## Submitted manuscripts

B. Champenois, C. Bastidas, B. LaBash, T. Sapsis, Data-driven modeling of 4D ocean and coastal acidification from surface measurements (2024), Submitted. [pdf] | |

M. Wang, A. Souza, R. Ferrari, T. Sapsis, Stochastic emulators of spatially resolved extreme temperatures of earth system models (2024), Submitted. [pdf] | |

S. Stamatelopoulos, T. Sapsis, Can diffusion models predict extreme events? (2024), Submitted. [pdf] | |

B. Champenois, T. Sapsis, Likelihood-Weighted Active Selection of Training Data for Improved Extreme Weather Event Prediction in Climate Models (2024), Submitted. [pdf] | |

B. Barthel Sorensen, L. Zepeda-Núñez, I. Lopez-Gomez, Z. Y. Wan, R. Carver, F. Sha, T. P. Sapsis, A probabilistic framework for learning non-intrusive corrections to long-time climate simulations from short-time training data (2024), Submitted. [pdf] | |

Y. Psarellis, T. Sapsis, I. Kevrekidis, Active search for bifurcations (2024), Submitted. [pdf] | |

E. Katsidoniotaki, B. Su, E. Kelasidi, T. Sapsis, Multifidelity digital twin for real-time monitoring of structural dynamics in aquaculture net cages (2024), Submitted. [pdf] | |

D. Kim, T. Sapsis, Real-time lift forecast of a NACA0012 airfoil maneuvering randomly under dynamic stall conditions at Re~10^5 (2024), Submitted. [pdf] | |

E. Katsidoniotaki, S. Guth, M. Göteman, T. Sapsis, Reduced order modeling of wave energy systems via sequential Bayesian experimental design and machine learning (2024), Submitted, (40 pages) [pdf] |

## Published Journal Papers

2024 | E. Pickering, T. Sapsis, Information FOMO: The unhealthy fear of missing out on information. A method for removing misleading data for healthier models, Entropy, (2024), Accepted [pdf] |

M. Kim, K. O'Connor, V. Pipiras, T. Sapsis, Sampling low-fidelity outputs for estimation of high-fidelity density and its tails (2024), SIAM/ASA Journal of Uncertainty Quantification, Accepted (2024) [pdf] | |

S. Zhang, B. Harrop, R. Leung, A. Charalampopoulos, B. Barthel Sorensen, W. Xu, and T. Sapsis, A Machine Learning Bias Correction on Large‐Scale Environment of High‐Impact Weather Systems in E3SM Atmosphere Model, Journal of Advances in Modeling Earth Systems, 16, (2024) e2023MS004138 (34 pages) [pdf] | |

A. P. Mentzelopoulos, E. Prele, D. Fan, J. A. Ferrandis, T. Sapsis, M. S. Triantafyllou, Reconstructing flexible body vortex-induced vibrations using machine-vision and predicting the motions using semi-empirical models informed with transfer learned hydrodynamic coefficients, Journal of Fluid and Structures, 129 (2024) 104154 (13 pages) [pdf] | |

A. P. Mentzelopoulos, D. Fan; T. P. Sapsis, M. S. Triantafyllou, Variational autoencoders and transformers for multivariate time-series generative modelling and forecasting: applications to vortex-induced vibrations, Ocean Engineering Journal, 310 (2024) 118639 [pdf] | |

B. Barthel Sorensen, A. Charalampopoulos, S. Zhang, B. E. Harrop, L. R. Leung, and T. Sapsis, A non-intrusive machine learning framework for debiasing long-time coarse resolution climate simulations and quantifying rare events statistics, Journal of Advances in Modeling Earth Systems, 16 (2024) e2023MS004122 (29 pages) [pdf] [Featured by the MIT News] | |

J. Ferrandis, A. Mentzelopoulos, E. Ronglan, S. Rudy, D. Fan, T. Sapsis, M. Triantafyllou, Improving predictions of vortex induced vibrations via generalizable hydrodynamic databases across several current incidence angles, Journal of Fluids and Structures, 126 (2024) 104086 (21 pages) [pdf] | |

