Batch Deterministic and Stochastic Petri nets Modeling for Reliability Quantification for Safety Critical Systems of Nuclear Power Plants

• Published in: Nuclear engineering and design 2023-04, Vol.404, p.112191, Article 112191
• Main Authors: Kumar Jyotish, Nand, Kumar Singh, Lalit, Kumar, Chiranjeev, Singh, Pooja
• Format: Article
• Language: English
• Subjects: Batch Deterministic and Stochastic Petri nets; Markov Chain; Modeling; Nuclear Power Plant; Reliability; Safety Critical Systems
• ISSN: 0029-5493; 1872-759X
• DOI: 10.1016/j.nucengdes.2023.112191

•Instrumentation and control (I&C) systems are crucial in managing and controlling the facilities of nuclear power plant (NPP).•Such systems contain multiple processing nodes that communicate with each other is modelled by a Petri net.•Petri net is used to perform behavioral analysis of safety-critical systems (SCS) to evaluate various dependability metrics.•A novel approach to model and quantify the reliability of SCS using batch deterministic and stochastic Petri nets (BDSPNs).•The paper uses the BDSPN and the continuous time Markov chain for the reliability measurement of SCS. Safety-critical systems (SCS) are essential in maintaining and controlling the nuclear power plant (NPP) facilities, providing feedback on the plant's conditions, and safeguarding it from adverse consequences i.e., SCS plays a vital role in NPP. Thus, failure of such systems can lead to massive financial losses, human resource damage, and environmental degradation. It is, therefore, important that these systems should have a high level of reliability and accuracy. This research introduces a novel method for designing and assessing the reliability of SCS by employing batch deterministic & stochastic Petri nets (BDSPNs) and Markov chain. Our method of reliability evaluation achieved 99.9905% accuracy, proving its effectiveness. This paper illustrates the proposed approach to NPP's Shutdown System (SDS).