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Numerical methods and programming, 2022, Volume 23, Issue 2, Pages 75–94
DOI: https://doi.org/10.26089/NumMet.v23r206
(Mi vmp1051)
 

Methods and algorithms of computational mathematics and their applications

Efficient algorithm for solving the system of Allen–Cahn and Cahn–Hilliard equations: modeling the sintering process

D. I. Prokhorova, Ya. V. Bazaikina, V. V. Lisitsab

a Sobolev Institute of Mathematics, Siberian Branch of Russian Academy of Sciences, Novosibirsk, Russia
b Trofimuk Institute of Petroleum Geology and Geophysics, Siberian Branch of Russian Academy of Sciences, Novosibirsk, Russia
Abstract: In this work, we present an algorithm for solving the system of Allen–Cahn and Cahn–Hilliard equations, which describes the process of sintering. The algorithm does not require significant computational resources and makes possible the sintering simulating of a large number of grains using a computation node with an Intel Xeon E5 2697 v3 CPU and an NVIDIA K40 GPU in a reasonable time. Experiments were carried out to simulate the sintering of sorbent-like structures (packings of spherical particles), for which the efficiency of the algorithm was shown.
Keywords: sintering, phase-field, Cahn-Hilliard equation, Allen-Cahn equation.
Funding agency Grant number
Russian Science Foundation 21–71–20003
Ministry of Science and Higher Education of the Russian Federation 0331–2019–0008
Received: 03.03.2022
Accepted: 02.04.2022
Document Type: Article
UDC: 519.63
Language: Russian
Citation: D. I. Prokhorov, Ya. V. Bazaikin, V. V. Lisitsa, “Efficient algorithm for solving the system of Allen–Cahn and Cahn–Hilliard equations: modeling the sintering process”, Num. Meth. Prog., 23:2 (2022), 75–94
Citation in format AMSBIB
\Bibitem{ProBazLis22}
\by D.~I.~Prokhorov, Ya.~V.~Bazaikin, V.~V.~Lisitsa
\paper Efficient algorithm for solving the system of Allen–Cahn and
Cahn–Hilliard equations: modeling the sintering process
\jour Num. Meth. Prog.
\yr 2022
\vol 23
\issue 2
\pages 75--94
\mathnet{http://mi.mathnet.ru/vmp1051}
\crossref{https://doi.org/10.26089/NumMet.v23r206}
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