S. Guth, A. Mojahed, T. Sapsis, Quality measures for the evaluation of machine learning architectures on the quantification of epistemic and aleatoric uncertainties in complex dynamical systems, Computer Methods in Applied Mechanics and Engineering, 420 (2024) 116760 (22 pages) [pdf] | |

B. Champenois, T. Sapsis, Machine learning framework for the real-time reconstruction of regional 4D ocean temperature fields from historical reanalysis data and real-time satellite and buoy surface measurements, Physica D, 459 (2024) 134026 (14 pages) [pdf] | |

D. Glotzer, V. Pipiras, V. Belenky, K. Weems, T. Sapsis, Distributions and extreme value analysis of critical response rate and split-time metric in nonlinear oscillators with stochastic excitation, Journal of Ocean Engineering, 292 (2024) 116538 (12 pages). [pdf] | |

M. Levine, S. Edwards, D. Howard, K. Weems, T. Sapsis, V. Pipiras, Multi-fidelity data-adaptive autonomous seakeeping, Journal of Ocean Engineering, 292 (2024) 116322 (13 pages). [pdf] | |

V. Belenky, K. Weems, W.-M. Lin, V. Pipiras, T. Sapsis, Estimation of probability of capsizing with split-time method, Journal of Ocean Engineering, 292 (2024) 116452 (27 pages). [pdf] | |

S. Guth, E. Katsidoniotaki, T. Sapsis, Statistical modeling of fully nonlinear hydrodynamic loads on offshore wind turbine foundations using wave episodes and targeted CFD simulations through active sampling, Wind Energy, 27 (2024) 75-100. [pdf] | |

2023 | B. Campbell, V. Belenky, V. Pipiras, K. Weems, T. Sapsis, Estimation of probability of large roll angle with envelope peaks over threshold method, Journal of Ocean Engineering, 290 (2023), 116296 (16 pages) [pdf] |

B. Hammond, T. Sapsis, UUV autonomy and control near submarines using actively sampled surrogates, Journal of Ship Research, 67 (2023) 235-251. [pdf] | |

B. Hammond, T. Sapsis, Reduced order modeling of hydrodynamic interactions between a submarine and unmanned underwater vehicle using non-myopic multi-fidelity active learning, Journal of Ocean Engineering, 288 (2023) 116016. [pdf] | |

J. Zhang, L. Cammarata, C. Squires, T. P. Sapsis, and C. Uhler, Active learning for optimal intervention design in causal models, Nature Machine Intelligence, 5 (2023) 1066-1075. [pdf] | |

B. Barthel, T. Sapsis, Harnessing the instability mechanisms in airfoil flow for the data-driven forecasting of extreme events (2023), American Institute of Aeronautics and Astronautics (AIAA) Journal, 61 (2023). [pdf] | |

S. Rudy, T. Sapsis, Output-weighted and relative entropy loss functions for deep learning precursors of extreme events, Physica D, 443 (2023) 133570 (12 pages). [pdf] | |

A. Mentzelopoulos, J. Ferrandis, D. Fan, S. Rudy, T. Sapsis, M. Triantafyllou, Physics-based data-informed prediction of vertical, catenary, and stepped riser vortex induced vibrations, International Journal of Offshore and Polar Engineering, 33 (2023) 367–379. [pdf] | |

2022 | E. Pickering, S. Guth, G. Karniadakis, T. Sapsis, Discovering and forecasting extreme events via active learning in neural operators, Nature Computational Science, 2 (2022) 833-843. [pdf] |

A. Mentzelopoulos, J. Ferrandis, S. Rudy, T. Sapsis, M. Triantafyllou, D. Fan, Data-driven prediction and study of vortex induced vibrations by leveraging hydrodynamic coefficient databases learned from sparse sensors, Ocean Engineering Journal, 266 (2022) 112833. [pdf] | |

