[en] A combination of reaction–diffusion models with moving-boundary problems yields a system in which the diffusion (spreading and penetration) and reaction (transformation) evolve the system’s state and geometry over time. These systems can be used in a wide range of engineering applications. In this study, as an example of such a system, the degradation of metallic materials is investigated. A mathematical model is constructed of the diffusion-reaction processes and the movement of corrosion front of a magnesium block floating in a chemical solution. The corresponding parallelized computational model is implemented using the finite element method, and the weak and strong-scaling behaviors of the model are evaluated to analyze the performance and efficiency of the employed high-performance computing techniques.
Disciplines :
Engineering, computing & technology: Multidisciplinary, general & others
Author, co-author :
Barzegari, Mojtaba ; Biomechanics Section, Department of Mechanical Engineering, KU Leuven, Leuven, Belgium
Geris, Liesbet ; Université de Liège - ULiège > GIGA > GIGA In silico medecine - Biomechanics Research Unit ; Biomechanics Section, Department of Mechanical Engineering, KU Leuven, Leuven, Belgium
Language :
English
Title :
Highly scalable numerical simulation of coupled reaction–Diffusion systems with moving interfaces
Publication date :
March 2022
Journal title :
International Journal of High Performance Computing Applications
H2020 - 772418 - INSITE - Development and use of an integrated in silico-in vitro mesofluidics system for tissue engineering
Name of the research project :
Interreg VA Flanders
Funders :
EU - European Union [BE] FWO - Fonds Wetenschappelijk Onderzoek Vlaanderen [BE]
Funding text :
The computational resources and services used in this work were provided by the VSC (Flemish Supercomputer Center), funded by the Research Foundation – Flanders (FWO) and the Flemish Government – department EWI.The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research is financially supported by the Prosperos project, funded by the Interreg VA Flanders – The Netherlands program, CCI grant no. 2014TC16RFCB046 and by the Fund for Scientific Research Flanders (FWO), grant G085018N. LG acknowledges support from the European Research Council under the European Union’s Horizon 2020 research and innovation program, ERC CoG 772418.
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