Dynamic Reliability and Safety Modeling of a Molten Salt Reactor Using Sysml V2

The increasing demand for clean and sustainable energy sources has reignited interest in nuclear power, with Molten Salt Reactors (MSRs) emerging as a promising innovation due to their enhanced safety, efficiency, and sustainability compared to traditional solid-fuel reactors.However, the large-scale deployment of MSRs faces critical challenges, particularly the corrosive nature of molten salts and the complex interdependencies of system components, which necessitate advanced methods for safety and reliability assessment.This study pioneers a model-based safety and reliability assessment of an MSR system using the Systems Modeling Language (SysML) v2.This approach facilitates a holistic and system-engineering-driven representation of the MSR, encompassing requirements, constraints, metadata, and system architecture.The focus is on the primary fuel loop, specifically the primary heat exchanger and fuel pump, two key subsystems that are critical for efficient reactor operation.The SysML v2 model, annotated with safety information, is consumed by the SAFEST toolchain, a state-of-the-art probabilistic risk assessment (PRA) platform, generating safety artifacts -dynamic fault trees -and evaluating metrics like unreliability, full functional availability (FFA), mean time to failure (MTTF), etc.This methodology automates the generation of safety artifacts from SysML v2 models of dynamic systems, capturing time-dependent failure behavior and fault propagation pathways that static approaches cannot fully address.This study represents the first application of dynamic reliability artifact generation, which captures the time-dependent failure behavior of MSR system components, to an MSR system modeled in SysML v2, setting a new benchmark for model-based safety assessments in complex nuclear systems.The results provide quantitative insights into system reliability metrics, identify critical failure-prone components, and highlight opportunities for design refinement and optimization.This systematic approach provides a scalable framework for evaluating the safety and reliability of MSR and other complex engineered systems, contributing to their viability as a sustainable energy solution for the future.