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Numerical modeling of geomaterial fracture using a cohesive crack model in grain-based DEM

Overview of attention for article published in Computational Particle Mechanics, November 2019
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Mentioned by

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1 Facebook page

Citations

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21 Dimensions

Readers on

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14 Mendeley
Title
Numerical modeling of geomaterial fracture using a cohesive crack model in grain-based DEM
Published in
Computational Particle Mechanics, November 2019
DOI 10.1007/s40571-019-00295-4
Authors

Hadi Fathipour-Azar, Jianfeng Wang, Seyed-Mohammad Esmaeil Jalali, Seyed Rahman Torabi

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 14 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 14 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 6 43%
Student > Doctoral Student 3 21%
Student > Master 1 7%
Unknown 4 29%
Readers by discipline Count As %
Engineering 6 43%
Earth and Planetary Sciences 2 14%
Materials Science 1 7%
Energy 1 7%
Unknown 4 29%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 16 November 2019.
All research outputs
#20,590,073
of 23,175,240 outputs
Outputs from Computational Particle Mechanics
#180
of 294 outputs
Outputs of similar age
#277,411
of 326,895 outputs
Outputs of similar age from Computational Particle Mechanics
#4
of 15 outputs
Altmetric has tracked 23,175,240 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 294 research outputs from this source. They receive a mean Attention Score of 1.2. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 326,895 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 15 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.