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Neural network enhanced computations on coarse grids
Linköpings universitet, Matematiska institutionen, Beräkningsmatematik. Linköpings universitet, Tekniska fakulteten. Department of Mathematics and Applied Mathematics, University of Johannesburg, South Africa.ORCID-id: 0000-0002-7972-6183
Linköpings universitet, Matematiska institutionen, Beräkningsmatematik. Linköpings universitet, Tekniska fakulteten.ORCID-id: 0000-0001-9797-3834
2021 (engelsk)Inngår i: Journal of Computational Physics, ISSN 0021-9991, E-ISSN 1090-2716, Vol. 425, artikkel-id 109821Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

Unresolved gradients produce numerical oscillations and inaccurate results. The most straightforward solution to such a problem is to increase the resolution of the computational grid. However, this is often prohibitively expensive and may lead to ecessive execution times. By training a neural network to predict the shape of the solution, we show that it is possible to reduce numerical oscillations and increase both accuracy and efficiency. Data from the neural network prediction is imposed using multiple penalty terms inside the domain.

sted, utgiver, år, opplag, sider
Elsevier, 2021. Vol. 425, artikkel-id 109821
Emneord [en]
Boundary layer, Numerical oscillations, Neural network, Summation-by-parts, Penalty terms, Coarse grids
HSV kategori
Identifikatorer
URN: urn:nbn:se:liu:diva-170823DOI: 10.1016/j.jcp.2020.109821ISI: 000630256300003OAI: oai:DiVA.org:liu-170823DiVA, id: diva2:1478983
Tilgjengelig fra: 2020-10-23 Laget: 2020-10-23 Sist oppdatert: 2021-12-28
Inngår i avhandling
1. Applications of summation-by-parts operators
Åpne denne publikasjonen i ny fane eller vindu >>Applications of summation-by-parts operators
2020 (engelsk)Doktoravhandling, med artikler (Annet vitenskapelig)
Abstract [en]

Numerical solvers of initial boundary value problems will exhibit instabilities and loss of accuracy unless carefully designed. The key property that leads to convergence is stability, which this thesis primarily deals with. By employing discrete differential operators satisfying a so called summation-by-parts property, it is possible to prove stability in a systematic manner by mimicking the continuous analysis if the energy has a bound. The articles included in the thesis all aim to solve the problem of ensuring stability of a numerical scheme in some context. This includes a domain decomposition procedure, a non-conforming grid coupling procedure, an application in high energy physics, and two methods at the intersection of machine learning and summation-by-parts theory.

sted, utgiver, år, opplag, sider
Linköping: Linköping University Electronic Press, 2020. s. 32
Serie
Linköping Studies in Science and Technology. Dissertations, ISSN 0345-7524 ; 2106
HSV kategori
Identifikatorer
urn:nbn:se:liu:diva-171230 (URN)10.3384/diss.diva-171230 (DOI)9789179297534 (ISBN)
Disputas
2021-01-22, Ada Lovelace, B-Building, Campus Valla, Linköping, 13:15 (engelsk)
Opponent
Veileder
Tilgjengelig fra: 2020-11-11 Laget: 2020-11-11 Sist oppdatert: 2021-12-28bibliografisk kontrollert

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Nordström, JanÅlund, Oskar

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