Dynamic reliability modeling of digital instrumentation and control systems in nuclear power plants

This paper shows how it is possible construct PRA models of digital instrumentation and control system using the DFM and Markov/CCMT as two example dynamic methodologies. The digital feedwater control system of a PWR has been used as an example system to illustrate the process. The prime implicants and their probabilities generated by these two methodologies have been compared. The comparison shows a very close consistency between the DFM and Markov/CCMT results. The power of these dynamic methodologies is their ability to identify combinations of component failure modes, even across time boundaries, that can result in system failure modes that otherwise would be very difficult to identify with a standard ET/FT approach. Applications of either methodology require complete and thorough supporting analyses (e.g. FMEA) and data (e.g. transition and failure data for components), as well as a system model describing the system behavior under normal and upset conditions (e.g. simulator).