and Multi-Timescale Lagrangian Data Assimilation in Stochastic Dynamical Ocean Environments. Ph.D. Thesis, Massachusetts Institute of Technology, Department of Mechanical Engineering, May 2024.
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Suresh Babu, A.N., 2023. Stochastic Sea Ice Modeling with the Dynamically Orthogonal Equations. SM Thesis, Massachusetts Institute of Technology, Mechanical Engineering, September 2023.
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Ali, W.H., 2023. Stochastic Dynamically Orthogonal Modeling and Bayesian Learning for Underwater Acoustic Propagation. 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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Charous, A., 2023. Dynamical Reduced-Order Models for High-Dimensional Systems. Ph.D. Thesis, Massachusetts Institute of Technology, Department of Mechanical Engineering and Center for Computational Science and Engineering, June 2023.
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Gupta, A., 2022. Scientific Machine Learning for Dynamical Systems: Theory and Applications to Fluid Flow and Ocean Ecosystem Modeling. Ph.D. Thesis, Massachusetts Institute of Technology, Department of Mechanical Engineering, September 2022.
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Bhabra, M.S., 2021. Harvest-Time Optimal Path Planning in Dynamic Flows. SM Thesis, Massachusetts Institute of Technology, Mechanical Engineering and Computational Science & Engineering, September 2021.
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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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Charous, A., 2021. High-Order Retractions for Reduced-Order Modeling and Uncertainty Quantification. SM Thesis, Massachusetts Institute of Technology, Computational Science and Engineering, February 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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Lin, J., 2020. Bayesian Learning for High-Dimensional Nonlinear Dynamical Systems: Methodologies, Numerics and Applications to Fluid Flows. PhD thesis, Massachusetts Institute of Technology, Department of Mechanical Engineering, September 2020.
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Humara, M.J., 2020. Stochastic Acoustic Ray Tracing with Dynamically Orthogonal Equations. SM Thesis, Massachusetts Institute of Technology, Joint Program in Applied Ocean Science and Engineering, May 2020.
