Formal definition of coherency and computation of minimal cut sequences for binary dynamic and repairable systems

Preventive risk assessment of a complex system rely on a dynamic models which describe the link between the system failure and the scenarios of failure and repair events from its components. The qualitative analyses of a binary dynamic and repairable system is aiming at computing and analyse the scenarios that lead to the system failure. Since such systems describe a large set of those, only the most representative ones, called Minimal Cut Sequences (MCS), are of interest for the safety engineer. The lack of a formal definition for the MCS has generated multiple definitions either specific to a given model (and thus not generic) or informal. This work proposes i) a formal framework and definition for the MCS while staying independent of the reliability model used, ii) the methodology to compute them using property extracted from their formal definition, iii) an extension of the formal framework for multi-states components in order to perform the qualitative analyses of Boolean logic Driven Markov Processes (BDMP) models. Under the hypothesis that the scenarios implicitly described by any reliability model can always be represented by a finite automaton, this work is defining the coherency for dynamic and repairable systems as the way to give a minimal representation of all scenarios that are leading to the system failure.

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Source https://theses.hal.science/tel-00910331
Author Chaux, Pierre-Yves
Maintainer CCSD
Last Updated May 8, 2026, 01:43 (UTC)
Created May 8, 2026, 01:43 (UTC)
Identifier NNT: 2013DENS0014
Language fr
Rights https://about.hal.science/hal-authorisation-v1/
contributor Laboratoire Universitaire de Recherche en Production Automatisée (LURPA) ; École normale supérieure - Cachan (ENS Cachan)-Université Paris-Sud - Paris 11 (UP11)
creator Chaux, Pierre-Yves
date 2013-04-15T00:00:00
harvest_object_id 3424c761-c88a-4baa-b106-1411b1d99fdf
harvest_source_id 3374d638-d20b-4672-ba96-a23232d55657
harvest_source_title test moissonnage SELUNE
metadata_modified 2026-03-31T00:00:00
set_spec type:THESE