| Title |
Optimal counter-current exchange networks
|
|---|---|
| Published in |
Physical Review E: Statistical, Nonlinear, and Soft Matter Physics, November 2016
|
| DOI | 10.1103/physreve.94.052410 |
| Pubmed ID | |
| Authors |
Robert S. Farr, Yong Mao |
| Abstract |
We present a general analysis of exchange devices linking their efficiency to the geometry of the exchange surface and supply network. For certain parameter ranges, we show that the optimal exchanger consists of densely packed pipes which can span a thin sheet of large area (an "active layer"), which may be crumpled into a fractal surface and supplied with a fractal network of pipes. We derive the efficiencies of such exchangers, showing the potential for significant gains compared to regular exchangers (where the active layer is flat), using parameters relevant to biological systems. |
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 % |
|---|---|---|
| Members of the public | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 8 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 8 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 2 | 25% |
| Professor | 1 | 13% |
| Student > Bachelor | 1 | 13% |
| Student > Doctoral Student | 1 | 13% |
| Unknown | 3 | 38% |
| Readers by discipline | Count | As % |
|---|---|---|
| Physics and Astronomy | 2 | 25% |
| Engineering | 2 | 25% |
| Medicine and Dentistry | 1 | 13% |
| Chemistry | 1 | 13% |
| Unknown | 2 | 25% |
Attention Score in Context
This research output has an Altmetric Attention Score of 4. 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 30 May 2017.
All research outputs
#7,782,070
of 25,385,509 outputs
Outputs from Physical Review E: Statistical, Nonlinear, and Soft Matter Physics
#2,899
of 20,990 outputs
Outputs of similar age
#127,730
of 415,878 outputs
Outputs of similar age from Physical Review E: Statistical, Nonlinear, and Soft Matter Physics
#42
of 367 outputs
Altmetric has tracked 25,385,509 research outputs across all sources so far. This one has received more attention than most of these and is in the 69th percentile.
So far Altmetric has tracked 20,990 research outputs from this source. They receive a mean Attention Score of 2.9. This one has done well, scoring higher than 85% 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 415,878 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 68% of its contemporaries.
We're also able to compare this research output to 367 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 88% of its contemporaries.