S. Guth, T. Sapsis, Wave episode based Gaussian process regression for extreme event statistics in ship dynamics: Between the Scylla of Karhunen-Loève convergence and the Charybdis of transient features, Ocean Engineering Journal, 266 (2022) 112633 (18 pages). [pdf] | |

T. Sapsis, A. Blanchard, Optimal criteria and their asymptotic form for data selection in data-driven reduced-order modeling with Gaussian process regression, Philosophical Transactions of the Royal Society A, 380 (2022) 20210197 (12 pages). [pdf] | |

A. Charalampopoulos, T. Sapsis, Uncertainty quantification of turbulent systems via physically consistent and data-informed reduced-order models, Physics of Fluids, 34 (2022) 075120. [pdf] | |

Y. Yang, A. Blanchard, T. Sapsis, P. Perdikaris, Output-weighted sampling for multi-armed bandits with extreme payoffs, Proceedings of the Royal Society A, 478 (2022) 20210781 (17 pages). [code] [pdf] | |

S. Rudy, D. Fan, J. Ferrandis, T. Sapsis, M. Triantafyllou, Optimized parametric hydrodynamic databases provide accurate response predictions and describe the physics of vortex-induced vibrations, Journal of Fluids and Structures, 112 (2022) 103607.[pdf] | |

D. Eeltink, H. Branger, C. Luneau, Y. He, A. Chabchoub, J. Kasparian, T. S. van den Bremer, T. Sapsis, Nonlinear wave evolution with data-driven breaking, Nature Communications 13 (2022) 2343. [pdf] | |

S. Rudy, T. Sapsis, Prediction of intermittent fluctuations from surface pressure measurements on a turbulent airfoil, American Institute of Aeronautics and Astronautics (AIAA) Journal, 60 (2022) 4174-4190.[pdf] | |

J. E. Chen, T. Theurich, M. Krack, T. Sapsis, L. A. Bergman, A. F. Vakakis, Intense cross-scale energy cascades resembling “mechanical turbulence” in harmonically driven strongly nonlinear hierarchical chains of oscillators, Acta Mechanica, 233 (2022) 1289-1305. [pdf] | |

A. Charalampopoulos, S. H. Bryngelson, T. Colonius, T. Sapsis, Hybrid quadrature moment method for accurate and stable representation of non-Gaussian processes applied to bubble dynamics, Phil. Trans. Royal Soc. A, 380 (2022) 20210209 (19 pages). [pdf] | |

H. Arbabi, T. Sapsis, Generative stochastic modeling of strongly nonlinear flows with non-Gaussian statistics, SIAM/ASA Journal of Uncertainty Quantification, 10 (2022) 555-583. [code][pdf] | |

S. Atis, M. Leclair, T. Sapsis, T. Peacock, Anisotropic particles focusing effect in complex flows, Physical Review Fluids, 7 (2022) 084503 (12 pages). [pdf] | |

A. Charalampopoulos, T. Sapsis, Machine-learning energy-preserving nonlocal closures for turbulent fluid flows and inertial tracers, Physical Review Fluids, 7 (2022) 024305 (24 pages). [pdf] | |

A. Blanchard, T. Sapsis, Informative path planning for anomaly detection in environment exploration and monitoring, Ocean Engineering, (2022) 43 110242 (10 pages). [pdf] | |

A. Blanchard, G. C. Maceda, D. Fan, Y. Li, Y. Zhou, B. Noack, T. Sapsis, Bayesian optimization for active flow control, Acta Mechanica Sinica, 37 (2022) 1786-1798. [pdf] | |

2021 | S. Guth, T. Sapsis, Probabilistic characterization of the effect of transient stochastic loads on the fatigue-crack nucleation time, Probabilistic Engineering Mechanics, 66 (2021) 103162 (11 pages). [Code][pdf] |

Z. Wan, B. Dodov, C. Lessig, H. Dijkstra, T. Sapsis, A data-driven framework for the stochastic reconstruction of small-scale features with application to climate data sets, Journal of Computational Physics, 442 (2021) 110484 (24 pages). [movie] [pdf] | |

