Please use this identifier to cite or link to this item: http://dspace.pdaa.edu.ua:8080/handle/123456789/2396
Title: Application of Markov Modeling for Safety Assessment of Self-Diagnostic Programmable Instrumentations and Control Systems
Authors: Butenko, Valentyna
Odarushchenko, Oleg
Kharchenko, Vyacheslav
Moskalets, Viktoriya
Odarushchenko, Elena
Strjuk, Oleksii
Keywords: Instrumentation and Control system
Reactor Trip System
Issue Date: 2016
Publisher: Centre for Safety Infrastructure Oriented Research and Analysis, Kharkiv, Ukraine; National Aerospace University “KhAI”, Kharkiv, Ukraine; Research and Production Company “Radiy”, Kirovograd, Ukraine
Citation: 2. Application of Markov Modeling for Safety Assessment of Self-Diagnostic Programmable Instrumentations and Control Systems. Valentyna Butenko, Oleg Odarushchenko, Vyacheslav Kharchenko, Viktoriya Moskalets, Elena Odarushchenko, Oleksii Strjuk // In CERes Journal, Volume 2, Issue 2, 2016 – P. 61-69
Series/Report no.: ;2
Abstract: Markov modeling is a well-known analytical state space modeling technique which is widely applied for quantitative analysis of safety-critical systems. There are few roadblocks for greater application of Markov modeling: accounting of additional system components increases the model state space and complicates analysis; the non-numerically sophisticated user may find it difficult to select method and tool to provide an accurate analysis of constructed Markov model. Thus, achieving highly trusted result for safety-critical systems is a nontrivial task. In this paper we present the case-study on application of Markov modeling with deep testing the model features, for safety analysis of industrial self-diagnostic, programmable FPGA-based Instrumentation and Control system which operates on Nuclear Power Plant.
URI: http://dspace.pdaa.edu.ua:8080/handle/123456789/2396
Appears in Collections:Міжнародні видання

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