Sensitivity and Uncertainty Analysis of Accident Management Strategies Involving Multiple Decisions

Abstract

A framework for assessing severe accident management strategies is presented using a new analytical tool, namely, influence diagrams. This framework includes multiple and sequential decisions, sensitivity analysis, and uncertainty propagation, and is applied to a proposed set of strategies for a pressurized water reactor station blackout sequence. The influence diagram associated with these strategies is constructed and evaluated. Each decision variable, represented by a node in the influence diagram, has an uncertainty distribution associated with it. Using the mean value of these distributions, a best estimate assessment is performed, and each strategy is ranked with respect to the conditional frequency of early containment failure (ECF). For the preferred alternative, the sensitivity of the results to values of the input variables is investigated. The sensitivity of the ranking itself is then considered. The distributions of the uncertain variables are also propagated through the influence diagram to rank the alternatives with respect to the uncertainty associated with the calculated conditional frequency of ECF. Finally, the sensitivity of the variance of the output distribution, given the preferred decision alternative, to the uncertainty of the input variables is investigated.

Cite this work

No public copy is stored for this record, so only the metadata is cited.

Stored only when both papers are in the corpus — 10 citations exist upstream.

Papers that cite the same references — the relational fallback while embeddings are still backfilling.