On the construction of an efficient finite-element solver for phase-field simulations of many-particle solid-state-sintering processes

  • We present an efficient solver for the simulation of many-particle solid-state-sintering processes. The microstructure evolution is described by a system of equations consisting of one Cahn–Hilliard equation and a set of Allen-Cahn equations to distinguish neighboring particles. The particle packing is discretized in space via multicomponent linear adaptive finite elements and implicitly in time with variable time-step sizes, resulting in a large nonlinear system of equations with strong coupling between all components to be solved. Since on average 10k degrees of freedom per particle are necessary to accurately capture the interface dynamics in 3D, we propose strategies to solve the resulting large and challenging systems. This includes the efficient evaluation of the Jacobian matrix as well as the implementation of Jacobian-free methods by applying state-of-the-art matrix-free algorithms for high and dynamic numbers of components, advances regarding preconditioning, and a fullyWe present an efficient solver for the simulation of many-particle solid-state-sintering processes. The microstructure evolution is described by a system of equations consisting of one Cahn–Hilliard equation and a set of Allen-Cahn equations to distinguish neighboring particles. The particle packing is discretized in space via multicomponent linear adaptive finite elements and implicitly in time with variable time-step sizes, resulting in a large nonlinear system of equations with strong coupling between all components to be solved. Since on average 10k degrees of freedom per particle are necessary to accurately capture the interface dynamics in 3D, we propose strategies to solve the resulting large and challenging systems. This includes the efficient evaluation of the Jacobian matrix as well as the implementation of Jacobian-free methods by applying state-of-the-art matrix-free algorithms for high and dynamic numbers of components, advances regarding preconditioning, and a fully distributed grain-tracking algorithm. We validate the obtained results, examine in detail the node-level performance and demonstrate the scalability up to 10k particles on modern supercomputers. Such numbers of particles are sufficient to simulate the sintering process in (statistically meaningful) representative volume elements. Our framework thus forms a valuable tool for the virtual design of solid-state-sintering processes for pure metals and their alloys.show moreshow less

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Metadaten
Author:Peter MunchGND, Vladimir Ivannikov, Christian Cyron, Martin KronbichlerORCiDGND
URN:urn:nbn:de:bvb:384-opus4-1088725
Frontdoor URLhttps://opus.bibliothek.uni-augsburg.de/opus4/108872
ISSN:0927-0256OPAC
Parent Title (English):Computational Materials Science
Publisher:Elsevier BV
Type:Article
Language:English
Date of first Publication:2023/10/27
Publishing Institution:Universität Augsburg
Release Date:2023/11/10
Tag:Computational Mathematics; General Physics and Astronomy; Mechanics of Materials; General Materials Science; General Chemistry; General Computer Science
Volume:231
First Page:112589
DOI:https://doi.org/10.1016/j.commatsci.2023.112589
Institutes:Mathematisch-Naturwissenschaftlich-Technische Fakultät
Mathematisch-Naturwissenschaftlich-Technische Fakultät / Institut für Mathematik
Mathematisch-Naturwissenschaftlich-Technische Fakultät / Institut für Mathematik / Lehrstuhl für High-Performance Scientific Computing
Dewey Decimal Classification:5 Naturwissenschaften und Mathematik / 51 Mathematik / 510 Mathematik
Licence (German):CC-BY-NC-ND 4.0: Creative Commons: Namensnennung - Nicht kommerziell - Keine Bearbeitung (mit Print on Demand)