A. Blanchard, T. Sapsis, Output-weighted optimal sampling for Bayesian experimental design and rare-event quantification, SIAM/ASA Journal of Uncertainty Quantification, 9 (2021) 564-592. [code][pdf] | |

T. Sapsis, Statistics of extreme events in fluid flows and waves, Annual Review of Fluid Mechanics, 53 (2021) 85-111. [free access pdf] | |

A. Blanchard, T. Sapsis, Bayesian optimization with output-weighted optimal sampling, Journal of Computational Physics, 425 (2021) 109901 (16 pages). [code][pdf] | |

S. Rudy, T. Sapsis, Sparse methods for automatic relevance determination, Physica D, 418 (2021) 132843 (16 pages). [code] [pdf] | |

2020 | T. Sapsis, Output-weighted optimal sampling for Bayesian regression and rare event statistics using few samples, Proceedings of the Royal Society A, 476 (2020) 20190834 (24 pages). [pdf] |

Z. Y. Wan, P. Karnakov, P. Koumoutsakos, T. Sapsis, Bubbles in turbulent flows: Data-driven, kinematic models with history terms, International Journal of Multiphase Flows, 129 (2020) 103286 (11 pages). [pdf] | |

S. Bryngelson, A. Charalampopoulos, T. Sapsis, T. Colonius, A Gaussian moment method and its augmentation via LSTM recurrent neural networks for the statistics of cavitating bubble populations, International Journal of Multiphase Flows, 127 (2020) 103262 (8 pages). [pdf] | |

P. Vlachas, J. Pathak, B. R. Hunt, T. Sapsis, M. Girvan, E. Ott, P. Koumoutsakos, Forecasting of spatio-temporal chaotic dynamics with recurrent neural networks: a comparative study of reservoir computing and backpropagation algorithms, Neural Networks, 126 (2020) 191-217. [pdf] | |

A. Athanassoulis, G. Athanassoulis, M. Ptashnyk, T. Sapsis, Strong solutions for the Alber equation and stability of unidirectional wave spectra, Kinetic and Related Models, 13 (2020) 703-737. [pdf] | |

N. Aksamit, T. Sapsis, G. Haller, Machine-learning ocean dynamics from Lagrangian drifter trajectories, Journal of Physical Oceanography, 50 (2020) 1179-1196. [pdf] | |

2019 | A. Blanchard, T. Sapsis, Learning the tangent space of dynamical instabilities from data, Chaos, 29 (2019) 113120, Focus Issue: When Machine Learning Meets Complex Systems: Networks, Chaos and Nonlinear Dynamics, (2019) (15 pages). [pdf] |

S. Guth, T. Sapsis, Machine learning predictors of extreme events occurring in complex dynamical systems, Entropy, 21 (2019) 925 (18 pages). [Code][pdf] | |

M. Farazmand, T. Sapsis, Closed-loop adaptive control of extreme events in a turbulent flow, Physical Review E, 100 (2019) 033110 (7 pages). [pdf] | |

A. Blanchard, T. Sapsis, Stabilization of unsteady flows by reduced-order control with optimally time-dependent modes, Physical Review Fluids, 4 (2019) 053902 (27 pages). Editor’s Suggestion. [pdf] | |

V. Belenky, D. Glotzer, V. Pipiras, T. Sapsis, Distribution tail structure and extreme value analysis of constrained piecewise linear oscillators, Probabilistic Engineering Mechanics, 57 (2019) 1-13.[pdf] | |

A. Blanchard, T. Sapsis, Analytical description of optimally time-dependent modes for reduced-order modeling of transient instabilities, SIAM Journal on Applied Dynamical Systems, 18 (2019) 1143-1162. [pdf] | |

P. Blonigan, M. Farazmand, T. Sapsis, Are extreme dissipation events predictable in turbulent fluid flows?, Physical Review Fluids, 4 (2019) 044606 (21 pages). [pdf] | |

