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Attention Score in Context
| Title |
Analytical and computational modelling for wave energy systems: the example of oscillating wave surge converters
|
|---|---|
| Published in |
Acta Mechanica Sinica, June 2017
|
| DOI | 10.1007/s10409-017-0683-6 |
| Pubmed ID | |
| Authors |
Frédéric Dias, Emiliano Renzi, Sarah Gallagher, Dripta Sarkar, Yanji Wei, Thomas Abadie, Cathal Cummins, Ashkan Rafiee |
| Abstract |
The development of new wave energy converters has shed light on a number of unanswered questions in fluid mechanics, but has also identified a number of new issues of importance for their future deployment. The main concerns relevant to the practical use of wave energy converters are sustainability, survivability, and maintainability. Of course, it is also necessary to maximize the capture per unit area of the structure as well as to minimize the cost. In this review, we consider some of the questions related to the topics of sustainability, survivability, and maintenance access, with respect to sea conditions, for generic wave energy converters with an emphasis on the oscillating wave surge converter. New analytical models that have been developed are a topic of particular discussion. It is also shown how existing numerical models have been pushed to their limits to provide answers to open questions relating to the operation and characteristics of wave energy converters. |
X Demographics
The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Ireland | 2 | 67% |
| United Kingdom | 1 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 2 | 67% |
| Members of the public | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 77 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 77 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 14 | 18% |
| Researcher | 10 | 13% |
| Student > Master | 9 | 12% |
| Student > Bachelor | 7 | 9% |
| Professor | 3 | 4% |
| Other | 12 | 16% |
| Unknown | 22 | 29% |
| Readers by discipline | Count | As % |
|---|---|---|
| Engineering | 29 | 38% |
| Mathematics | 5 | 6% |
| Energy | 5 | 6% |
| Unspecified | 2 | 3% |
| Computer Science | 2 | 3% |
| Other | 9 | 12% |
| Unknown | 25 | 32% |
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 28 June 2017.
All research outputs
#13,205,576
of 22,979,862 outputs
Outputs from Acta Mechanica Sinica
#36
of 65 outputs
Outputs of similar age
#154,632
of 317,348 outputs
Outputs of similar age from Acta Mechanica Sinica
#2
of 3 outputs
Altmetric has tracked 22,979,862 research outputs across all sources so far. This one is in the 42nd percentile – i.e., 42% of other outputs scored the same or lower than it.
So far Altmetric has tracked 65 research outputs from this source. They receive a mean Attention Score of 3.0. This one is in the 44th percentile – i.e., 44% 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 317,348 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 50% of its contemporaries.
We're also able to compare this research output to 3 others from the same source and published within six weeks on either side of this one.