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Nonlinear multi-time-delay stochastic estimation: application to cavity flow and turbulent channel flow

Nonlinear multi-time-delay stochastic estimation: application to cavity flow and turbulent channel flow
Nonlinear multi-time-delay stochastic estimation: application to cavity flow and turbulent channel flow
A nonlinear extension of the multi-time-delay stochastic estimation technique is presented. The proposed approach consists of the design of nonlinear prediction filters based on artificial neural networks or, for smaller problems, on Volterra expansions of the measured wall variable. The application to two different flows is discussed. The first case is the estimation of the temporal dynamics of the velocity fluctuations in a cavity shear layer in low subsonic conditions from wall-pressure measurements. The second case is the estimation of the streamwise velocity fluctuations in the buffer layer of a fully developed turbulent channel flow from wall shear stress measurements. It is shown that the accuracy of the nonlinear technique is application dependent as it is significantly affected by the underlying nonlinear nature of the flow investigated. In particular, we show that, for the cavity shear layer case, the improvement is marginal and it does not appear to be worth the additional computational complexity associated with the nonlinear problem. On the other hand, the improvement in accuracy of the nonlinear estimation of the velocity fluctuations in the wall turbulence case is significant, owing to the strong nonlinearity of the dynamics in the wall-bounded flow.
0001-1452
2920-2935
Lasagna, Davide
0340a87f-f323-40fb-be9f-6de101486b24
Fronges, Linda
68bd18a4-e9c6-4e03-9f29-cd110bbd1034
Orazi, Matteo
a6177aef-f756-4125-bd51-1ece141259ac
Iuso, Gaetano
bddefee6-24c3-44fd-9b60-bec9ba1df95f
Lasagna, Davide
0340a87f-f323-40fb-be9f-6de101486b24
Fronges, Linda
68bd18a4-e9c6-4e03-9f29-cd110bbd1034
Orazi, Matteo
a6177aef-f756-4125-bd51-1ece141259ac
Iuso, Gaetano
bddefee6-24c3-44fd-9b60-bec9ba1df95f

Lasagna, Davide, Fronges, Linda and Orazi, Matteo et al. (2015) Nonlinear multi-time-delay stochastic estimation: application to cavity flow and turbulent channel flow. AIAA Journal, 53 (10), 2920-2935. (doi:10.2514/1.J053681).

Record type: Article

Abstract

A nonlinear extension of the multi-time-delay stochastic estimation technique is presented. The proposed approach consists of the design of nonlinear prediction filters based on artificial neural networks or, for smaller problems, on Volterra expansions of the measured wall variable. The application to two different flows is discussed. The first case is the estimation of the temporal dynamics of the velocity fluctuations in a cavity shear layer in low subsonic conditions from wall-pressure measurements. The second case is the estimation of the streamwise velocity fluctuations in the buffer layer of a fully developed turbulent channel flow from wall shear stress measurements. It is shown that the accuracy of the nonlinear technique is application dependent as it is significantly affected by the underlying nonlinear nature of the flow investigated. In particular, we show that, for the cavity shear layer case, the improvement is marginal and it does not appear to be worth the additional computational complexity associated with the nonlinear problem. On the other hand, the improvement in accuracy of the nonlinear estimation of the velocity fluctuations in the wall turbulence case is significant, owing to the strong nonlinearity of the dynamics in the wall-bounded flow.

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Accepted/In Press date: 11 December 2014
Published date: October 2015
Organisations: Aeronautics, Astronautics & Comp. Eng

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Local EPrints ID: 384134
URI: http://eprints.soton.ac.uk/id/eprint/384134
ISSN: 0001-1452
PURE UUID: 297ebd34-97d4-4e14-bc8c-de8b6a40e620
ORCID for Davide Lasagna: ORCID iD orcid.org/0000-0002-6501-6041

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Date deposited: 15 Dec 2015 11:47
Last modified: 15 Mar 2024 03:47

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Contributors

Author: Davide Lasagna ORCID iD
Author: Linda Fronges
Author: Matteo Orazi
Author: Gaetano Iuso

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