M. Farazmand, T. Sapsis, Surface waves enhance particle dispersion, Fluids, 4 (2019) (12 pages). [pdf] | |

W. Cousins, M. Onorato, A. Chabchoub, T. Sapsis, Predicting ocean rogue waves from point measurements: an experimental study, Physical Review E, 99 (2019) 032201 (9 pages). [pdf] | |

A. Blanchard, S. Mowlavi, T. Sapsis, Control of linear instabilities by dynamically consistent order reduction on optimally time-dependent modes, Nonlinear Dynamics, 95 (2019) 2745-2764. [pdf] | |

M. Farazmand, T. Sapsis, Extreme events: mechanisms and prediction, ASME Applied Mechanics Reviews, 71 (2019) 050801. Received the Lloyd Hamilton Donnell Best Paper Award for 2020. [pdf] | |

2018 | M. Mohamad, T. Sapsis, A sequential sampling strategy for extreme event statistics in nonlinear dynamical systems, Proceedings of the National Academy of Sciences, 115 (2018) 11138-11143. [open access link], [supporting information], Featured on the MIT News. |

Z. Y. Wan, T. Sapsis, Machine learning the kinematics of spherical particles in fluid flows, Journal of Fluid Mechanics, 857 (2018) R2 (11 pages). [Code][pdf] | |

T. Sapsis, New perspectives for the prediction and statistical quantification of extreme events in high-dimensional dynamical systems, Philosophical Transactions of the Royal Society A, 376 (2018) 20170133 (18 pages). [pdf] | |

Z. Y. Wan, P. Vlachas, P. Koumoutsakos, T. Sapsis, Data-assisted reduced-order modeling of extreme events in complex dynamical systems, PLOS One, 24 May (2018) (22 pages). [pdf] | |

P. Vlachas, W. Byeon, Z. Y. Wan, T. Sapsis, P. Koumoutsakos, Data-driven forecasting of high-dimensional chaotic systems with long-short term memory networks, Proceedings of the Royal Society A, 474 (2018) 20170844 (20 pages). [pdf] | |

M. Haji, J. Kluger, T. Sapsis, A. Slocum, A symbiotic approach to the design of offshore wind turbines with other energy harvesting systems, Ocean Engineering Journal, 169 (2018) 673-681. [pdf] | |

M. Haji, J. Kluger, J. Carrus, T. Sapsis, A. Slocum, Experimental investigation of hydrodynamic response of an ocean uranium extraction machine attached to a floating wind turbine, International Journal of Offshore and Polar Engineering, 28 (2018) 225-231. [pdf] | |

S. Mowlavi, T. Sapsis, Model order reduction for stochastic dynamical systems with continuous symmetries, SIAM Journal on Scientific Computing, 40 (2018) 1669-1695. [pdf] | |

M. Farazmand, T. Sapsis, Physics-based probing and prediction of extreme events, SIAM News, 51 (2018) 1. [link] [pdf] | |

D. Baleanu, T. Kalmar-Nagy, T. Sapsis, H. Yabano, Editorial for special issue on Nonlinear Dynamics: Models, Behavior, and Techniques, ASME Journal of Computational and Nolinear Dynamics, 13 (2018) 090301 (2 pages). [pdf] | |

H. -K. Joo, M. Mohamad, T. Sapsis, Heavy-tailed response of structural systems subjected to extreme forcing events, ASME Journal of Computational and Nonlinear Dynamics, 13 (2018) 090914 (12 pages). [pdf] | |

A. Blanchard, T. Sapsis, A. Vakakis, Non-reciprocity in nonlinear elastodynamics, Journal of Sound and Vibration, 412 (2018) 326-335. [pdf] | |

2017 | M. Farazmand, T. Sapsis, A variational approach to probing extreme events in turbulent dynamical systems, Science Advances, 3:e1701533 (2017) (7 pages). [pdf] |

A. Athanassoulis, G. Athanassoulis, T. Sapsis, Localized instabilities of the Wigner equation as a model for the emergence of rogue Waves, J. Ocean Eng. Mar. Energy, 3 (2017) 353-372. [pdf] | |

