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Combining computational fluid dynamics and magnetic resonance imaging data using lattice Boltzmann based topology optimisation

Klemens, Fabian

Abstract (englisch):
This thesis presents the combination of magnetic resonance imaging (MRI) measurements and computational fluid dynamics (CFD) to reduce statistical measurement noise and identify objects and finer structures in the MRI data. Using a lattice Boltzmann based topology optimisation approach, the method allows those solutions that best match the measured flow field but satisfy the macroscopic conservation laws of fluid flow, here mass and momentum conservation. This combination is formulated as a distributed control problem that minimises the distance between measured and simulated flow field, the latter being the solution of a parametrised Boltzmann equation with Bhatnagar-Gross-Krook collision operator, where the controls represent the porosity distributed in the domain. The problem is solved with an adjoint lattice Boltzmann method using the open source software OpenLB.

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Volltext §
DOI: 10.5445/IR/1000125499
Veröffentlicht am 02.11.2020
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Angewandte und Numerische Mathematik (IANM)
Institut für Mechanische Verfahrenstechnik und Mechanik (MVM)
Publikationstyp Hochschulschrift
Publikationsdatum 02.11.2020
Sprache Englisch
Identifikator KITopen-ID: 1000125499
Verlag Karlsruhe
Umfang XI, 131 S.
Art der Arbeit Dissertation
Fakultät Fakultät für Mathematik (MATH)
Institut Institut für Angewandte und Numerische Mathematik (IANM)
Prüfungsdatum 30.09.2020
Referent/Betreuer PD Dr. G. Thäter
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