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physics.flu-dyn2022
A Physics-Informed Data-Driven Algorithm for Ensemble Forecast of Complex Turbulent Systems
Nan Chen, Di Qi
A new ensemble forecast algorithm, named as the physics-informed data-driven algorithm with conditional Gaussian statistics (PIDD-CG), is developed to predict the time evolution of…
physics.flu-dyn2020
Anomalous waves triggered by abrupt depth changes: laboratory experiments and truncated KdV statistical mechanics
M. N. J. Moore, C. Tyler Bolles, Andrew J. Majda +1
Recent laboratory experiments of Bolles et al. (2019) demonstrate that an abrupt change in bottom topography can trigger anomalous statistics in randomized surface waves. Motivated…
physics.flu-dyn2018
Strategies for Reduced-Order Models for Predicting the Statistical Responses and Uncertainty Quantification in Complex Turbulent Dynamical Systems
Andrew J. Majda, Di Qi
Turbulent dynamical systems characterized by both a high-dimensional phase space and a large number of instabilities are ubiquitous among many complex systems in science and engine…