Far-Wake Meandering of a Wind Turbine Model with Imposed Motions: An Experimental S-PIV Analysis

Autor: Navid Belvasi, Boris Conan, Benyamin Schliffke, Laurent Perret, Cian Desmond, Jimmy Murphy, Sandrine Aubrun

Publikováno v: Energies, Vol 15, Iss 20, p 7757 (2022)

Intra-array wake meandering increases fatigue loading in downstream turbines and decreases farm total power output. In the case of floating offshore wind turbines (FOWTs), the motions of the floating substructure could have a non-neglectable contribu

Externí odkaz: https://doaj.org/article/9d6fd397d61a4a9f88975dd0e4b9967e

Machine learning for fluid flow reconstruction from limited measurements

Autor: Thomas Gomez, Laurent Perret, Laurent Planckaert, Pierre Dubois

Publikováno v: Journal of Computational Physics
Journal of Computational Physics, Elsevier, 2022, 448, pp.110733. ⟨10.1016/j.jcp.2021.110733⟩
Journal of Computational Physics, 2022, 448, pp.110733. ⟨10.1016/j.jcp.2021.110733⟩

International audience; This paper investigates the use of data-driven methods for the reconstruction of unsteady fluid flow fields. The proposed framework is based on the combination of machine learning tools: dimensionality reduction to extract dom

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b798b74edceb7d250580c904fd4b0bf2
https://hal.archives-ouvertes.fr/hal-03396275

Assessment of inner–outer interactions in the urban boundary layer using a predictive model

Autor: Laurent Perret, Romain Mathis, Karin Blackman

Publikováno v: Journal of Fluid Mechanics
Journal of Fluid Mechanics, Cambridge University Press (CUP), 2019, 875, pp.44-70. ⟨10.1017/jfm.2019.427⟩

Urban-type rough-wall boundary layers developing over staggered cube arrays with plan area packing density, $\unicode[STIX]{x1D706}_{p}$, of 6.25 %, 25 % or 44.4 % have been studied at two Reynolds numbers within a wind tunnel using hot-wire anemomet

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9b12de74a28bb32b7885f61e0c854049
https://doi.org/10.1017/jfm.2019.427

Prédictions orientées données du système de Lorenz

Autor: Laurent Planckaert, Laurent Perret, Thomas Gomez, Pierre Dubois

Publikováno v: Physica D: Nonlinear Phenomena
Physica D: Nonlinear Phenomena, Elsevier, 2020, 408, pp.132495. ⟨10.1016/j.physd.2020.132495⟩
Physica D: Nonlinear Phenomena, 2020, 408, pp.132495. ⟨10.1016/j.physd.2020.132495⟩

International audience; This paper investigates the use of a data-driven method to model the dynamics of the chaotic Lorenz system. An architecture based on a recurrent neural network with long and short term dependencies predicts multi-step ahead th

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::390b65d00acc6547428ebc7b0c2534c9
https://hal.archives-ouvertes.fr/hal-02475962v2/file/DAAA19190.1587487898_postprint.pdf

The Spanwise Variation of Roof-Level Turbulence in a Street-Canyon Flow

Autor: Laurent Perret, Thomas Jaroslawski, Karin Blackman, Eric Savory

Publikováno v: Boundary-Layer Meteorology. 170:373-394

The effect of upstream roughness and canyon width on turbulent street-canyon flow is investigated, using wind-tunnel measurements made in a horizontal plane at near roof level of a street canyon and stereoscopic particle image velocimetry. Three upst

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::6d0b41f8f057ac4c12173171882679ef
https://doi.org/10.1007/s10546-018-0405-z