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Activated sludge model 2d calibration with full-scale WWTP data: comparing model parameter identifiability with influent and operational uncertainty

Overview of attention for article published in Bioprocess and Biosystems Engineering, December 2013
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35 Mendeley
Title
Activated sludge model 2d calibration with full-scale WWTP data: comparing model parameter identifiability with influent and operational uncertainty
Published in
Bioprocess and Biosystems Engineering, December 2013
DOI 10.1007/s00449-013-1099-8
Pubmed ID
Authors

Vinicius Cunha Machado, Javier Lafuente, Juan Antonio Baeza

Abstract

The present work developed a model for the description of a full-scale wastewater treatment plant (WWTP) (Manresa, Catalonia, Spain) for further plant upgrades based on the systematic parameter calibration of the activated sludge model 2d (ASM2d) using a methodology based on the Fisher information matrix. The influent was characterized for the application of the ASM2d and the confidence interval of the calibrated parameters was also assessed. No expert knowledge was necessary for model calibration and a huge available plant database was converted into more useful information. The effect of the influent and operating variables on the model fit was also studied using these variables as calibrating parameters and keeping the ASM2d kinetic and stoichiometric parameters, which traditionally are the calibration parameters, at their default values. Such an "inversion" of the traditional way of model fitting allowed evaluating the sensitivity of the main model outputs regarding the influent and the operating variables changes. This new approach is able to evaluate the capacity of the operational variables used by the WWTP feedback control loops to overcome external disturbances in the influent and kinetic/stoichiometric model parameters uncertainties. In addition, the study of the influence of operating variables on the model outputs provides useful information to select input and output variables in decentralized control structures.

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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.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 35 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 3%
Unknown 34 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 12 34%
Student > Master 7 20%
Professor 3 9%
Researcher 3 9%
Other 1 3%
Other 3 9%
Unknown 6 17%
Readers by discipline Count As %
Engineering 7 20%
Environmental Science 6 17%
Chemical Engineering 3 9%
Earth and Planetary Sciences 2 6%
Chemistry 2 6%
Other 2 6%
Unknown 13 37%
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 14 July 2014.
All research outputs
#16,106,935
of 25,457,858 outputs
Outputs from Bioprocess and Biosystems Engineering
#8
of 8 outputs
Outputs of similar age
#189,192
of 320,819 outputs
Outputs of similar age from Bioprocess and Biosystems Engineering
#1
of 3 outputs
Altmetric has tracked 25,457,858 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 8 research outputs from this source. They receive a mean Attention Score of 2.2. This one scored the same or higher as 0 of them.
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 320,819 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 38th percentile – i.e., 38% of its contemporaries scored the same or lower than it.
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. This one has scored higher than all of them