Thesis abstract:

«p»This study delves into the critical issue of microbiologically induced corrosion (MIC) in wastewater assets, specifically focusing on its impact on concrete and soil infrastructure. Microorganisms, such as sulfate-reducing bacteria, have been identified as key culprits in the deterioration of these assets, leading to costly repairs and environmental concerns. This research employs predictive modeling techniques to forecast the likelihood of failure in wastewater systems due to MIC-induced corrosion. By considering environmental conditions, microbial activity, and material properties, the models aim to provide early warnings of potential asset failures, allowing for timely maintenance and resource allocation. The findings from this study have the potential to significantly enhance the management and sustainability of wastewater infrastructure, thereby reducing costs and environmental impacts associated with unexpected asset failures.«/p»