Lesnic, D orcid.org/0000-0003-3025-2770 and Alosaimi, M (2023) Determination of the space-dependent source in the thermal-wave model of bio-heat transfer. Computers and Mathematics with Applications, 129. pp. 34-49. ISSN 0898-1221
Abstract
We consider linear but ill-posed inverse problems consisting of finding the unknown space-dependent source in the thermal-wave model of bio-heat transfer from final-time or time-average temperature measurements. In contrast to the previous research on parabolic bio-heat transfer models, this work concerns a more involved and practical hyperbolic model used in biomedical engineering. First, the unique solvability of the linear inverse source problems is established. Then, the inverse problems are recast as variational problems, allowing the gradients of the least-squares objective functionals to be derived. These latter problems are solved iteratively using the conjugate gradient method combined with the discrepancy principle. Finally, the inversion algorithm is tested on identifying one- and two-dimensional space-dependent sources.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2022 Elsevier Ltd. All rights reserved. This is an author produced version of an article published in Computers and Mathematics with Applications. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | Inverse source problem; Bio-heat transfer; Conjugate gradient method; Regularization; Thermal-wave model |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Mathematics (Leeds) > Applied Mathematics (Leeds) |
Funding Information: | Funder Grant number EPSRC (Engineering and Physical Sciences Research Council) EP/W000873/1 |
Depositing User: | Symplectic Publications |
Date Deposited: | 02 Dec 2022 16:50 |
Last Modified: | 21 Nov 2023 01:13 |
Status: | Published |
Publisher: | Elsevier |
Identification Number: | 10.1016/j.camwa.2022.10.026 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:193570 |