Transformation of deterministic models into state space models for safety analysis of safety critical systems: A case study of NPP

Abstract

The state space models has been successfully applied in engineering, statistics, computer science and economics to solve a broad range of dynamical systems problems; like safety analysis, reliability analysis, performability analysis, etc. However, embedding the complete and accurate system requirements in such models is quite challenging. Analyzing model with incomplete or inaccurate requirements gives inaccurate results. UML is a proven and easy approach to capture all the system requirements. This paper proposes a methodology to transform the UML model into the state space model. The resultant model will embed all the system requirements and hence can be used to analyze the critical attributes of the systems. The methodology is validated on 13 sets of operational profile of different safety critical systems of Nuclear Power Plant and shown on Reactor Core Isolation Cooling System (RCICS). © 2017 Elsevier Ltd