Estimating the kinetic parameters of activated sludge storage using weighted non-linear least-squares and accelerating genetic algorithm

Fang, Fang, Ni, Bing-Jie and Yu, Han-Qing (2009) Estimating the kinetic parameters of activated sludge storage using weighted non-linear least-squares and accelerating genetic algorithm. Water Research, 43 10: 2595-2604. doi:10.1016/j.watres.2009.01.002


Author Fang, Fang
Ni, Bing-Jie
Yu, Han-Qing
Title Estimating the kinetic parameters of activated sludge storage using weighted non-linear least-squares and accelerating genetic algorithm
Journal name Water Research   Check publisher's open access policy
ISSN 0043-1354
1879-2448
Publication date 2009-06
Sub-type Article (original research)
DOI 10.1016/j.watres.2009.01.002
Volume 43
Issue 10
Start page 2595
End page 2604
Total pages 10
Place of publication London United Kingdom
Publisher I W A Publishing
Language eng
Formatted abstract
In this study, weighted non-linear least-squares analysis and accelerating genetic algorithm are integrated to estimate the kinetic parameters of substrate consumption and storage product formation of activated sludge. A storage product formation equation is developed and used to construct the objective function for the determination of its production kinetics. The weighted least-squares analysis is employed to calculate the differences in the storage product concentration between the model predictions and the experimental data as the sum of squared weighted errors. The kinetic parameters for the substrate consumption and the storage product formation are estimated to be the maximum heterotrophic growth rate of 0.12 1/h, the yield coefficient of 0.44 mg CODX/mg CODS (COD, chemical oxygen demand) and the substrate half saturation constant of 16.9 mg/L, respectively, by minimizing the objective function using a real-coding-based accelerating genetic algorithm. Also, the fraction of substrate electrons diverted to the storage product formation is estimated to be 0.43 mg CODSTO/mg CODS. The validity of our approach is confirmed by the results of independent tests and the kinetic parameter values reported in literature, suggesting that this approach could be useful to evaluate the product formation kinetics of mixed cultures like activated sludge. More importantly, as this integrated approach could estimate the kinetic parameters rapidly and accurately, it could be applied to other biological processes
Keyword Accelerating genetic algorithm (AGA)
Activated sludge
Kinetic parameter estimation
Storage product
Sequencing Batch Reactor
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status Non-UQ

Document type: Journal Article
Sub-type: Article (original research)
Collection: Advanced Water Management Centre Publications
 
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