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Main Authors: Perez, Adalberto, Toosi, Siavash, Olsen, Tim Felle, Markidis, Stefano, Schlatter, Philipp
Format: Preprint
Published: 2025
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Online Access:https://arxiv.org/abs/2504.12301
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author Perez, Adalberto
Toosi, Siavash
Olsen, Tim Felle
Markidis, Stefano
Schlatter, Philipp
author_facet Perez, Adalberto
Toosi, Siavash
Olsen, Tim Felle
Markidis, Stefano
Schlatter, Philipp
contents PySEMTools is a Python-based library for post-processing simulation data produced with high-order hexahedral elements in the context of the spectral element method in computational fluid dynamics. It aims to minimize intermediate steps typically needed when analyzing large files. Specifically, the need to use separate codebases (like the solvers themselves) at post-processing. For this effect, we leverage the use of message passing interface (MPI) for distributed computing to perform typical data processing tasks such as spectrally accurate differentiation, integration, interpolation, and reduced order modeling, among others, on a spectral element mesh. All the functionalities are provided in self-contained Python code and do not depend on the use of a particular solver. We believe that `PySEMTools` provides tools to researchers to accelerate scientific discovery and reduce the entry requirements for the use of advanced methods in computational fluid dynamics.
format Preprint
id arxiv_https___arxiv_org_abs_2504_12301
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle PySEMTools: A library for post-processing hexahedral spectral element data
Perez, Adalberto
Toosi, Siavash
Olsen, Tim Felle
Markidis, Stefano
Schlatter, Philipp
Computational Physics
PySEMTools is a Python-based library for post-processing simulation data produced with high-order hexahedral elements in the context of the spectral element method in computational fluid dynamics. It aims to minimize intermediate steps typically needed when analyzing large files. Specifically, the need to use separate codebases (like the solvers themselves) at post-processing. For this effect, we leverage the use of message passing interface (MPI) for distributed computing to perform typical data processing tasks such as spectrally accurate differentiation, integration, interpolation, and reduced order modeling, among others, on a spectral element mesh. All the functionalities are provided in self-contained Python code and do not depend on the use of a particular solver. We believe that `PySEMTools` provides tools to researchers to accelerate scientific discovery and reduce the entry requirements for the use of advanced methods in computational fluid dynamics.
title PySEMTools: A library for post-processing hexahedral spectral element data
topic Computational Physics
url https://arxiv.org/abs/2504.12301