Common Cause Failure Analysis System Results. Frances Marshall, INEEL, POB 1625, Idaho Falls, ID 83415-3865; Ali Mosleh, UMD, College Park, MD 20742-2115; Steve Novack, INEEL; and Dale Rasmuson, USNRC/AEOD T4F
Common cause failure (CCF) events have been shown to be significant contributors to the safety system unavailability and accident sequence core damage frequency in commercial nuclear power plants. The Idaho National Engineering and Environmental Laboratory (INEEL) and the U. S. Nuclear Regulatory Commission’s (NRC’s) Office for Analysis and Evaluation of Operational Data (AEOD) have developed a CCF data collection and analysis system that includes a method for identifying, classifying, and coding CCF events for use in CCF studies, and a personal computer system for storing and analyzing the data for use in reliability and risk analysis studies. The system described in this paper presents an integrated approach for screening and collecting CCF events, coding and loading them into the database, selecting data for applicability to a given reliability or risk study and estimating the appropriate CCF parameters. The techniques used here are based on previous CCF methods, models, and data collection procedures. The data collection effort associated with this project has added a substantial number of CCF events to the database for use in CCF analyses. There are approximately 1500 CCF events affecting several diverse component types in 15 different nuclear power plant safety systems. Engineering evaluation of the CCF database events revealed several mechanisms in power plants that tie together individual component failures resulting in the CCF events. These mechanisms are related to similarities in design, maintenance practices, and operational characteristics. Elimination of and analysis system that includes a method for identifying, classifying, and coding CCF events for use in CCF studies, and a personal computer system for storing and analyzing the data for use in reliability and risk analysis studies. The system described in this paper presents an integrated approach for screening and . . . . [RiskWorld Note: Submitted abstract incomplete]