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Title: Enhancement of flow measurements using fluid-dynamic constraints

Abstract

Novel experimental modalities acquire spatially resolved velocity measurements for steady state and transient flows which are of interest for engineering and biological applications. One of the drawbacks of such high resolution velocity data is their susceptibility to measurement errors. In this paper, we propose a novel filtering strategy that allows enhancement of the noisy measurements to obtain reconstruction of smooth divergence free velocity and corresponding pressure fields which together approximately comply to a prescribed flow model. The main step in our approach consists of the appropriate use of the velocity measurements in the design of a linearized flow model which can be shown to be well-posed and consistent with the true velocity and pressure fields up to measurement and modeling errors. The reconstruction procedure is then formulated as an optimal control problem for this linearized flow model. The resulting filter has analyzable smoothing and approximation properties. We briefly discuss the discretization of the approach by finite element methods and comment on the efficient solution by iterative methods. The capability of the proposed filter to significantly reduce data noise is demonstrated by numerical tests including the application to experimental data. In addition, we compare with other methods like smoothing and solenoidalmore » filtering.« less

Authors:
 [1];  [1];  [2]
  1. Institute for Numerical Analysis and Scientific Computing, Department of Mathematics, TU Darmstadt (Germany)
  2. Institute for Fluid Mechanics and Aerodynamics, Center of Smart Interfaces, TU Darmstadt (Germany)
Publication Date:
OSTI Identifier:
22701594
Resource Type:
Journal Article
Journal Name:
Journal of Computational Physics
Additional Journal Information:
Journal Volume: 344; Other Information: Copyright (c) 2017 Elsevier Science B.V., Amsterdam, The Netherlands, All rights reserved.; Country of input: International Atomic Energy Agency (IAEA); Journal ID: ISSN 0021-9991
Country of Publication:
United States
Language:
English
Subject:
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS; FILTERS; FINITE ELEMENT METHOD; FLOW MODELS; FLUID MECHANICS; ITERATIVE METHODS; NAVIER-STOKES EQUATIONS; OPTIMAL CONTROL; SIMULATION

Citation Formats

Egger, H., E-mail: egger@mathematik.tu-darmstadt.de, Seitz, T., and Tropea, C. Enhancement of flow measurements using fluid-dynamic constraints. United States: N. p., 2017. Web. doi:10.1016/J.JCP.2017.04.080.
Egger, H., E-mail: egger@mathematik.tu-darmstadt.de, Seitz, T., & Tropea, C. Enhancement of flow measurements using fluid-dynamic constraints. United States. doi:10.1016/J.JCP.2017.04.080.
Egger, H., E-mail: egger@mathematik.tu-darmstadt.de, Seitz, T., and Tropea, C. Fri . "Enhancement of flow measurements using fluid-dynamic constraints". United States. doi:10.1016/J.JCP.2017.04.080.
@article{osti_22701594,
title = {Enhancement of flow measurements using fluid-dynamic constraints},
author = {Egger, H., E-mail: egger@mathematik.tu-darmstadt.de and Seitz, T. and Tropea, C.},
abstractNote = {Novel experimental modalities acquire spatially resolved velocity measurements for steady state and transient flows which are of interest for engineering and biological applications. One of the drawbacks of such high resolution velocity data is their susceptibility to measurement errors. In this paper, we propose a novel filtering strategy that allows enhancement of the noisy measurements to obtain reconstruction of smooth divergence free velocity and corresponding pressure fields which together approximately comply to a prescribed flow model. The main step in our approach consists of the appropriate use of the velocity measurements in the design of a linearized flow model which can be shown to be well-posed and consistent with the true velocity and pressure fields up to measurement and modeling errors. The reconstruction procedure is then formulated as an optimal control problem for this linearized flow model. The resulting filter has analyzable smoothing and approximation properties. We briefly discuss the discretization of the approach by finite element methods and comment on the efficient solution by iterative methods. The capability of the proposed filter to significantly reduce data noise is demonstrated by numerical tests including the application to experimental data. In addition, we compare with other methods like smoothing and solenoidal filtering.},
doi = {10.1016/J.JCP.2017.04.080},
journal = {Journal of Computational Physics},
issn = {0021-9991},
number = ,
volume = 344,
place = {United States},
year = {2017},
month = {9}
}