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A shear-lag model for laminated beams with extreme modulus mismatch between layers

Overview of attention for article published in Mechanics of Materials, January 2024
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About this Attention Score

  • Among the highest-scoring outputs from this source (#31 of 329)
  • Good Attention Score compared to outputs of the same age (72nd percentile)
  • High Attention Score compared to outputs of the same age and source (90th percentile)

Mentioned by

twitter
6 X users

Readers on

mendeley
2 Mendeley
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Title
A shear-lag model for laminated beams with extreme modulus mismatch between layers
Published in
Mechanics of Materials, January 2024
DOI 10.1016/j.mechmat.2023.104844
Authors

Zheliang Wang, Hao Sheng, Xinyi Lin, Yifan Rao, Jia Liu, Nanshu Lu

X Demographics

X Demographics

The data shown below were collected from the profiles of 6 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 2 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 2 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 1 50%
Unknown 1 50%
Readers by discipline Count As %
Unspecified 1 50%
Unknown 1 50%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 5. 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 10 November 2023.
All research outputs
#7,037,514
of 25,394,764 outputs
Outputs from Mechanics of Materials
#31
of 329 outputs
Outputs of similar age
#89,418
of 332,959 outputs
Outputs of similar age from Mechanics of Materials
#1
of 10 outputs
Altmetric has tracked 25,394,764 research outputs across all sources so far. This one has received more attention than most of these and is in the 72nd percentile.
So far Altmetric has tracked 329 research outputs from this source. They receive a mean Attention Score of 2.4. This one has done particularly well, scoring higher than 90% of its peers.
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 332,959 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 72% of its contemporaries.
We're also able to compare this research output to 10 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them