Dynamic Reliability Models for Multiple Dependent Competing Degradation Processes

International audienceThis paper presents a holistic treatment to multiple dependent competing degradation processes, by employing the piecewise-deterministic Markov process (PDMP) modeling framework. The proposed method can handle the dependencies between physics-based models, between multi-state models and between these two types of models. A Monte Carlo simulation algorithm is developed to compute the components/systems reliability. A case study on one subsystem of the residual heat removal system (RHRS) of a nuclear power plant is illustrated

Identifying Intraspecific Variation in Venom Yield of Chinese Cobra (Naja atra) from Ten Populations in Mainland China

Detailed information on venom yield is helpful in preparing antivenoms and treating snakebites, but such information is lacking for many species of venomous snakes. The Chinese cobra (Naja atra) is a large sized, venomous snake commonly found in southeastern China, where it causes a heavy burden of snakebites. To examine the effects of various factors (morphology, sex, age, season, and geographical origin) on the venom yield in this snake, we collected venom samples of 446 individuals (426 adults and 20 neonates) from 10 populations of N. atra over an eight-year period. We used two variables, lyophilized venom mass (venom yield) and solid content of venom (% solids), to quantify the venom yield. We used linear regression analysis to check if venom yield was related to morphological factors, one-way ANOVA and one-way ANCOVA to detect the sexual, ontogenetic, and geographic variation in venom yield, and repeated-measures ANOVA to examine seasonal shifts in venom yield. Our results indicate that venom yield of N. atra is positively related to the morphological traits examined, with male snakes expelling more venom than females. Venom yield in N. atra was age-related, with elder snakes always expelling more venom than younger ones. Geographic variation in venom yield was also observed, while seasonal variation was not. The solid content of venom was lower in males than in females, but this was not related to morphology, season, age, or geography. Our findings suggest that venom yield in N. atra is influenced by multiple factors, as well as by the interactions among these factors

MODELING MULTIPLE DEPENDENT COMPETING DEGRADATIONS UNDER EPISTEMIC UNCERTAINTY VIA PDMP

International audiencePiecewise-deterministic Markov process (PDMP) modeling framework can handle the dependencies between physics-based models, between multi-state models and between these two types of models. Epistemic uncertainty can arise due to the incomplete or imprecise knowledge about the degradation processes and the governing parameters: to take into account this, we describe the parameters of the PDMP model as fuzzy numbers. In this paper, we extend the finite-volume (FV) method to quantify the (fuzzy) reliability of the system. The proposed method is tested on one subsystem of the residual heat removal system (RHRS) of a nuclear power plant, and a comparison is offered with a Monte Carlo (MC) simulation solution

Multi-State Physics Model for the Reliability Assessment of a Component under Degradation Processes and Random Shocks

International audienceWe extend a multi-state physics model (MSPM) framework for component reliability assessment by including semi-Markov and random shock processes. Dependences between the two processes are considered. A Monte Carlo simulation algorithm is developed to compute component reliability. An example is illustrated with respect to a literature case study

Dynamic Reliability Models for Multiple Dependent Competing Degradation Processes

International audienceThis paper presents a holistic treatment to multiple dependent competing degradation processes, by employing the piecewise-deterministic Markov process (PDMP) modeling framework. The proposed method can handle the dependencies between physics-based models, between multi-state models and between these two types of models. A Monte Carlo simulation algorithm is developed to compute the components/systems reliability. A case study on one subsystem of the residual heat removal system (RHRS) of a nuclear power plant is illustrated

MODELING MULTIPLE DEPENDENT COMPETING DEGRADATIONS UNDER EPISTEMIC UNCERTAINTY VIA PDMP

International audiencePiecewise-deterministic Markov process (PDMP) modeling framework can handle the dependencies between physics-based models, between multi-state models and between these two types of models. Epistemic uncertainty can arise due to the incomplete or imprecise knowledge about the degradation processes and the governing parameters: to take into account this, we describe the parameters of the PDMP model as fuzzy numbers. In this paper, we extend the finite-volume (FV) method to quantify the (fuzzy) reliability of the system. The proposed method is tested on one subsystem of the residual heat removal system (RHRS) of a nuclear power plant, and a comparison is offered with a Monte Carlo (MC) simulation solution