Title :

A Bayesian fusion model for space-time reconstruction of finely resolved velocities in turbulent flows from low resolution measurements

Author(s) :

van Nguyen, Linh [Auteur]
Laboratoire de Mécanique de Lille - FRE 3723 [LML]
Laval, Jean-Philippe [Auteur]
Centre National de la Recherche Scientifique [CNRS]
Laboratoire de Mécanique de Lille - FRE 3723 [LML]
Chainais, Pierre [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]

Journal title :

Journal of Statistical Mechanics: Theory and Experiment

Publisher :

IOP Publishing

Publication date :

2015-10-09

ISSN :

1742-5468

English keyword(s) :

Reconstruction
Bayesian
Turbulence

HAL domain(s) :

Physique [physics]/Mécanique [physics]/Mécanique des fluides [physics.class-ph]
Informatique [cs]/Recherche d'information [cs.IR]
Sciences de l'ingénieur [physics]

English abstract : [en]

The study of turbulent flows calls for measurements with high resolution both in space and time. We propose a new approach to reconstruct High-Temporal-High-Spatial resolution velocity fields by combining two sources of ...
Show more >The study of turbulent flows calls for measurements with high resolution both in space and time. We propose a new approach to reconstruct High-Temporal-High-Spatial resolution velocity fields by combining two sources of information that are well-resolved either in space or in time, the Low-Temporal-High-Spatial (LTHS) and the High-Temporal-Low-Spatial (HTLS) resolution measurements. In the framework of co-conception between sensing and data post-processing, this work extensively investigates a Bayesian reconstruction approach using a simulated database. A Bayesian fusion model is developed to solve the inverse problem of data reconstruction. The model uses a maximum\textit{a posteriori} estimate, which yields the most probable field knowing the measurements. The DNS of a wall-bounded turbulent flow at moderate Reynolds number is used to validate and assess the performances of the present approach. Low resolution measurements are subsampled in time and space from the fully resolved data. Reconstructed velocities are compared to the reference DNS to estimate the reconstruction errors. The model is compared to other conventional methods such as Linear Stochastic Estimation and cubic spline interpolation. Results show the superior accuracy of the proposed method in all configurations. Further investigations of model performances on various range of scales demonstrate its robustness. Numerical experiments also permit to estimate the expected maximum information level corresponding to limitations of experimental instruments.Show less >

Language :

Anglais

Popular science :

Non

Collections :

• Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189

Source :

Harvested from HAL