Probabilistic fault tree analysis and dynamic redundancy optimization for next-generation avionic flight control systems

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dc.authorid0000-0002-2073-8956
dc.contributor.authorDagal, Idriss
dc.date.accessioned2026-01-31T15:08:22Z
dc.date.available2026-01-31T15:08:22Z
dc.date.issued2026
dc.departmentİstanbul Beykent Üniversitesi
dc.description.abstractThe increasing complexity of next-generation avionic systems necessitates advanced reliability frameworks to ensure fault tolerance while meeting stringent constraints on weight, cost, and certification. This paper presents a novel probabilistic modeling approach that integrates Dynamic Fault Tree Analysis (DFTA), Bayesian Belief Networks, and semi-Markov processes to assess failure probabilities in safety-critical flight control architectures, such as Fly-by-Wire (FBW) systems and Integrated Modular Avionics (IMA). To complement this, a Dynamic Redundancy Optimization (DRO) framework using a Multi-Objective Genetic Algorithm (MOGA) is introduced to optimally allocate redundancy under realistic conditions, including common-cause failures and intermittent faults. The methodology is validated on a triplex-redundant Flight Control Computer (FCC), achieving a 41.8 % improvement in mean time between failures (MTBF) and a 36.5 % reduction in catastrophic event probability compared to static baseline models. Importantly, the framework conforms to DO-178C and ARP4761A standards, ensuring traceability and certification readiness. The results reveal a Pareto frontier representing optimal tradeoffs between reliability enhancements and system resource overheads, providing critical guidance for the design of next-generation avionic systems and regulatory assessment.
dc.identifier.doi10.1016/j.ress.2025.111841
dc.identifier.issn0951-8320
dc.identifier.issn1879-0836
dc.identifier.scopus2-s2.0-105020942559
dc.identifier.scopusqualityQ1
dc.identifier.urihttps://doi.org./10.1016/j.ress.2025.111841
dc.identifier.urihttps://hdl.handle.net/20.500.12662/10667
dc.identifier.volume266
dc.identifier.wosWOS:001608386000009
dc.identifier.wosqualityQ1
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherElsevier Sci Ltd
dc.relation.ispartofReliability Engineering & System Safety
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_WoS_20260128
dc.subjectDynamic fault tree analysis (DFTA)
dc.subjectBayesian networks (BNs)
dc.subjectRedundancy optimization
dc.subjectFlight control systems
dc.subjectAvionics reliability
dc.titleProbabilistic fault tree analysis and dynamic redundancy optimization for next-generation avionic flight control systems
dc.typeArticle

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