4 papers
Differential-Embedding Reconstruction of Dynamical Systems from Scalar Time Series
Ameir Shaa, Claude Guet
We study the reconstruction of an unknown dynamical system from a single noisy scalar time series. The goal is to recover the underlying dynamics for forecasting. We introduce a me…
Surrogate modeling of drift-reduced Braginskii turbulence with resistivity-conditioned Koopman neural operators
Ameir Shaa, Kyungtak Lim, Long Shan Chan +1
Machine-learning-driven surrogate operators are developed for three-dimensional, nonlinear, flux-driven simulations of boundary plasma turbulence based on the two-fluid drift-reduc…
Hybrid Neural Interpolation of a Sequence of Wind Flows
Ameir Shaa, Claude Guet, Xiasu Yang +3
Rapid and accurate urban wind field prediction is essential for modeling particle transport in emergency scenarios. Traditional Computational Fluid Dynamics (CFD) approaches are to…
Extracting a stochastic model for predator-prey dynamic of turbulence and zonal flows with limited data
J. C. Huang, Z. S. Qu, R. Varennes +6
Understanding the interaction between turbulence and zonal flows is critical for modeling turbulence transport in fusion plasmas, often described through predator-prey dynamics. Ho…