Estimation of common cause failures probabilities in control systems by colored, hierarchical Petri nets
Résumé
In nuclear I&C safety systems, redundant and separated architectures reduce risk to a residual level, mostly due to Common Cause Failures (CCF). Common Cause Failures (CCF) are faults, resulting from a single cause, which can affect different components at the same time. There are different models to represent them, such as the Atwood model. The latter assumes that components are almost identical, and have the same common-cause failure probability due to shocks. However, these hypothesis are too restrictive for our needs and may induce modeling errors. Thus, we introduce the concept of “oriented CCF”, which takes into account the difference of vulnerabilities among similar components, due to the structural features of our system. Oriented CCF may represent various root causes (hardware, software, human failure), and different spreading patterns. To handle the complexity of our system, we chose to use hierarchical, timed, Colored Petri Nets (CPN). CPN is a discrete-event modeling language combining the capabilities of Petri Nets with the capabilities of a high level programming language. The main difference with Petri Nets is that the CPN tokens can have different colors representing data types (e.g. Boolean, integer or more complex data structure). CPN concept of hierarchy allows us to propose a modular modeling approach for a complex system, based on generic modules that can be instantiated as often as needed. The modeling software we use is CPN Tools, an open-source tool for editing, simulating and analyzing hierarchical and timed CPN. The tool also features various probability distributions, which can be used to emulate a stochastic behavior.