Reliability and Degradation Analysis of Complex Systems Using Stochastic Petri Nets and Monte Carlo Simulations in Modelica

This study investigates the anticipated transient behavior of molten salt reactors (MSRs), focusing on the effects of a reduction in mass flow caused by primary fuel pump degradation. The analysis evaluates the impact of this degradation on reactor power, core temperature, and overall safety, addressing a gap in existing research on MSRs under such conditions. An integrated approach is employed, combining Stochastic Petri Nets (SPNs) and Monte Carlo simulations within the Modelica environment. SPNs model the probabilistic transitions of the fuel pump between functional, degraded, and failed states using Weibull distributions. These stochastic models are dynamically coupled with the deterministic MSR physical model, which uses validated empirical data to capture continuous system behaviors like heat transfer and mass flow. The results reveal significant power increases and temperature fluctuations in the core during degraded states, providing critical insights into reactor safety and performance under adverse conditions. This work offers a novel framework for modeling the reliability of MSRs under uncertainty, contributing to improved reactor safety, optimized maintenance strategies, and enhanced understanding of transient behaviors in advanced nuclear systems.

Keywords: Reliability, SPN, MSR, Physical model, Monte Carlo simulation.