ABSTRACT Title of Document: A GENERAL CAUSE BASED METHODOLOGY FOR ANALYSIS OF DEPENDENT FAILURES IN SYSTEM RISK AND RELIABILITY ASSESSMENTS

Traditional parametric Common Cause Failure (CCF) models quantify the soft dependencies between component failures through the use of empirical ratio relationships. Furthermore CCF modeling has been essentially restricted to identical components in redundant formations. While this has been advantageous in allowing the prediction of system reliability with little or no data, it has been prohibitive in other applications such as modeling the characteristics of a system design or including the characteristics of failure when assessing the risk significance of a failure or degraded performance event (known as an event assessment). This dissertation extends the traditional definition of CCF to model soft dependencies between like and non-like components. It does this through the explicit modeling of soft dependencies between systems (coupling factors) such as sharing a maintenance team or sharing a manufacturer. By modeling the soft dependencies explicitly these relationships can be individually quantified based on the specific design of the system and allows for more accurate event assessment given knowledge of the failure cause. Since the most data informed model in use is the Alpha Factor Model (AFM), it ha