61 citations · 302 across the 13 of their papers we have counts for
14 papers
Reinforcement Learning Increases Wind Farm Power Production by Enabling Closed-Loop Collaborative Control
Andrew Mole, Max Weissenbacher, Georgios Rigas +1
Traditional wind farm control operates each turbine independently to maximize individual power output. However, coordinated wake steering across the entire farm can substantially i…
Unsupervised Random Quantum Networks for PDEs
Josh Dees, Antoine Jacquier, Sylvain Laizet
Classical Physics-informed neural networks (PINNs) approximate solutions to PDEs with the help of deep neural networks trained to satisfy the differential operator and the relevant…
FR3D: Three-dimensional Flow Reconstruction and Force Estimation for Unsteady Flows Around Extruded Bluff Bodies via Conformal Mapping Aided Convolutional Autoencoders
Ali Girayhan Özbay, Sylvain Laizet
In many practical fluid dynamics experiments, measuring variables such as velocity and pressure is possible only at a limited number of sensor locations, \textcolor{black}{for a fe…
Investigating Bayesian optimization for expensive-to-evaluate black box functions: Application in fluid dynamics
Mike Diessner, Joseph O'Connor, Andrew Wynn +4
Bayesian optimization provides an effective method to optimize expensive-to-evaluate black box functions. It has been widely applied to problems in many fields, including notably i…
Direct numerical simulations of shocklet-containing turbulent channel counter-flows
Arash Hamzehloo, David J. Lusher, Sylvain Laizet +1
Counter-flow or counter-current configurations can maintain high turbulence intensities and exhibit a significant level of mixing. We have previously introduced a wall-bounded coun…
Deep learning fluid flow reconstruction around arbitrary two-dimensional objects from sparse sensors using conformal mappings
Ali Girayhan Özbay, Sylvain Laizet
The usage of neural networks (NNs) for flow reconstruction (FR) tasks from a limited number of sensors is attracting strong research interest, owing to NNs' ability to replicate hi…
Lagrangian Coherent Track Initialisation (LCTI)
Ali Rahimi Khojasteh, Yin Yang, Dominique Heitz +1
Advances in time-resolved Particle Tracking Velocimetry (4D-PTV) techniques have been consistently revealed more accurate Lagrangian particle motions. A novel track initialisation…
Flows Over Periodic Hills of Parameterized Geometries: A Dataset for Data-Driven Turbulence Modeling From Direct Simulations
Heng Xiao, Jin-Long Wu, Sylvain Laizet +1
Computational fluid dynamics models based on Reynolds-averaged Navier--Stokes equations with turbulence closures still play important roles in engineering design and analysis. Howe…
Poisson CNN: Convolutional neural networks for the solution of the Poisson equation on a Cartesian mesh
Ali Girayhan Özbay, Arash Hamzehloo, Sylvain Laizet +3
The Poisson equation is commonly encountered in engineering, for instance in computational fluid dynamics (CFD) where it is needed to compute corrections to the pressure field to e…
A model under location uncertainty to predict the mean velocity in wall bounded flows
Benoit Pinier, Etienne Mémin, Sylvain Laizet +1
To date no satisfying model exists to explain the mean velocity profile within the whole turbulent layer of canonical wall bounded flows. We propose a modification of the velocity…
Turbulence-resolving simulations of wind turbine wakes
Georgios Deskos, Sylvain Laizet, Matthew D. Piggott
Turbulence-resolving simulations of wind turbine wakes are presented using a high--order flow solver combined with both a standard and a novel dynamic implicit spectral vanishing v…
Representation of Reynolds Stress Perturbations with Application in Machine-Learning-Assisted Turbulence Modeling
Jinlong Wu, Rui Sun, Sylvain Laizet +1
Numerical simulations based on Reynolds-Averaged Navier--Stokes (RANS) equations are widely used in engineering design and analysis involving turbulent flows. However, RANS simulat…
Influence of the spatial resolution on fine-scale features in DNS of turbulence generated by a single square grid
S. Laizet, J. Nedić, J. C. Vassilicos
We focus in this paper on the effect of the resolution of Direct Numerical Simulations (DNS) on the spatio-temporal development of the turbulence downstream of a single square grid…
Vortex line density in counterflowing He II with laminar and turbulent normal fluid velocity profiles
A. W. Baggaley, S. Laizet
Superfluid helium is an intimate mixture of a viscous normal fluid, with continuous vorticity, and an inviscid superfluid, where vorticity is constrained to thin, stable topologica…