Failure Conditions Assessment of Complex Water Systems Using Fuzzy Logic

Climate change, energy transition, population growth and other natural and anthropogenic impacts, combined with outdated (unfashionable) infrastructure, can force Dam and Reservoir Systems (DRS) operation outside of the design envelope (adverse operating conditions). Since there is no easy way to redesign or upgrade the existing DRSs to mitigate against all the potential failure situations, Digital Twins (DT) of DRSs are required to assess system's performance under various what-if scenarios. The current state of practice in failure modelling is that failures (system's not performing at the expected level or not at all) are randomly created and implemented in simulation models. That approach helps in identifying the riskiest parts (subsystems) of the DRS (risk-based approach), but does not consider hazards leading to failures, their occurrence probabilities or subsystem failure exposure. To overcome these drawbacks, this paper presents a more realistic failure scenario generator based on a causal approach. Here, the novel failure simulation approach utilizes fuzzy logic reasoning to create DRS failures based on hazard severity and subsystems' reliability. Combined with the system dynamics (SD) model this general failure simulation tool is designed to be used with any DRS. The potential of the proposed method is demonstrated using the Pirot DRS case study in Serbia over a 10-year simulation period. Results show that even occasional hazards (as for more than 97% of the simulation there were no hazards), combined with outdated infrastructure can reduce DRS performance by 50%, which can help in identifying possible hidden failure risks and support system maintenance prioritization.

Automated summary

Climate change, energy transition, population growth, and outdated infrastructure can cause Dam and Reservoir Systems (DRS) to operate outside of their design envelope. To assess system performance under different scenarios, Digital Twins (DT) of DRSs are necessary. This paper presents a more realistic failure scenario generator based on a causal approach, utilizing fuzzy logic reasoning to create DRS failures based on hazard severity and subsystem reliability. The proposed method was demonstrated using a case study of the Pirot DRS in Serbia, showing that occasional hazards combined with outdated infrastructure can significantly reduce DRS performance and identify hidden failure risks.