↓ Skip to main content

Boundary element method for normal non-adhesive and adhesive contacts of power-law graded elastic materials

Overview of attention for article published in Computational Mechanics, August 2017
Altmetric Badge

About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (54th percentile)
  • Good Attention Score compared to outputs of the same age and source (66th percentile)

Mentioned by

wikipedia
2 Wikipedia pages

Citations

dimensions_citation
28 Dimensions

Readers on

mendeley
30 Mendeley
Title
Boundary element method for normal non-adhesive and adhesive contacts of power-law graded elastic materials
Published in
Computational Mechanics, August 2017
DOI 10.1007/s00466-017-1461-9
Authors

Qiang Li, Valentin L. Popov

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 30 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 30 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 5 17%
Professor 4 13%
Student > Bachelor 3 10%
Student > Master 3 10%
Other 3 10%
Other 3 10%
Unknown 9 30%
Readers by discipline Count As %
Engineering 14 47%
Physics and Astronomy 2 7%
Computer Science 1 3%
Materials Science 1 3%
Chemical Engineering 1 3%
Other 0 0%
Unknown 11 37%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 13 April 2018.
All research outputs
#7,543,662
of 23,015,156 outputs
Outputs from Computational Mechanics
#78
of 256 outputs
Outputs of similar age
#120,772
of 317,988 outputs
Outputs of similar age from Computational Mechanics
#2
of 6 outputs
Altmetric has tracked 23,015,156 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 256 research outputs from this source. They receive a mean Attention Score of 3.7. This one is in the 47th percentile – i.e., 47% 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 317,988 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 54% of its contemporaries.
We're also able to compare this research output to 6 others from the same source and published within six weeks on either side of this one. This one has scored higher than 4 of them.