Use of Bayesian Methods in the Process of Uranium Bioleaching by Acidithiobacillus ferrooxidans

This research is focused on investigating the utilization of Bayesian methodologies, specifically the Markov Chain Monte Carlo method, as well as filter sampling by importance and sequential resampling. The objective is to estimate kinetic parameters and state variables associated with the uranium b...

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Bibliographic Details
Published in:Applied sciences 2024-01, Vol.14 (1), p.109
Main Authors: Cardoso, Altair Costa, Dias, Camila Santana, Moura, Carlos Henrique Rodrigues de, Ferreira, Josiel Lobato, Rodrigues, Emerson Cardoso, Macêdo, Emanuel Negrão, Estumano, Diego Cardoso, Viegas, Bruno Marques
Format: Article
Language:English
Subjects:
Acidithiobacillus ferrooxidans
Bacteria
Cell growth
Kinetics
Markov analysis
Markov Chain Monte Carlo method
Mathematical models
Metabolism
Metabolites
Metals
Microorganisms
Nuclear energy
Nuclear power plants
Ordinary differential equations
Oxidation
Parameter estimation
SIR particle filter
Sulfur
Uranium
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Summary:This research is focused on investigating the utilization of Bayesian methodologies, specifically the Markov Chain Monte Carlo method, as well as filter sampling by importance and sequential resampling. The objective is to estimate kinetic parameters and state variables associated with the uranium bioleaching process by Acidithiobacillus ferrooxidans. Experimental data of cell concentration, uranium concentration, and concentrations of ferrous and ferric ions, obtained from literature, were employed. These measurements were evaluated using a mathematical model expressed by a system of ordinary differential equations. Three different mathematical models were evaluated, considering different uncertainties in experimental measurements and mathematical models (1% and 5%). The estimation results presented a good fit to the experimental data, with coefficients of determination in the range of 0.95 to 0.99. The validation of the mathematical models was obtained by reproducing the experimental measurements and the Bayesian techniques proved to be suitable for application in the bioleaching process.
ISSN:2076-3417
2076-3417
DOI:10.3390/app14010109