A cell-to-cell Markovian model for the reliability of a digital control system of a steam generator

With the shift of technology from analog to digital systems, due to the obsolescence of the older analog systems and the functional advantages of the digital ones, existing nuclear power plants have begun to replace their systems, while newer plants use digital systems from the beginning of their construction. However, the process of risk-informed analysis for digital systems has not been satisfactorily developed yet. Traditional methods, such as fault trees, have limitations, while dynamic methods are still in the tests stage and may be difficult to be applied to a real size probabilistic safety assessment (PSA) model. The objective of this paper is to study and obtain a better comprehension of the Markov/CCMT method, a method that combines the traditional Markovian methodology with the cell-to-cell mapping technique for representing the possible failure events that can be originated in the dynamic interactions between the instrumentation and control system and the controlled process, and among the various components of the digital system. The study consists of the simulation of a digital water level control system of the steam generator of a PWR plant. From this simulation, a Failure Modes and Effects Analysis (FMEA) was made and the information obtained was used to calculate the system reliability, using the Markov/CCMT methodology. The results show that the method is capable of identifying the most probable causes for a possible failure of the digital system. (author)