Modeling the bacterial oxidation of ferrous iron with Acidithiobacillus ferrooxidans using kriging interpolation

Abstract

A modeling approach of the bacterial oxidation of ferrous iron in batch culture is presented. It is based on the spatial interpolation of experimental data known as kriging interpolation. It is shown that, using the proposed method, the prediction error between model and true system variables is optimal in the sense of minimum variance. The results obtained improve the prediction error associated to the use of the current “knowledge-based” models. Results on modeling the kinetics of the bacterium Acidithiobacillus ferrooxidans, previously called Thiobacillus ferrooxidans, growing in ferrous iron as energy source in a batch airlift reactor are presented. The prediction error bound associated with the model is deduced theoretically and calculated for the application case.