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Titel:

Sparse identification of truncation errors

Dokumenttyp:
Zeitschriftenaufsatz
Autor(en):
Thaler, Stephan; Paehler, Ludger; Adams, Nikolaus A.
Abstract:
This work presents a data-driven approach to the identification of spatial and temporal truncation errors for linear and nonlinear discretization schemes of Partial Differential Equations (PDEs). Motivated by the central role of truncation errors, for example in the creation of implicit Large Eddy schemes, we introduce the Sparse Identification of Truncation Errors (SITE) framework to automatically identify the terms of the modified differential equation from simulation data. We build on recent...     »
Stichworte:
Data-driven scientific computing; Modified differential equation analysis; Preconditioning; Sparse regression; Truncation error
Dewey Dezimalklassifikation:
620 Ingenieurwissenschaften
Zeitschriftentitel:
Journal of Computational Physics
Jahr:
2019
Band / Volume:
397
Nachgewiesen in:
Scopus
Volltext / DOI:
doi:10.1016/j.jcp.2019.07.049
WWW:
https://www.sciencedirect.com/science/article/pii/S0021999119305352
Verlag / Institution:
Elsevier BV
E-ISSN:
0021-9991
Eingereicht (bei Zeitschrift):
03.04.2019
Angenommen (von Zeitschrift):
20.07.2019
Publikationsdatum:
29.07.2019
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