Component- and system-level degradation modeling of digital Instrumentation and Control systems based on a Multi-State Physics Modeling Approach

Abstract

A system-level degradation modeling is proposed for the reliability assessment of digital Instrumentation and Control (I&C) systems in Nuclear Power Plants (NPPs). At the component level, we focus on the reliability assessment of a Resistance

A sensitivity analysis for the adequacy assessment of a multi-state physics modeling approach for reliability analysis

“…The RTD-MSPM assumptions are described as follows: To estimate the transition rates, we build the empirical relationship plotted in Figure 10 between τ, t and δ based on the experimental data listed in Tables 5 and 6 (Hashemian, 2011;Yun et al, 2012). For further details on the empirical model, the interested the reader may refer to (Wang et al, 2016). Table 5.…”

“…It is worth pointing out the use of λS(t|δ) as the aging-and environmental-dependent transition rate of the RTD from functioning state to any of the state of the diagram that entails its involvement (i.e., states 0 to 1, and 3 to 5). The cdf P(t|δ) (i.e., the RPS system unreliability when aging and factors affecting the degradation of the RTD are considered) can be estimated by resorting to a two-loop MC simulation (Wang et al, 2016). In few words, the inner loop estimates the RTD failure time, by accounting for both stochastic (the air gap size between the sensing element tip and the thermowell bottom) and deterministic (the RTD age) processes, as described in Section 4.1, whereas the outer loop implements a crude direct Monte Carlo simulation (Zio, 2013) to build the P(t|δ), by sampling all the component failure times from the respective probability distributions.…”

“…MSPM offers the possibility of embedding the physical degradation process into the assessment (Wang et al, 2016).…”

Three-loop Monte Carlo simulation approach to Multi-State Physics Modeling for system reliability assessment

“…On one hand, RTDs are safety -critical components (with large failure rates and corresponding standard deviations, with respect to the other RPS components),and their whose effectiveness ofin promptly detectiong of anomalous temperatures changes is very important for greatly affects the plant operators forcapability to monitoring the NPP operational conditions and to take counteracting measures to avoid system failure (Hashemian, 2011). The On the other hand, RTDs reliability and accuracy of RTDs is important for allow controlling the NPP power rate with confidence, guaranteeing the larger power rates with sufficient enoughsafety margins from the system failure domain (hence, better plant economics) (Yun et al, 2012;Wang et al, 2016). (Wang et al, 2015) According to the RPS scheme of Fig.…”

“…MSPM is a semi-Markov modeling framework that allows inserting physical knowledge on the system failure process, for improving the system reliability assessment by accounting for the effects of both the stochastic degradation process and the uncertain environmental and operational parameters (Unwin et al, 2011;Di Maio et al, 2015;Lin et al, 2015;Wang et al, 2016).…”