Use of Bayesian Methods in the Process of Uranium Bioleaching by Acidithiobacillus ferrooxidans
Year: 2023
Type: article
Abstract: 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.
Source: Applied Sciences
DOI: 10.3390/app14010109
Institution: Universidade Federal do Pará
Language: English
Subfield: Metals and Alloys
Field: Materials Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,558
OpenAlex ID: W4390111902
