Butenko, V.Odarushchenko, O. M.Kharchenko, V.Moskalets, V.Odarushchenko, O. B.Strjuk, O.Одарущенко, Олег МиколайовичОдарущенко, Олена Борисівна2019-02-142019-02-1420162. 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. 61-69https://dspace.pdau.edu.ua/handle/123456789/2396Markov 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.enInstrumentation and Control systemReactor Trip SystemArticle