295 citations · 609 across the 13 of their papers we have counts for
14 papers
Multigrid sequential data assimilation for the large-eddy simulation of a massively separated bluff-body flow
Gabriel Moldovan, Alessandro Mariotti, Laurent Cordier +3
The potential for data-driven applications to scale-resolving simulations of turbulent flows is assessed herein. Multigrid sequential data assimilation algorithms have been used to…
Optimized parametric inference for the inner loop of the Multigrid Ensemble Kalman Filter
Gabriel Moldovan, Guillaume Lehnasch, Laurent Cordier +1
Essential features of the Multigrid Ensemble Kalman Filter (G. Moldovan, G. Lehnasch, L. Cordier, M. Meldi, A multigrid/ensemble Kalman filter strategy for assimilation of unsteady…
A multigrid/ensemble Kalman Filter strategy for assimilation of unsteady flows
Gabriel Moldovan, Guillame Lehnasch, Laurent Cordier +1
A sequential estimator based on the Ensemble Kalman Filter for Data Assimilation of fluid flows is presented in this research work. The main feature of this estimator is that the K…
Interpolatory-based data-driven pulsed fluidic actuator control design and experimental validation
Charles Poussot-Vassal, Pauline Kergus, Franck Kerhervé +2
Pulsed fluidic actuators play a central role in the fluid flow experimental control strategy to achieve better performances of aeronautic devices. In this paper, we demonstrate, th…
Control of chaotic systems by Deep Reinforcement Learning
Michele Alessandro Bucci, Onofrio Semeraro, Alexandre Allauzen +3
Deep Reinforcement Learning (DRL) is applied to control a nonlinear, chaotic system governed by the one-dimensional Kuramoto-Sivashinsky (KS) equation. DRL uses reinforcement learn…
Rethinking the Reynolds Transport Theorem, Liouville Equation, and Perron-Frobenius and Koopman Operators
Robert K. Niven, Laurent Cordier, Eurika Kaiser +2
The Reynolds transport theorem provides a generalized conservation law for the transport of a conserved quantity by fluid flow through a continuous connected control volume. It is…