Karageorghis, A and Lesnic, D orcid.org/0000-0003-3025-2770 (2020) Identification of obstacles immersed in a stationary Oseen fluid via boundary measurements. Inverse Problems in Science and Engineering, 28 (7). pp. 950-967. ISSN 1741-5977
Abstract
In this paper we consider the interior inverse problem of identifying a rigid boundary of an annular infinitely long cylinder within which there is a stationary Oseen viscous fluid, by measuring various quantities such as the fluid velocity, fluid traction (stress force) and/or the pressure gradient on portions of the outer accessible boundary of the annular geometry. The inverse problems are nonlinear with respect to the variable polar radius parameterizing the unknown star-shaped obstacle. Although for the type of boundary data that we are considering the obstacle can be uniquely identified based on the principle of analytic continuation, its reconstruction is still unstable with respect to small errors in the measured data. In order to deal with this instability, the nonlinear Tikhonov regularization is employed. Obstacles of various shapes are numerically reconstructed using the method of fundamental solutions for approximating the fluid velocity and pressure combined with the MATLAB©© toolbox routine lsqnonlin for minimizing the nonlinear Tikhonov's regularization functional subject to simple bounds on the variables.
Metadata
Item Type: | Article |
---|---|
Authors/Creators: |
|
Copyright, Publisher and Additional Information: | © 2019, Informa UK Limited, trading as Taylor & Francis group. This is an author produced version of a paper published in Inverse Problems in Science and Engineering. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | Inverse obstacle problem, Oseen equations, method of fundamental solutions, nonlinear minimization |
Dates: |
|
Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Mathematics (Leeds) > Applied Mathematics (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 16 Oct 2019 14:01 |
Last Modified: | 15 Dec 2020 11:08 |
Status: | Published |
Publisher: | Taylor & Francis |
Identification Number: | 10.1080/17415977.2019.1686498 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:152178 |