Economically optimal strategies for medium-term recovery after a major nuclear reactor accident

D Yumashev, Paul Johnson, P. J. Thomas

    Research output: Contribution to journalArticlepeer-review


    The dynamic process of ground contamination after a major nuclear accident is
    modelled, and the system is then extended to include the transient equations
    describing the three broad countermeasures: food bans, remediation and population movement (relocation and repopulation). Countermeasures are assumed to be applicable once the deposition period has ended and surface contamination measurements have stabilised. A value function is constructed to account for the major economic factors, including allowance for the detrimental effect on human health of radiation exposure. The principle of optimality is then applied by requiring the value function to satisfy the Hamilton-Jacobi-Bellman partial differential equation, yielding an economically optimal combination of the countermeasures at any given moment of time within the recovery period. A classification into Broad Strategies is made in order to explore the similarities in structure of optimal strategies for wide ranges of economic parameter values. Population relocation forms no part of any optimal strategy in the Base Case (or Case I) as parameters are varied over a wide range. Strategies incorporating relocation have a low probability of being optimal even in the low-probability sensitivity studies of Case II, where relocation is imposed immediately the accident happens, and Case III, where the Base Case assumption is reversed of lower economic productivity awaiting those moving from the original to
    the new area. It is concluded that relocation is almost certain to be a less than optimal response after a great many large-scale nuclear accidents.
    Original languageEnglish
    Pages (from-to)63-76
    Number of pages13
    JournalProcess Safety and Environmental Protection
    Issue numberA
    Early online date20 Nov 2017
    Publication statusPublished - Nov 2017


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