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Train small, model big: Scalable physics simulators via reduced order modeling and domain decomposition

Overview of attention for article published in Computer Methods in Applied Mechanics & Engineering, July 2024
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (52nd percentile)
  • Good Attention Score compared to outputs of the same age and source (73rd percentile)

Mentioned by

twitter
2 X users

Readers on

mendeley
4 Mendeley
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Title
Train small, model big: Scalable physics simulators via reduced order modeling and domain decomposition
Published in
Computer Methods in Applied Mechanics & Engineering, July 2024
DOI 10.1016/j.cma.2024.117041
Authors

Seung Whan Chung, Youngsoo Choi, Pratanu Roy, Thomas Moore, Thomas Roy, Tiras Y. Lin, Du T. Nguyen, Christopher Hahn, Eric B. Duoss, Sarah E. Baker

Timeline

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X Demographics

X Demographics

The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
As of 1 July 2024, you may notice a temporary increase in the numbers of X profiles with Unknown location. Click here to learn more.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 4 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 4 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 2 50%
Professor 1 25%
Unknown 1 25%
Readers by discipline Count As %
Physics and Astronomy 1 25%
Engineering 1 25%
Unknown 2 50%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 22 May 2024.
All research outputs
#17,030,251
of 26,798,288 outputs
Outputs from Computer Methods in Applied Mechanics & Engineering
#807
of 1,911 outputs
Outputs of similar age
#140,783
of 316,282 outputs
Outputs of similar age from Computer Methods in Applied Mechanics & Engineering
#5
of 19 outputs
Altmetric has tracked 26,798,288 research outputs across all sources so far. This one is in the 34th percentile – i.e., 34% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,911 research outputs from this source. They receive a mean Attention Score of 2.4. This one has gotten more attention than average, scoring higher than 55% 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 316,282 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 52% of its contemporaries.
We're also able to compare this research output to 19 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 73% of its contemporaries.