Low-Order Modeling and Machine Learning in Fluid Dynamics: Other Applications II

FOCUS · ZC11 · ID: 2665114

Presentations

  • Dynamic Mode Decomposition of Wake Flow Structures for Supersonic Oscillating Genesis Atmospheric Entry Capsule

    ORAL

    –

    Publication: [1] Ohmichi, Y., Kobayashi, K. and Kanazaki, M., 2019. Numerical investigation of wake structures of an atmospheric entry capsule by modal analysis. Physics of Fluids, 31(7).
    [2] Teramoto, S., Hiraki, K. and Fujii, K., 2001. Numerical analysis of dynamic stability of a reentry capsule at transonic speeds. AIAA journal, 39(4), pp.646-653.
    [3] Kazemba, C.D., Braun, R.D., Schoenenberger, M. and Clark, I.G., 2015. Dynamic stability analysis of blunt-body entry vehicles using time-lagged aftbody pitching moments. Journal of Spacecraft and Rockets, 52(2), pp.393-403.
    [4] Romeo, S.A.S., Oz, F., Kassem, A., Kara, K. and San, O., 2024. An augmented physics informed neural network approach for blunt-body dynamics. Physics of Fluids, 36(1).
    [5] Kobayashi, K., Ohmichi, Y. and Kanazaki, M., 2019. Modal decomposition analysis of subsonic unsteady flow around an atmospheric Entry capsule with forced oscillation. In AIAA Scitech 2019 Forum (p. 1851).
    [6] Oz, F., Romeo, S. A. S., Kassem, A., Ekelschot, D., Schulz, J. C., Kazemba, C., San, O., and Kara, K., "Nonlinear Parameter
    Estimation for Entry Capsule Dynamic Stability Analysis and Uncertainty Quantification," Journal of Spacecraft and Rockets,
    2024. Under Review, 2024-01-A35998.

    Presenters

    • Ashraf Kassem

      Oklahoma State University-Stillwater

    Authors

    • Ashraf Kassem

      Oklahoma State University-Stillwater

    • Shafi Al Salman Romeo

      Oklahoma State University-Stillwater, Oklahoma State University

    • Bipin Tiwari

      University of Tennessee-Knoxville

    • Omer San

      University of Tennessee

    • Kursat Kara

      Oklahoma State University

    View abstract →

  • Optimizing progress variables for ammonia/hydrogen combustion using encoding-decoding networks

    ORAL

    –

    Publication: Kamila Zdybał, James C. Sutherland, Alessandro Parente - Optimizing progress variables for ammonia/hydrogen combustion using encoding-decoding networks, 2024.

    Presenters

    • James Sutherland

      University of Utah

    Authors

    • Kamila Zdybal

      Empa, Swiss Federal Laboratory

    • James Sutherland

      University of Utah

    • Alessandro Parente

      Université Libre de Bruxelles

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  • Quantifying Uncertainty in Groundwater Vulnerability Assessment: a Bayesian Approach

    ORAL

    –

    Publication: [1] National Research Council 1993. Ground Water Vulnerability Assessment: Predicting Relative Contamination Potential Under Conditions of Uncertainty, Washington, DC, The National Academies Press, DOI: doi:10.17226/2050.
    [2] Taghavi, N., Niven, R. K., Paull, D. J. & Kramer, M. 2022. Groundwater vulnerability assessment: A review including new statistical and hybrid methods. Science of The Total Environment, 822, 153486 DOI: https://doi.org/10.1016/j.scitotenv.2022.153486.
    [3] Mohammad Djafari, A. & Dumitru, M. J. D. S. P. 2015. Bayesian sparse solutions to linear inverse problems with non-stationary noise with Student-t priors. 47, 128-156.

    Presenters

    • Nasrin Taghavi

      University of New South Wales

    Authors

    • Nasrin Taghavi

      University of New South Wales

    • Robert K Niven

      University of New South Wales

    • David J Paull

      University of New South Wales

    • Matthias Kramer

      University of New South Wales

    View abstract →