The power of precursors: An empirical assessment of nuclear power risks

Abstract

The opposition in some countries to including nuclear power in future sustainable energy portfolios—in part due to “nuclear dread”—often has limited quantitative scientific foundation of the real benefits and risks. This has been amplified by the lack of sound estimates of operational risk due to the scarcity of the relevant empirical data. In order to address this gap, we use the largest open database on accident precursors along with our in-house generic probabilistic safety assessment models to conduct a comprehensive statistical study of operational risks in the civil nuclear sector. We find that the distribution of precursor severities follows a Pareto distribution, and we observe a runaway Dragon Kings regime for the most significant events. Based on our findings, we have determined that exogenous factors account for 95% of the risk associated with nuclear power. By addressing these factors in new reactor designs, we estimate that the frequency of accidents similar to the Fukushima Daiichi level can be reduced to about one every 300 years for the global fleet. Finally, our study highlights the importance and need for international cooperation focused on constructing comprehensive blockchains of accident precursors.