Sensitivity analysis of the semiempirical model for the growth of the indigenous Acidithiobacillus thiooxidans

Based on the concept of transport phenomena and driving force, we had previously developed a semiempirical model, in which only one mathematical equation and three parameters ( K L, B L, and C L) are required to describe the complicated bacterial growth of the indigenous Acidithiobacillus thiooxidan...

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Bibliographic Details
Published in:Chemical engineering journal (Lausanne, Switzerland : 1996) Switzerland : 1996), 2007-05, Vol.129 (1), p.105-112
Main Authors: Liu, Hsuan-Liang, Yang, Fu-Chiang, Huang, Chih-Hung, Fang, Hsu-Wei, Cheng, Yung-Chu
Format: Article
Language:English
Subjects:
Acidithiobacillus thiooxidans
Applied sciences
Bioleaching
Chemical engineering
Exact sciences and technology
Morris method
Semiempirical model
Sensitivity analysis
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Summary:Based on the concept of transport phenomena and driving force, we had previously developed a semiempirical model, in which only one mathematical equation and three parameters ( K L, B L, and C L) are required to describe the complicated bacterial growth of the indigenous Acidithiobacillus thiooxidans. In order to determine the effects of these parameters, sensitivity analysis based on Morris method was further conducted in this study. The results show that K L, B L, and C L are closely related to the maximal cell concentration, the growth rate in the exponential phase, and the residual time in the lag phase, respectively. The effects of four important cultivation factors: the concentrations of elemental sulfur (S 0), CaCl 2, MnSO 4, and the initial pH, on these three parameters were also analyzed. The results show that the concentration of elemental sulfur exhibits positive correlations with K L and C L; whereas it exhibits a negative correlation with B L. We have subsequently developed three regression equations to predict the values of these three parameters with the concentration of elemental sulfur as the sole information available. These parameters can be further fed into the semiempirical model for predicting the bacterial growth of the indigenous A. thiooxidans with high accuracy.
ISSN:1385-8947
1873-3212
DOI:10.1016/j.cej.2006.10.011