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Numerical experiments to "Error analysis of second-order local time integration methods for discontinuous Galerkin discretizations of linear wave equations"

Carle, Constantin 1; Hochbruck, Marlis [Beteiligte*r] 1
1 Institut für Angewandte und Numerische Mathematik (IANM), Karlsruher Institut für Technologie (KIT)

Abstract:

This code was used for the numerical experiments in the CRC 1173 Preprint 2023/2 (URL: https://www.waves.kit.edu/downloads/CRC1173_Preprint_2023-2.pdf) by C. Carle and M. Hochbruck.


Zugehörige Institution(en) am KIT Institut für Angewandte und Numerische Mathematik (IANM)
Publikationstyp Forschungsdaten
Publikationsdatum 16.05.2023
Erstellungsdatum 10.05.2023
Identifikator DOI: 10.5445/IR/1000158573
KITopen-ID: 1000158573
Lizenz Creative Commons Namensnennung – Nicht kommerziell – Weitergabe unter gleichen Bedingungen 4.0 International
Projektinformation SFB 1173/2 (DFG, DFG KOORD, SFB 1173/2 2019)
Externe Relationen Siehe auch
Schlagwörter time integration, wave equation, leapfrog method, discontinuous Galerkin method, error analysis, CFL condition, Chebyshev polynomials, local time-stepping, locally implicit
Liesmich

The scripts are intended to reproduce the figures from the preprint

"Error analysis of second-order local time integration methods
for discontinuous Galerkin discretizations of linear wave equations"

by Constantin Carle and Marlis Hochbruck

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Requirements

The codes are tested with

Ubuntu 20.04.2 LTS and Python 3.8.10 and the following version of its modules:

numpy - 1.17.4
scipy

dolfin (fenics) - 2019.2.0.dev0 (including mshr)

matplotlib - 3.1.2
tikzplotlib - 0.9.6
pandas - 0.25.3

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Generation of figures

For the generation of Figure Y, Y=1,2,3, either execute the Python script 'script_figY.py'
in a suitable integrated development environment or run the command
python3 script_figY.py
in a terminal session.

For the generation of Figure 4 first execute the Python script 'script_fig4_data.py'
(via a suitable integrated development environment or in a terminal session)
which generates and saves the data for the figure.
To obtain the figure execute the script 'script_fig4_plot.py'
(the script 'script_fig4_plot_single.py' generates a different view of the data).

Additionally to the plots you can get the tikz-files which were used for
generating the figures in the preprint by setting the Boolean variable 'write_tikz'
from 'False' to 'True' at the beginning of the scripts.

The scripts for Figure 1, 2, 4 run in parallel on all available processors.
The number of used processors can be specified with the
variable 'num_processors_max' (integer). - 1.3.3

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