Fuzzy TOPSIS-based risk assessment model for effective nuclear decommissioning risk management

Abstract

The dynamics of the nuclear decommissioning project warrant a critical study of the inherent risks and uncertainties. Previous works have identified several nuclear decommissioning risk factors. However, there is no detailed study that systematically ranks the risk factors to aid risk management decision-making. This work presents a fuzzy-based Technique for Order Preference by Similarities to Ideal Solution (Fuzzy TOPSIS) to evaluate the overall risk factors that may arise in a nuclear decommissioning project. The novel analytic tool presented in this work is used to rank eighteen nuclear decommissioning project risk factors according to their severity, for easy risk management. The evaluation and ranking metrics are the Fuzzy Positive Ideal Solution (FPIS), Fuzzy Negative Ideal Solution (FNIP), and Closeness Coefficient (CC). Feedback from nuclear decommissioning experts is processed in linguistic terms and converted into fuzzy values to perform the computation of the closeness coefficient rank for each of the risk factors. The ranking shows the effect of each risk factor on project safety, cost overrun, and time delay. The highest ranked risk factors are the structural condition of the facility before decommissioning, the radiological characteristics of the facility before decommissioning, and the established regulation for the disposal of radioactive material, with closeness coefficients of 0.54351, 0.53239, and 0.48637 respectively. The lowest ranked risk factors are the historical documentation, the availability and condition of waste management facility, and increasing public opposition, with closeness coefficients 0.33806, 0.33355, and 0.28917 respectively. The result shows the capability and the importance of the proposed approach for nuclear decommissioning risk assessment, risk management, and optimal decision-making.