Reconstruction of large scale flow structures in a stirred tank from limited sensor data
File(s)aic.17348.pdf (4.01 MB)
Published version
Author(s)
Papadakis, Georgios
Rigopoulos, Stelios
Mikhaylov, kirill
Type
Journal Article
Abstract
We combine reduced order modelling and system identification to reconstruct the temporal evolution of large scale vortical structures behind the blades of a Rushton impeller. We performed Direct Numerical Simulations at Reynolds number 600 and employed proper orthogonal decomposition (POD) to extract the dominant modes and their temporal coefficients. We then applied the identification algorithm, N4SID, to construct an estimator that captures the relation between the velocity signals at sensor points (input) and the POD coefficients (output). We show that the first pair of modes can be very well reconstructed using the velocity time signal from even a single sensor point. A larger number of points improves accuracy and robustness, and also leads to better reconstruction for the second pair of POD modes. Application of the estimator derived at Re=600 to the flows at Re=500 and 700, shows that it is robust with respect to changes in operating conditions.
Date Issued
2021-10
Date Acceptance
2021-05-18
Citation
AIChE Journal, 2021, 67 (10), pp.1-16
ISSN
0001-1541
Publisher
Wiley
Start Page
1
End Page
16
Journal / Book Title
AIChE Journal
Volume
67
Issue
10
Copyright Statement
© 2021 The Authors. AIChE Journal published by Wiley Periodicals LLC on behalf of American Institute of Chemical Engineers.
This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
License URL
Identifier
https://aiche.onlinelibrary.wiley.com/doi/10.1002/aic.17348
Subjects
Science & Technology
Technology
Engineering, Chemical
Engineering
computational fluid dynamics (CFD)
fluid mechanics
turbulence
PROPER ORTHOGONAL DECOMPOSITION
TURBULENT-FLOW
LARGE-EDDY
NUMERICAL-SIMULATION
POWER-CONSUMPTION
IDENTIFICATION
VESSEL
HYDRODYNAMICS
DYNAMICS
TIME
Chemical Engineering
0904 Chemical Engineering
0914 Resources Engineering and Extractive Metallurgy
Publication Status
Published
Date Publish Online
2021-06-08