Zobrazeno 1 - 10
of 83
pro vyhledávání: '"Podvin, Bérengère"'
We present a formulation of proper orthogonal decomposition (POD) producing a velocity-temperature basis optimized with respect to an $H^1$ dissipation norm. This decomposition is applied, along with a conventional POD optimized with respect to an $L
Externí odkaz:
http://arxiv.org/abs/2311.11807
We apply a probabilistic clustering method, Latent Dirichlet Allocation (LDA), to characterize the largescale dynamics of Rayleigh-B\'enard convection. The method, introduced in Frihat et al. 2021, is applied to a collection of snapshots in the verti
Externí odkaz:
http://arxiv.org/abs/2305.03708
Publikováno v:
Phys. Rev. Fluids 9 (2024) 014605
We present an experimental study of the aerodynamic forces on a thick and cambered airfoil at a high Reynolds number 3.6 x 10^6, which is of direct relevance for wind turbine design. Unlike thin airfoils at low chord-based Reynolds numbers, no consis
Externí odkaz:
http://arxiv.org/abs/2304.02927
Autor:
Podvin, Bérengère, Pellerin, Stéphanie, Fraigneau, Yann, Bonnavion, Guillaume, Cadot, Olivier
We investigate the near-wake flow of an Ahmed body which is characterized by switches between two asymmetric states that are mirrors of each other in the spanwise direction. The work focuses on the relationship between the base pressure distribution
Externí odkaz:
http://arxiv.org/abs/2111.15595
Identification of coherent structures is an essential step to describe and model turbulence generation mechanisms in wall-bounded flows. To this end we present a clustering method based on Latent Dirichlet Allocation (LDA), a generative probabilistic
Externí odkaz:
http://arxiv.org/abs/2005.10010
Publikováno v:
Phys. Rev. Fluids 5, 064612 (2020)
We investigate numerically the 3-D flow around a squareback Ahmed body at Reynolds number Re = 104. Proper Orthogonal Decomposition (POD) is applied to a symmetry-augmented database in order to describe and model the flow dynamics. Comparison with ex
Externí odkaz:
http://arxiv.org/abs/1909.13129
An extension of Proper Orthogonal Decomposition is applied to the wall layer of a turbulent channel flow (Re {\tau} = 590), so that empirical eigenfunctions are defined in both space and time. Due to the statistical symmetries of the flow, the igenfu
Externí odkaz:
http://arxiv.org/abs/1805.01494
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Akademický článek
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We propose to use a clustering method, Latent Dirichlet Allocation or LDA (Frihat et al. JFM2021), to characterize the convective heat flux in turbulent Rayleigh-B\'enard convection. LDA provides a probabilistic decomposition of a collection of field
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=arXiv_______::0c02b11c4469c68e393d2084ae04744a
http://arxiv.org/abs/2305.03708
http://arxiv.org/abs/2305.03708