34 citations · 57 across the 12 of their papers we have counts for
8 papers · 1 filter
Prediction of Intermittent Fluctuations from Surface Pressure Measurements on a Turbulent Airfoil
Samuel H. Rudy, Themistoklis P. Sapsis
This work studies the effectiveness of several machine learning techniques for predicting extreme events occurring in the flow around an airfoil at low Reynolds. For certain Reynol…
Learning Optimal Parametric Hydrodynamic Database for Vortex-Induced Crossflow Vibration Prediction
Samuel Rudy, Dixia Fan, Jose del Aguila Ferrandis +2
The Vortex-induced vibration (VIV) prediction of long flexible cylindrical structures relies on the accuracy of the hydrodynamic database constructed via rigid cylinder forced vibr…
Machine-learning energy-preserving nonlocal closures for turbulent fluid flows and inertial tracers
Alexis-Tzianni G. Charalampopoulos, Themistoklis P. Sapsis
We formulate a data-driven, physics-constrained closure method for coarse-scale numerical simulations of turbulent fluid flows. Our approach involves a closure scheme that is non-l…
A Gaussian moment method and its augmentation via LSTM recurrent neural networks for the statistics of cavitating bubble populations
Spencer H. Bryngelson, Alexis Charalampopoulos, Themistoklis P. Sapsis +1
Phase-averaged dilute bubbly flow models require high-order statistical moments of the bubble population. The method of classes, which directly evolve bins of bubbles in the probab…
Bubbles in Turbulent Flows: Data-driven, kinematic models with memory terms
Zhong Yi Wan, Petr Karnakov, Petros Koumoutsakos +1
We present data driven kinematic models for the motion of bubbles in high-Re turbulent fluid flows based on recurrent neural networks with long-short term memory enhancements. The…
Closed-loop adaptive control of extreme events in a turbulent flow
Mohammad Farazmand, Themistoklis P. Sapsis
Extreme events that arise spontaneously in chaotic dynamical systems often have an adverse impact on the system or the surrounding environment. As such, their mitigation is highly…