H. -K. Joo, M. Mohamad, T. Sapsis, Extreme events and their optimal mitigation in nonlinear structural systems excited by stochastic loads: Application to ocean engineering systems, Ocean Engineering Journal, 142 (2017) 145-160. [pdf] | |

H. Babaee, M. Farazmand, G. Haller, T. Sapsis, Reduced-order description of transient instabilities and computation of finite-time Lyapunov exponents, Chaos, 27 (2017) 063103 (12 pages). [pdf] | |

J.M. Kluger, A.H. Slocum, and T. Sapsis, Ring-based stiffening flexure applied as a load cell with high resolution and large force range, ASME Journal of Mechanical Design, 139 (2017) 103501 (8 pages). [pdf] | |

M. Farazmand, T. Sapsis, Reduced-order prediction of rogue waves in two dimensional water waves, Journal of Computational Physics, 340 (2017) 418-434. [pdf] | |

Z. Y. Wan, T. Sapsis, Reduced-space Gaussian process regression for data-driven probabilistic forecast of chaotic dynamical systems, Physica D, 345 (2017) 40-55. [pdf] | |

H. Babaee, M. Choi, T. Sapsis, G. Karniadakis, A robust bi-orthogonal/dynamically-orthogonal method using the covariance pseudo-inverse with application to stochastic flow problems, Journal of Computational Physics, 344 (2017) 303-319. [pdf]. | |

O. Gendelman, T. Sapsis, Energy exchange and localization in essentially nonlinear oscillatory systems: Canonical formalism, ASME Journal of Applied Mechanics, 84 (2017) 011009 (9 pages). [pdf] | |

2016 | M. Farazmand, T. Sapsis, Dynamical indicators for the prediction of bursting phenomena in high-dimensional systems, Physical Review E, 94 (2016) 032212 (15 pages). [pdf] Featured on the Physical Review E: Kaleidoscope. |

M. Mohamad, W. Cousins, T. Sapsis, A probabilistic decomposition-synthesis method for the quantification of rare events due to internal instabilities, Journal of Computational Physics, 322 (2016) 288-308. [pdf] | |

M. Mohamad, T. Sapsis, Probabilistic response and rare events in Mathieu’s equation under correlated parametric excitation, Ocean Engineering Journal,120 (2016) 289-297. [pdf] | |

H. Babaee, T. Sapsis, A minimization principle for the description of time-dependent modes associated with transient instabilities, Proceedings of the Royal Society A, 472 (2016) 20150779 (27 pages). [pdf] Featured on the journal's cover page. | |

W. Cousins, T. Sapsis, Reduced order precursors of rare events in unidirectional nonlinear water waves, Journal of Fluid Mechanics, 790 (2016) 368-388. [pdf] Featured as MIT spotlight. Reported by The Economist. | |

H. -K. Joo, T. Sapsis, A moment-equation-copula-closure method for nonlinear vibrational systems subjected to correlated noise, Probabilistic Engineering Mechanics, 46 (2016) 120-132. [pdf] | |

J. Kluger, T. Sapsis, A. Slocum, A high-resolution and large force-range load cell by means of nonlinear cantilever beams, Precision Engineering, 43 (2016) 241-256. [pdf] | |

2015 | M. Mohamad, T. Sapsis, Probabilistic description of extreme events in intermittently unstable dynamical systems excited by correlated stochastic processes, SIAM/ASA Journal on Uncertainty Quantification, 3 (2015) 709-736. [pdf] |

W. Cousins, T. Sapsis, The unsteady evolution of localized unidirectional deep water wave groups, Physical Review E, 91 (2015) 063204 (5 pages). [pdf] | |

J. Kluger, T. Sapsis, A. Slocum, Robust energy harvesting from walking vibrations by means of nonlinear cantilever beams, Journal of Sound and Vibration, 341 (2015) 174-194. [pdf] | |

H. -K. Joo, T. Sapsis, Closure schemes for nonlinear bistable systems subjected to correlated Noise: Applications to energy harvesting from water waves, Journal of Ocean and Wind Energy, 2 (2015) 65-72. [pdf] | |

