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A modified coupled complex boundary method for an inverse chromatography problem
Department of Mathematics, Zhejiang University, Hangzhou, Zhejiang, China.
Department of Mathematics, Zhejiang University, Hangzhou, Zhejiang, China.
Örebro University, School of Science and Technology. Department of Mathematics.ORCID iD: 0000-0003-4023-6352
Department of Mathematics, Nanjing University of Aeronautics and Astronautics, Nanjing, China.
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2017 (English)In: Journal of Inverse and Ill-Posed Problems, ISSN 0928-0219, E-ISSN 1569-3945Article in journal (Refereed) Epub ahead of print
Abstract [en]

Adsorption isotherms are the most important parameters in rigorous models of chromatographic processes. In this paper, in order to recover adsorption isotherms, we consider a coupled complex boundary method (CCBM), which was previously proposed for solving an inverse source problem [2]. With CCBM, the original boundary fitting problem is transferred to a domain fitting problem. Thus, this method has advantages regarding robustness and computation in reconstruction. In contrast to the traditional CCBM, for the sake of the reduction of computational complexity and computational cost, the recovered adsorption isotherm only corresponds to the real part of the solution of a forward complex initial boundary value problem. Furthermore, we take into account the position of the profiles and apply the momentum criterion to improve the optimization progress. Using Tikhonov regularization, the well-posedness, convergence properties and regularization parameter selection methods are studied. Based on an adjoint technique, we derive the exact Jacobian of the objective function and give an algorithm to reconstruct the adsorption isotherm. Finally, numerical simulations are given to show the feasibility and efficiency of the proposed regularization method.

Place, publisher, year, edition, pages
Walter de Gruyter, 2017.
Keyword [en]
Chromatography; adsorption isotherm; inverse problem; coupled complex boundary method; Tikhonov regularization
National Category
Computational Mathematics
Research subject
Mathematics
Identifiers
URN: urn:nbn:se:oru:diva-58691DOI: 10.1515/jiip-2016-0057OAI: oai:DiVA.org:oru-58691DiVA: diva2:1127584
Available from: 2017-07-17 Created: 2017-07-17 Last updated: 2017-10-18Bibliographically approved

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Zhang, YeGulliksson, Mårten

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