| Title |
Warm starting the projected Gauss–Seidel algorithm for granular matter simulation
|
|---|---|
| Published in |
Computational Particle Mechanics, November 2015
|
| DOI | 10.1007/s40571-015-0088-x |
| Authors |
Da Wang, Martin Servin, Tomas Berglund |
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.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 2 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 50% |
| Members of the public | 1 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 6 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Sweden | 1 | 17% |
| Unknown | 5 | 83% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 2 | 33% |
| Other | 1 | 17% |
| Lecturer > Senior Lecturer | 1 | 17% |
| Student > Master | 1 | 17% |
| Unknown | 1 | 17% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 2 | 33% |
| Chemical Engineering | 1 | 17% |
| Physics and Astronomy | 1 | 17% |
| Engineering | 1 | 17% |
| Unknown | 1 | 17% |
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 18 March 2018.
All research outputs
#14,638,545
of 23,891,012 outputs
Outputs from Computational Particle Mechanics
#49
of 298 outputs
Outputs of similar age
#202,096
of 392,104 outputs
Outputs of similar age from Computational Particle Mechanics
#4
of 18 outputs
Altmetric has tracked 23,891,012 research outputs across all sources so far. This one is in the 37th percentile – i.e., 37% of other outputs scored the same or lower than it.
So far Altmetric has tracked 298 research outputs from this source. They receive a mean Attention Score of 1.2. This one has done well, scoring higher than 83% 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 392,104 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 47th percentile – i.e., 47% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 18 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 83% of its contemporaries.