A. Petsakou, T. Sapsis, J. Blau, Circadian rhythms in Rho1 activity regulate neuronal plasticity and network hierarchy, Cell, 162 (2015) 1-13. [pdf] | |

2014 | A. Majda, D. Qi, T. Sapsis, Blended particle filters for large dimensional chaotic dynamical systems, Proceedings of the National Academy of Sciences, 111 (2014) 7511-7516. [pdf] |

W. Cousins, T. Sapsis, Quantification and prediction of extreme events in a one-dimensional nonlinear dispersive wave model, Physica D, 280-281 (2014) 48-58. [pdf] | |

H.-K. Joo, T. Sapsis, Performance measures for single-degree-of-freedom energy harvesters under stochastic excitation, Journal of Sound and Vibration, 313 (2014) 4695-4710. [pdf] | |

M. Choi, T. Sapsis, G. E. Karniadakis, On the equivalence of dynamically orthogonal and dynamically bi-orthogonal methods: Theory and numerical simulations, Journal of Computational Physics, 270 (2014) 1-20. [pdf] | |

K. Remick, H.-K. Joo, D.M. McFarland, T. Sapsis, L. Bergman, D.D. Quinn, A. Vakakis, Sustained high-frequency energy harvesting through a strongly nonlinear electromechanical system under single and repeated impulsive excitations, Journal of Sound and Vibration, 333 (2014) 3214-3235. [pdf] | |

K. Remick, A. Vakakis, L. Bergman, D. M. McFarland, D. D. Quinn, T. Sapsis, Sustained high-frequency dynamic instability of a nonlinear system of coupled oscillators forced by single or repeated impulses: Theoretical and experimental results, ASME Journal of Vibration & Acoustics, 136 (2014) 011013 (15 pages). [pdf] | |

2013 | T. Sapsis, A. Majda, Statistically accurate low order models for uncertainty quantification in turbulent dynamical systems, Proceedings of the National Academy of Sciences, 110 (2013) 13705-13710.[pdf] |

T. Sapsis, A. Majda, Blending modified Gaussian closure and non-Gaussian reduced subspace methods for turbulent dynamical systems, Journal of Nonlinear Science, 23 (2013) 1039 (33 pages). [pdf] | |

T. Sapsis, A. Majda, Blended reduced subspace algorithms for uncertainty quantification of quadratic systems with a stable mean state, Physica D, 258 (2013) 61-76. [pdf] | |

T. Sapsis, Attractor local dimensionality, nonlinear energy transfers, and finite-time instabilities in stochastic dynamical systems with applications to 2D fluid flows, Proceedings of the Royal Society A, 469 (2013) 20120550 (23 pages). [pdf] | |

T. Sapsis, A. Majda, A statistically accurate modified quasilinar Gaussian closure for uncertainty quantification in turbulent dynamical systems, Physica D, 252 (2013) 34-45. [pdf] | |

T. Sapsis, and H. A. Dijkstra, Interaction of additive noise and nonlinear dynamics in the double-gyre wind-driven ocean circulation, Journal of Physical Oceanography, 43 (2013) 366-381. [pdf] | |

T. Sapsis, M. Ueckermann, P. Lermusiaux, Global analysis of Navier-Stokes and Boussinesq stochastic flows using dynamical orthogonality, Journal of Fluid Mechanics, 734 (2013) 83-113. [pdf] | |

M. Choi, T. Sapsis, G. E. Karniadakis, A convergence study for SPDEs using combined polynomial chaos and dynamically-orthogonal schemes, Journal of Computational Physics, 245 (2013) 281-301. [pdf] | |

M. Ueckermann, P. Lermusiaux, T. Sapsis, Numerical schemes for dynamically orthogonal equations of stochastic fluid and ocean flows, Journal of Computational Physics, 233 (2013) 272-294. [pdf] | |

