Of Disasters and Dragon Kings: A Statistical Analysis of Nuclear Power Incidents & Accidents
Spencer Wheatley, Benjamin Sovacool, and Didier Sornette

TL;DR
This paper conducts a comprehensive statistical analysis of nuclear incidents, revealing heavy-tailed damage distributions, the presence of dragon-king phenomena, and inconsistencies in the INES severity scale, with implications for risk assessment.
Contribution
It provides the largest dataset analysis to date, identifying heavy-tailed damage distributions, dragon-king effects, and proposing revisions to the INES scale for consistency.
Findings
Damage distribution follows a Pareto tail with index 0.55.
The largest event accounts for 60% of total damages.
There is a 50% chance of a Fukushima-sized event in 50 years.
Abstract
We provide, and perform a risk theoretic statistical analysis of, a dataset that is 75 percent larger than the previous best dataset on nuclear incidents and accidents, comparing three measures of severity: INES (International Nuclear Event Scale), radiation released, and damage dollar losses. The annual rate of nuclear accidents, with size above 20 Million US$, per plant, decreased from the 1950s until dropping significantly after Chernobyl (April, 1986). The rate is now roughly stable at 0.002 to 0.003, i.e., around 1 event per year across the current fleet. The distribution of damage values changed after Three Mile Island (TMI; March, 1979), where moderate damages were suppressed but the tail became very heavy, being described by a Pareto distribution with tail index 0.55. Further, there is a runaway disaster regime, associated with the "dragon-king" phenomenon, amplifying the risk…
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Taxonomy
TopicsRisk Perception and Management
