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ZENODO
Dataset . 2023
License: CC BY
Data sources: Datacite
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2023
License: CC BY
Data sources: Datacite
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2023
License: CC BY
Data sources: ZENODO
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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Computational results and python files for the work "Divergence-conforming velocity and vorticity approximations for incompressible fluids obtained with minimal facet coupling"

Authors: Lederer, Philip; Kogler, Lukas; Gopalakrishnan, Jay; Schöberl, Joachim;

Computational results and python files for the work "Divergence-conforming velocity and vorticity approximations for incompressible fluids obtained with minimal facet coupling"

Abstract

This repository contains data accompanying the paper "Divergence-conforming velocity and vorticity approximations for incompressible fluids obtained with minimal facet coupling". The implementation is based on the python-interface of the NGSolve open source Finite Element library (ngsolve.org). The file solve_problem_allione.py represents a minimum working example where the proposed MCS/HDG (set the use_MCS flag) method is used to solve the problem from the numerics section of the paper. The files FlowTemplates.py and krylovspace_extension.py contain a somewhat larger and more modular implementation of the proposed method that also features preconditioned iterative solvers, including support for the NgsAMG NGSolve extension library as well as the NGSolve-PETSc interface. The files errors_hdg.pickle, errors_mcs.pickle and kappas.pickle contain the raw data the tables and pictures in the paper were generated from. This data was generated with the scripts conv3d_hdg.py, conv3d_mcs.py and calc_kappas.py which use the FlowTemplates.py infrastructure.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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