Imperial College London

DrSylvainLaizet

Faculty of EngineeringDepartment of Aeronautics

Reader in Computational Fluid Mechanics
 
 
 
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Contact

 

+44 (0)20 7594 5045s.laizet Website

 
 
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Location

 

339City and Guilds BuildingSouth Kensington Campus

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Summary

 

Summary

I am a reader in the Department of Aeronautics at Imperial College London (ICL). I hold a PhD and a Habilitation à Diriger des Recherches from the University of Poitiers in France in the field of Computational Fluid Dynamics (CFD) applied to turbulence. 

Understanding turbulent flows and how to use them in various engineering applications is the motivation behind my research. With my collaborators at Imperial College, in France and in Brazil, we develop high-order finite-difference highly-scalable flow solvers dedicated to turbulent flows. 


https://github.com/xcompact3d

https://www.turbulencesimulation.com/


Within the turbulence simulation group, we are currently investigating wake-to-wake interaction in wind farms, Bayesian optimisation techniques for drag reduction and energy saving, active control solutions of free shear flows, immersed boundary methods for moving objects, neural networks applied to computational fluid dynamics and particle-laden gravity currents.

Publications

Journals

Deskos G, Laizet S, Palacios R, WInc3D: A novel framework for turbulence-resolving simulations of wind farm wake interactions, Wind Energy, ISSN:1095-4244

Mahfoze O, Moody A, Wynn A, et al., 2019, Reducing the skin-friction drag of a turbulent boundary-layer flow with low-amplitude wall-normal blowing within a Bayesian optimisation framework., Physical Review Fluids, Vol:4, ISSN:2469-990X, Pages:094601-1-094601-23

Bartholomew P, Laizet S, 2019, A new highly scalable, high-order accurate framework for variable-density flows: application to non-Boussinesq gravity currents, Computer Physics Communications, Vol:242, ISSN:0010-4655, Pages:83-94

Pinier B, Mémin E, Laizet S, et al., 2019, Stochastic flow approach to model the mean velocity profile of wall-bounded flows, Physical Review E (statistical, Nonlinear, and Soft Matter Physics), Vol:99, ISSN:1539-3755

Deskos G, Laizet S, Piggott M, 2019, Turbulence-resolving simulations of wind turbine wakes, Renewable Energy, Vol:134, ISSN:1879-0682, Pages:989-1002

More Publications