[M-GI36] Computational sciences on the universe, galaxies, stars, planets and their environments

[MGI36-P01] Estimating the Rayleigh number and thermal structure in laboratory convection via PINN-based Lagrangian data assimilation

*Atsushi Nakao^1,2, Takatoshi Yanagisawa^2,3, Daisuke Noto^3,4, Yuji Tasaka^3,2, Tatsu Kuwatani² (1. Institute of Systems and Information Engineering, University of Tsukuba, 2. Research Institute for Marine Geodynamics, JAMSTEC, 3. Faculty of Engineering, Hokkaido University, 4. Department of Earth and Environmental Science, University of Pennsylvania)

Keywords:Data Assimilation, Deep Learning, Computational Fluid Dynamics (CFD), Particle Tracking Velocimetry (PTV), Thermal Convection