Analysis reveals that D2T2 enhances reliability predictions in boiling water reactors, suggesting better safety applications.
The availability of accurate models capturing the realistic behaviour of complex systems is critical for the safe operation and optimal management of nuclear installations. However, the dynamic nature of such systems and the resulting dense network of interdependencies existing among their parts are no match for current risk modelling techniques, which rely on oversimplifying premises. Dependencies are often simplified or ignored, with conservative assumptions introduced to compensate, leading to results of uncertain realism. Alternative methods address these limitations but often remain difficult to scale, interpret, or integrate into established Probabilistic Safety Assessment practice. The Dynamic and Dependent Tree Theory (D2T2) offers a bridging framework that preserves the familiar FT/ET structure while enabling dependencies to be represented directly at the basic-event, intermediate, or subsystem level through compact submodels. This paper applies D2T2 to a loss of main feed water accident in a boiling water reactor, capturing dependencies from maintenance strategies to subsystem interactions. Results show that D2T2 improves reliability predictions compared with conventional FT/ET, aligns closely with dynamic benchmarks, and remains computationally tractable. Beyond accuracy, the approach makes modelling assumptions explicit and transparent, promoting deeper system understanding while lowering barriers to adoption in safety-critical applications.
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Tolo et al. (2025) studied this question.
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