Understanding rare safety and reliability events using transition path sampling

Abstract In the chemical and process industries, processes and their control systems are typically well-designed to mitigate abnormal events having potential adverse consequences to human health, environment, and/or property. Strong motivation exists to understand how these events develop and propagate. These events occur so rarely that statistical analyses of their occurrences alone are incapable of describing and characterizing them − especially when they have not yet occurred. Moreover, the use of process models to understand such rare events is hampered by the orders of magnitude separating the frequencies with which reliability and safety events (years to decades) occur and the duration over which they occur (minutes to hours). To address these challenges, we adapt a Monte-Carlo based, rare-event sampling technique, Transition Path Sampling (TPS), which was developed by the molecular simulation community. Important modifications to the TPS technique are needed to apply it to process dynamics, and are discussed herein.