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Comparison between classical Kelvin-Voigt and fractional derivative Kelvin-Voigt models in prediction of linear viscoelastic behaviour of waste activated sludge

Overview of attention for article published in Science of the Total Environment, September 2017
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Title
Comparison between classical Kelvin-Voigt and fractional derivative Kelvin-Voigt models in prediction of linear viscoelastic behaviour of waste activated sludge
Published in
Science of the Total Environment, September 2017
DOI 10.1016/j.scitotenv.2017.09.206
Pubmed ID
Authors

Ehsan Farno, Jean-Christophe Baudez, Nicky Eshtiaghi

Abstract

Appropriate sewage sludge rheological models are essential for computational fluid dynamic simulation of wastewater treatment processes, in particular aerobic and anaerobic digestions. The liquid-like behaviour of sludge is well documented but the solid-like behaviour remains poorly described despite its importance for dead-zone formation. In this study, classical Kelvin-Voigt model, commonly used for sludge in literature, were compared with fractional derivative Kelvin-Voigt model regarding their predictive ability for describing the solid-like behaviour. Results showed that the fractional Kelvin-Voigt model best fitted the experimental data obtained from creep and frequency sweep tests. Whereas, classical Kelvin-Voigt could not fit the frequency sweep data as this model is not a function of angular velocity. Also, the Kelvin-Voigt model was unable to predict the creep data at low stresses.

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X Demographics

The data shown below were collected from the profile of 1 X user 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 46 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 46 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 10 22%
Student > Master 6 13%
Researcher 6 13%
Student > Bachelor 3 7%
Lecturer 3 7%
Other 6 13%
Unknown 12 26%
Readers by discipline Count As %
Engineering 13 28%
Chemical Engineering 5 11%
Environmental Science 5 11%
Mathematics 2 4%
Unspecified 1 2%
Other 3 7%
Unknown 17 37%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 27 October 2017.
All research outputs
#17,292,294
of 25,382,440 outputs
Outputs from Science of the Total Environment
#19,180
of 29,635 outputs
Outputs of similar age
#209,319
of 326,430 outputs
Outputs of similar age from Science of the Total Environment
#301
of 485 outputs
Altmetric has tracked 25,382,440 research outputs across all sources so far. This one is in the 21st percentile – i.e., 21% of other outputs scored the same or lower than it.
So far Altmetric has tracked 29,635 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.6. This one is in the 24th percentile – i.e., 24% 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 326,430 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 27th percentile – i.e., 27% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 485 others from the same source and published within six weeks on either side of this one. This one is in the 28th percentile – i.e., 28% of its contemporaries scored the same or lower than it.