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Application of Markov Modeling for Safety Assessment of Self-Diagnostic Programmable Instrumentations and Control Systems
(Centre for Safety Infrastructure Oriented Research and Analysis, Kharkiv, Ukraine; National Aerospace University “KhAI”, Kharkiv, Ukraine; Research and Production Company “Radiy”, Kirovograd, Ukraine, 2016) Butenko, V.; Odarushchenko, O. M.; Kharchenko, V.; Moskalets, V.; Odarushchenko, O. B.; Strjuk, O.; Одарущенко, Олег Миколайович; Одарущенко, Олена Борисівна
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.