Application of Markov Modeling for Safety Assessment of Self-Diagnostic Programmable Instrumentations and Control Systems
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Date
2016
Authors
Butenko, V.
Odarushchenko, O. M.
Kharchenko, V.
Moskalets, V.
Odarushchenko, O. B.
Strjuk, O.
Одарущенко, Олег Миколайович
Одарущенко, Олена Борисівна
Journal Title
Journal ISSN
Volume Title
Publisher
Centre for Safety Infrastructure Oriented Research and Analysis, Kharkiv, Ukraine; National Aerospace University “KhAI”, Kharkiv, Ukraine; Research and Production Company “Radiy”, Kirovograd, Ukraine
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.
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Keywords
Instrumentation and Control system, Reactor Trip System
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