Risk Modeling of Variable Probability External Initiating Events in a Functional Modeling Paradigm
As component engineering has progressively advanced over the past 20 years to encompass a robust element of reliability, a paradigm shift has occurred in how complex systems fail. While failures used to be dominated by ‘component failures,’ failures are now governed by other factors such as environmental factors, integration capability, design quality, system complexity, built-in testability, etc. Of these factors, environmental factors are some of the most difficult to predict and assess. While test regimes typically encompass environmental factors, significant design changes to the system to mitigate any potential failures is not likely to occur due to the cost. The early stages of the systems engineering design process offer significant opportunity to evaluate and mitigate risks due to environmental factors. Systems that are expected to operate in a dynamic and changing environment have significant challenges for assessing environmental factors. For example, external failure initiating event probabilities may change with respect to time, and new discovered external initiating events may also be expected to have varying probabilities of occurrence with respect to time. While some industry standard methods such as Probabilistic Risk Assessment (PRA)  and Failure Modes and Effects Analysis (FMEA)  can partially address a time-dependent external initiating event probability, current methods of analyzing system failure risk during conceptual system design cannot. We have developed the Time Based Failure Flow Evaluator (TBFFE) to address the need for a risk analysis tool that can account for variable probabilities in initiating events over the duration of a system’s operation. This method builds upon the Function Based Engineering Design (FBED)  method of functional modeling and the Function Failure Identification and Propagation (FFIP)  failure analysis method that is compatible with FBED. Through the development of TBFFE, we have found that the method can provide significant insights into a design that is to be used in an environment with variable probability external initiating events. We present a case study of the conceptual design of a nuclear power plant’s spent fuel pool experiencing a variety of external initiating events that vary in probability based upon the time of year. The case study illustrates the capability of TBFFE by identifying how seasonally variable initiating event occurrences can impact the probability of failure on a monthly timescale that otherwise would not be seen on a yearly timescale. Changing the design helps to reduce the impact that time-varying initiating events have on the monthly risk of system failure.