# Journal Papers

**Click here to see journal papers organized by areas** OR search in the box below by topic (e.g. extreme events, turbulent systems, random vibrations, data driven methods, uncertainty, etc.), by author, or by year.

Supervised Students and Postdoctoral Scholars underlined

| Paper | Topic |

79. | H. Arbabi, T. Sapsis, Data-driven modeling of strongly nonlinear chaotic systems with non-Gaussian statistics, Submitted, (2019) (32 pages). [pdf] | Extreme events, Uncertainty quantification |

78. | S. Guth, T. Sapsis, Machine learning predictors of extreme events occurring in complex dynamical systems, Submitted, (2019) (22 pages). [pdf] | Extreme events, Data driven modeling |

77. | T. Sapsis, Output-weighted optimal sampling for Bayessian regression and rare event statistics using few samples, Submitted, (2019) (28 pages). [pdf] | Extreme events, Uncertainty quantification |

76. | A. Blanchard, T. Sapsis, Machine learning the tangent space of dynamical instabilities from data, Submitted, (2019) (16 pages). [pdf] | Order reduction, Data driven modeling |

75. | M. Farazmand, T. Sapsis, Closed-loop adaptive control of extreme events in a turbulent flow, Submitted, (2019) (7 pages). [pdf] | Control, Order reduction, Chaotic flows, Extreme events |

74. | 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). [pdf], Editor's Suggestion. | Control, Order reduction, Chaotic flows |

73. | 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] | Extreme events, Uncertainty quantification |

72. | 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] | Extreme events, Order reduction |

69. | 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] | Extreme events, Nonlinear waves |

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

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

68. | 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] | Control, Order reduction, Chaotic flows |

67. | 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. | Extreme events, Uncertainty quantification |

66. | M. Farazmand, T. Sapsis, Extreme events: mechanisms and prediction, ASME Applied Mechanics Reviews, In Press (2018). [pdf] | Extreme events, Review |

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

64. | 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] | Extreme events, Review |

63. | 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] | Data driven modeling, Extreme events, Turbulent systems |

62. | 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] | Data driven modeling, Turbulent systems |

61. | 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] | Energy harvesting, Random vibrations |

60. | 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] | Energy harvesting, Random vibrations |

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

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

57. | 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] | Editorial, Nonlinear vibrations, Random vibrations |

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

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

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

53. | 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] | Extreme events, Nonlinear waves |

52. | 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] | Extreme events, Random vibrations |

51. | 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] | Extreme events, Order reduction |

50. | 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] | Nonlinear load cells |

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

48. | 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] | Data driven modeling, Turbulent systems |

47. | 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] | Uncertainty quantification, Order reduction |

46. | 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] | Nonlinear vibrations |

45. | 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. | Extreme events, Order reduction, Turbulent systems |

44. | 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] | Extreme events, Nonlinear waves |

43. | 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] | Extreme events, Nonlinear vibrations |

42. | 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. | Extreme events, Order reduction, Turbulent systems |

41. | 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. | Extreme events, Nonlinear waves |

40. | 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] | Uncertainty quantification, Random vibrations |

39. | 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] | Nonlinear load cells |

38. | 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] | Extreme events, Turbulent systems |

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

36. | 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] | Random vibrations, Energy harvesting |

35. | 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] | Random vibrations, Energy harvesting |

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

33. | 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] | Uncertainty quantification, Order reduction, Turbulent systems |

32. | 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] | Extreme events, Nonlinear waves |

31. | 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] | Nonlinear vibrations, Energy harvesting |

30. | 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] | Uncertainty quantification, Order reduction |

29. | 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] | Nonlinear vibrations, Energy harvesting |

28. | 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] | Uncertainty quantification, Order reduction, Turbulent systems |

27. | 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 (2013) 011013 (15 pages). [pdf] | Nonlinear vibrations, Energy harvesting |

26. | 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] | Uncertainty quantification, Order reduction, Turbulent systems |

25. | 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] | Uncertainty quantification, Order reduction |

24. | 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] | Uncertainty Quantification, Order reduction, Chaotic flows |

23. | 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] | Uncertainty quantification, Order reduction, Turbulent systems |

22. | 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] | Uncertainty quantification, Order reduction, Chaotic flows |

21. | 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] | Uncertainty quantification, Order reduction, Chaotic flows |

20 | 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] | Uncertainty quantification, Order reduction |

19. | 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] | Uncertainty quantification, Order reduction, Chaotic flows |

18. | 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] | Uncertainty quantification, Correlated excitation |

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

16. | T. Sapsis, D. Quinn, A. Vakakis, & L. Bergman, Effective stiffening and damping enhancement of structures with strongly nonlinear local attachments, ASME Journal of Vibration & Acoustics, 134 (2012) 011016 (12 pages). [pdf] | Nonlinear vibrations |

15. | 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] | Finite size particles |

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

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

12. | 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] | Nonlinear Vibrations, Random vibrations |

11. | 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] | Nonlinear vibrations |

10. | 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] | Nonlinear vibrations |

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

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

7. | T. Sapsis & P. Lermusiaux, Dynamically orthogonal field equations for continuous stochastic dynamical systems, Physica D, 238 (2009) 2347-2360. [pdf] | Uncertainty quantification, Order reduction, Chaotic fluid flows |

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

5. | 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] | Nonlinear vibrations |

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

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

1. | 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] | Uncertainty quantification, Correlated excitation |

2. | 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] | Nonlinear vibrations |