## Submitted manuscripts

B. Barthel, T. Sapsis, Harnessing the instability mechanisms in airfoil flow for the data-driven forecasting of extreme events (2023), Submitted, (41 pages) [pdf] | |

B. Hammond, T. Sapsis, UUV autonomy and control near submarines using actively sampled surrogates (2023), Submitted, (16 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 (2023), Submitted, (36 pages) [pdf] | |

E. Pickering, T. Sapsis, Information FOMO: The unhealthy fear of missing out on information. A method for removing misleading data for healthier models, Submitted, (2023) (14 pages) [pdf] | |

B. Champenois, T. Sapsis, Real-time reconstruction of 3D ocean temperature fields from reanalysis data and satellite and buoy surface measurements, Submitted (2023) [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, Submitted, (2023) (27 pages) [pdf] | |

J. Zhang, L. Cammarata, C. Squires, T. P. Sapsis, and C. Uhler, Active learning for optimal intervention design in causal models, Submitted, (2022) (44 pages) [pdf] |

## Published Journal Papers

2023 | 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, Data-driven prediction of flexible cylinder vortex induced vibrations using limited sensor measurements, International Journal of Offshore and Polar Engineering, (2023) In Press (7 pages). [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, (2021) 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] |