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ZENODO
Dataset . 2022
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 . 2022
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/
ZENODO
Dataset . 2022
License: CC BY
Data sources: Datacite
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Original datasets for : A computational homogenization framework with enhanced localization criterion for macroscopic cohesive failure in heterogeneous materials

Research datakeyboard_double_arrow_right Dataset 11 Feb 2022 English Publisher:ZenodoFunded by:NWO | Multiscale characterizati...
Authors: Ke, Lu; van der Meer, Frans;

doi: 10.5281/zenodo.6044934 , 10.5281/zenodo.6044933

Original datasets for : A computational homogenization framework with enhanced localization criterion for macroscopic cohesive failure in heterogeneous materials

Abstract

The original datasets from tests in the article: A computational homogenization framework with enhanced localization criterion for macroscopic cohesive failure in heterogeneous materials. The results are produced by the in-house fem codes of the Computational Mechanics group, CiTG, TU delft.

Financial support from the Dutch Research Council NWO under Vidi grant 16464 is gratefully acknowledged.

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Keywords

computational homogenization, dataset, phantom node method, multiscale modeling, FE2

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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.
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