Comprehensiveness of scenarios in the safety assessment of nuclear waste repositories

Tosoni, Edoardo; Salo, Ahti; Govaerts, Joan; Zio, Enrico

doi:10.1016/j.ress.2019.04.012

Cited by 19 publications

(24 citation statements)

References 42 publications

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“…The objectives (7) and (8) aim to minimize the size of the disposal facility such that (7) minimizes the total length of disposal tunnels and (8) minimizes the length of the central tunnel.…”

Section: Objectivesmentioning

confidence: 99%

“…Some of these entities are concentrated more on political or social aspects like to determine where to put a disposal repository [3] or how to route the transfer of the nuclear waste, or hazardous waste in general [4,5]. More safety-related aspects are the optimization of the nuclear safeguards [6,7] and the safety assessment of nuclear waste repositories [8]. In our study, we aim to produce a disposal schedule such that several goals related to all the interim storage, the encapsulation facility, and the disposal facility are taken into account simultaneously with multiobjective optimization.…”

Section: Introductionmentioning

confidence: 99%

“…For the current solution f 3 the decision-maker selects the solution r3q8 due to the low costs and small disposal facility area. Since one motivation for this research was to take into account more goals than just the costs, we are eager to see what happens if we omit the costs and solve the problem with only the first eight objectives (1)- (8). The reference point 3' is similar to the reference point 3 without the value for the costs.…”

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confidence: 99%

“…It can be seen that even if all these solutions suggest the early start of the disposal, they still have some differences. One can improve goals (7) and (8) by disposing of spent fuel with a small volume at the beginning. However, this declines goals (1)-(3), (5), (6) and (9) which can be seen from the solution r3q2.…”

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confidence: 99%

“…The objective values corresponding the selected solutions q = 2 and q = 8 for the modified reference point 3 with objectives (1)-(8).…”

mentioning

confidence: 99%

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Planning the Schedule for the Disposal of the Spent Nuclear Fuel with Interactive Multiobjective Optimization

2019

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Several countries utilize nuclear power and face the problem of what to do with the spent nuclear fuel. One possibility, which is under the scope in this paper, is to dispose of the fuel assemblies in the disposal facility. Before the assemblies can be disposed of, they must cool down their decay heat power in the interim storage. Next, they are loaded into canisters in the encapsulation facility, and finally, the canisters are placed in the disposal facility. In this paper, we model this process as a nonsmooth multiobjective mixed-integer nonlinear optimization problem with the minimization of nine objectives: the maximum number of assemblies in the storage, maximum storage time, average storage time, total number of canisters, end time of the encapsulation, operation time of the encapsulation facility, the lengths of disposal and central tunnels, and total costs. As a result, we obtain the disposal schedule i.e., amount of canisters disposed of periodically. We introduce the interactive multiobjective optimization method using the two-slope parameterized achievement scalarizing functions which enables us to obtain systematically several different Pareto optimal solutions from the same preference information. Finally, a case study adapting the disposal in Finland is given. The results obtained are analyzed in terms of the objective values and disposal schedules.

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Section: Objectivesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

“…The objective values corresponding the selected solutions q = 2 and q = 8 for the modified reference point 3 with objectives (1)-(8).…”

mentioning

confidence: 99%

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Planning the Schedule for the Disposal of the Spent Nuclear Fuel with Interactive Multiobjective Optimization

2019

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Using cross‐impact analysis for probabilistic risk assessment

Salo

Tosoni

Roponen

et al. 2021

Futures & Foresight Science

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Cross-impact analysis is widely employed to inform management and policy decisions based on the formulation of scenarios, defined as combinations of outcomes of relevant uncertainty factors. In this paper, we argue that the use of nonprobabilistic variants of cross-impact analysis is problematic in the context of risk assessment where the usual aim is to produce conservative risk estimates which may exceed but are not smaller than the actual risk level. Then, building on the characterization of probabilistic dependencies, we develop an approach to probabilistic cross-impact analysis which (i) admits several kinds of probabilistic statements about the outcomes of relevant uncertainty factors and their dependencies; (ii) maps such statements into constraints on the joint probability distribution over all possible scenarios; (iii) provides support for preserving the consistency of elicited statements; and (iv) uses mathematical optimization to compute lower and upper bounds on the overall risk level. This approach-which is illustrated with an example from the context of nuclear waste repositories-is useful in that it retains the informativeness of cross-impact statements while ensuring that these statements are interpreted within the coherent framework of probability theory.

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On the boundaries of experimental research on scenario planning: A commentary on Derbyshire et al. (2022)

Salo

2023

Futures & Foresight Science

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Comprehensiveness of scenarios in the safety assessment of nuclear waste repositories

Cited by 19 publications

References 42 publications

Planning the Schedule for the Disposal of the Spent Nuclear Fuel with Interactive Multiobjective Optimization

Planning the Schedule for the Disposal of the Spent Nuclear Fuel with Interactive Multiobjective Optimization

Using cross‐impact analysis for probabilistic risk assessment

On the boundaries of experimental research on scenario planning: A commentary on Derbyshire et al. (2022)

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