Imperial College London
Alternate

ProfessorGeorgePapadakis

Faculty of Engineering, Department of Aeronautics

Professor of Aerodynamics
 
 
 
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Contact

 

+44 (0)20 7594 5080g.papadakis

 
 
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Location

 

331City and Guilds BuildingSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@article{Lu:2023:10.1007/s10494-023-00417-2,
author = {Lu, S and Papadakis, G},
doi = {10.1007/s10494-023-00417-2},
journal = {Flow, Turbulence and Combustion},
pages = {1059--1090},
title = {Flow reconstruction around a surface-mounted prism from sparse velocity and/or scalar measurements using a combination of POD and a data-driven estimator},
url = {http://dx.doi.org/10.1007/s10494-023-00417-2},
volume = {110},
year = {2023}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - A data-driven algorithm is proposed for flow reconstruction from sparse velocity and/or scalar measurements. The algorithm is applied to the flow around a two-dimensional, wall-mounted, square prism. To reduce the problem dimensionality, snapshots of flow and scalar fields are processed to derive POD modes and their time coefficients. Then a system identification algorithm is employed to build a reduced order, linear, dynamical system for the flow and scalar dynamics. Optimal estimation theory is subsequently applied to derive a Kalman estimator to predict the time coefficients of the POD modes from sparse measurements. Analysis of the flow and scalar spectra demonstrate that the flow field leaves its footprint on the scalar, thus extracting velocity from scalar concentration measurements is meaningful. The results show that remarkably good reconstruction of the flow statistics (Reynolds stresses) and instantaneous flow patterns can be obtained using a very small number of sensors (even a single scalar sensor yields very satisfactory results for the case considered). The Kalman estimator derived at one condition is able to reconstruct with acceptable accuracy the flow fields at two nearby off-design conditions. Further work is needed to assess the performance of the algorithm in more complex, three-dimensional, flows.
AU  - Lu,S
AU  - Papadakis,G
DO  - 10.1007/s10494-023-00417-2
EP  - 1090
PY  - 2023///
SN  - 0003-6994
SP  - 1059
TI  - Flow reconstruction around a surface-mounted prism from sparse velocity and/or scalar measurements using a combination of POD and a data-driven estimator
T2  - Flow, Turbulence and Combustion
UR  - http://dx.doi.org/10.1007/s10494-023-00417-2
UR  - https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000970736700001&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=a2bf6146997ec60c407a63945d4e92bb
UR  - https://link.springer.com/article/10.1007/s10494-023-00417-2
UR  - http://hdl.handle.net/10044/1/106891
VL  - 110
ER  -
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