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Modeling of Growth using an Immersed Finite Element Method

Ebrahem, Adnan ; Hiemstra, René R. ; Stoter, Stein K. F. ; Schillinger, Dominik (2023)
Modeling of Growth using an Immersed Finite Element Method.
In: PAMM - Proceedings in Applied Mathematics & Mechanics, 2023, 22 (1)
doi: 10.26083/tuprints-00023689
Article, Secondary publication, Publisher's Version

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Item Type: Article
Type of entry: Secondary publication
Title: Modeling of Growth using an Immersed Finite Element Method
Language: English
Date: 12 May 2023
Place of Publication: Darmstadt
Year of primary publication: 2023
Publisher: Wiley-VCH
Journal or Publication Title: PAMM - Proceedings in Applied Mathematics & Mechanics
Volume of the journal: 22
Issue Number: 1
Collation: 7 Seiten
DOI: 10.26083/tuprints-00023689
Corresponding Links:
Origin: Secondary publication DeepGreen

To prevent remeshing, we explore the use of a non‐boundary‐fitted finite element method for the computational modeling of growth including contact mechanics. Accordingly, we utilize a mesh‐related mapping procedure for the use of implicit geometry description by a level set function within the framework of immersed methods. Hence, our framework provides a setting to include patient‐specific geometries based on imaging data as we use a level set function for the implicit geometry description. In this contribution, we show that the proposed approach is a viable alternative for problems with mesh‐related obstacles, in particular when large growth simulations on complex patient‐specific geometries are of primary interest.

Status: Publisher's Version
URN: urn:nbn:de:tuda-tuprints-236893
Additional Information:

Special Issue: 92nd Annual Meeting of the International Association of Applied Mathematics and Mechanics (GAMM)

Classification DDC: 600 Technology, medicine, applied sciences > 620 Engineering and machine engineering
Divisions: 13 Department of Civil and Environmental Engineering Sciences > Mechanics > Numerical Mechanics
Date Deposited: 12 May 2023 08:49
Last Modified: 14 Nov 2023 19:05
SWORD Depositor: Deep Green
URI: https://tuprints.ulb.tu-darmstadt.de/id/eprint/23689
PPN: 509296009
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