Multi-approach Based Safety Analysis of a Wastewater Treatment System
Résumé
Wastewater treatment systems are critical for protecting eco-systems and public health, yet the prediction of untreated effluent discharges from wastewater treatment plants (WWTPs) and their impact on plant performance remain largely underexplored. In this work, we examine the safety and reliability of a wastewater treatment system serving one of the largest agglomerations in Paris, France. We are interested in predicting failures that lead to untreated effluent discharges into the Seine River. The system comprises two WWTPs connected by a bypass channel designed to mitigate untreated discharges from the plant with lower capacity. Despite flow management efforts, both plants frequently face overloading. This is particularly true during heavy rainfall, which significantly increases the likelihood of untreated discharges. To address this issue, we combine fault tree analysis and machine learning techniques to evaluate vulnerabilities and predict discharges. The approach is based on real-world data and demonstrates promising predictive capabilities despite the challenges of a small dataset. The findings support decision-making efforts to mitigate untreated wastewater discharges and enhance system reliability.