A Multi-State Physics Modeling approach for the reliability assessment of Nuclear Power Plants piping systems. (June 2015)

• Record Type: Journal Article
• Authors: Di Maio, Francesco; Colli, Davide; Zio, Enrico; Tao, Liu; Tong, Jiejuan
• Is Part Of: Annals of nuclear energy. Volume 80(2015:Jun.)
• Page Start: 151
• Page End: 165
• Publication Date: 2015-06
• Subjects: Piping reliability -- Multi-State Physics Modeling -- Degradation process -- Markov Chain Model -- Monte Carlo -- Time-dependant transition rates -- Nuclear Power Plant; Nuclear energy -- Periodicals; Nuclear engineering -- Periodicals; 621.4805
• DOI: 10.1016/j.anucene.2015.02.007
• Languages: English
• ISSNs: 0306-4549

Abstract

Highlights: We model piping systems degradation of Nuclear Power Plants under uncertainty. We use Multi-State Physics Modeling (MSPM) to describe a continuous degradation process. We propose a Monte Carlo (MC) method for calculating time-dependent transition rates. We apply MSPM to a piping system undergoing thermal fatigue. Abstract: A Multi-State Physics Modeling (MSPM) approach is here proposed for degradation modeling and failure probability quantification of Nuclear Power Plants (NPPs) piping systems. This approach integrates multi-state modeling to describe the degradation process by transitions among discrete states (e.g., no damage, micro-crack, flaw, rupture, etc.), with physics modeling by (physic) equations to describe the continuous degradation process within the states. We propose a Monte Carlo (MC) simulation method for the evaluation of the time-dependent transition rates between the states of the MSPM. Accountancy is given for the uncertainty in the parameters and external factors influencing the degradation process. The proposed modeling approach is applied to a benchmark problem of a piping system of a Pressurized Water Reactor (PWR) undergoing thermal fatigue. The results are compared with those obtained by a continuous-time homogeneous Markov Chain Model.