2012 | D. Venturi, T. Sapsis, H. Cho, and G. E. Karniadakis, A computable evolution equation for the joint response-excitation probability density function of stochastic dynamical systems, Proceedings of the Royal Society A, 468 (2012) 759 (25 pages). [pdf] |

T. Sapsis & P. Lermusiaux, Dynamical criteria for the evolution of the stochastic dimensionality in flows with uncertainty, Physica D, 241 (2012) 60-76. [pdf] | |

2011 | T. Sapsis, A. Vakakis, & L. Bergman, Effect of stochasticity on targeted energy transfer from a linear medium to a strongly nonlinear attachment, Probabilistic Engineering Mechanics, 26 (2011) 119-133. [pdf] |

T. Sapsis, N. Ouellette, J. Gollub, & G. Haller, Neutrally buoyant particle dynamics in fluid flows: Comparison of Experiments with Lagrangian stochastic models, Physics of Fluids, 23 (2011) 093304 (15 pages). [pdf] | |

G. Haller, T. Sapsis, Lagrangian coherent structures and the smallest finite-time Lyapunov exponent, Chaos, 21 (2011) 023115 (7 pages). [pdf] | |

T. Sapsis, J. Peng, & G. Haller, Instabilities on prey dynamics in jellyfish feeding, Bulletin of Mathematical Biology, 73 (2011) 1841-1856. [pdf] | |

T. Sapsis, A. Vakakis, & L. Bergman, Effect of stochasticity on targeted energy transfer from a linear medium to a strongly nonlinear attachment, Probabilistic Engineering Mechanics, 26 (2011) 119-133. [pdf] | |

O. Gendelman, T. Sapsis, A. Vakakis, L. Bergman, Enhanced passive targeted energy transfer in strongly nonlinear mechanical oscillators, Journal of Sound and Vibration, 330 (2011) 1-8. [pdf] | |

T. Sapsis & A. Vakakis, Subharmonic orbits of a strongly nonlinear oscillator forced by closely spaced harmonics, Journal of Computational and Nonlinear Dynamics, 6 (2011) 011014 (10 pages). [pdf] | |

2010 | T. Sapsis & G. Haller, Clustering criterion for inertial particles in 2D time-periodic and 3D steady flows, Chaos, 20 (2010) 017515 (11 pages). [pdf] |

G. Haller & T. Sapsis, Localized instability and attraction along invariant manifolds, SIAM Journal of Applied Dynamical Systems, 9 (2010) 611-633. [pdf] | |

2009 | T. Sapsis & P. Lermusiaux, Dynamically orthogonal field equations for continuous stochastic dynamical systems, Physica D, 238 (2009) 2347-2360. [pdf] |

T. Sapsis & G. Haller, Inertial particle dynamics in a hurricane, Journal of the Atmospheric Sciences, 66 (2009) 2481-2492. [pdf] | |

T. Sapsis, A. Vakakis, O. Gendelman, L. Bergman, G. Kerschen, & D. Quinn. Efficiency of targeted energy transfers in coupled nonlinear oscillators associated with 1:1 resonance captures: Part II, analytical study, Journal of Sound and Vibration, 325 (2009) 297-320. [pdf] | |

2008 | T. Sapsis & G. Haller, Instabilities in the dynamics of neutrally buoyant particles, Physics of Fluids, 20 (2008) 017102 (7 pages). [pdf] |

G. Haller, T. Sapsis, Where do inertial particles go in fluid flows?, Physica D, 237 (2008) 573-583. [pdf] | |

D. Quinn, O. Gendelman, G. Kerschen, T. Sapsis, L. Bergman, & A. Vakakis. Efficiency of targeted energy transfers in coupled nonlinear oscillators associated with 1:1 resonance aaptures: Part I, Journal of Sound and Vibration, 311 (2008) 1228-1248. [pdf] | |

T. Sapsis & G. Athanassoulis, New partial differential equations governing the response-excitation joint probability distributions of nonlinear systems under general stochastic excitation, Probabilistic Engineering Mechanics, 23 (2008) 289-306. [pdf] |