Analysis of the space propulsion system problem using RAVEN

This paper presents a solution of the space propulsion problem using a PRA code currently under development at Idaho National Laboratory (INL). RAVEN (Risk Analysis and Virtual control ENviroment) is a multi-purpose Probabilistic Risk Assessment (PRA) software framework that allows dispatching different functionalities. It is designed to derive and actuate the control logic required to simulate the plant control system and operator actions (guided procedures) and to perform both Monte-Carlo sampling of randomly distributed events and Event Tree based analysis. In order to facilitate the input/output handling, a Graphical User Interface and a post-processing data-mining module are available. RAVEN also allows to interface with several numerical codes such as RELAP-7, RELAP5-3D and ad-hoc system simulators. For the space propulsion system problem, an ad-hoc simulator has been developed in Python and then interfaced to RAVEN. Such a simulator fully models both the deterministic (e.g., system dynamics and interactions between system components) and the stochastic behaviors (e.g., failures of components/systems such as distribution lines and thrusters). Stochastic analysis is performed using random sampling based methodologies (i.e., Monte-Carlo). Such analysis is accomplished in order to determine both the reliability of the space propulsion system and to propagate the uncertainties associated with a specific set of parameters. As also indicated in the scope of the benchmark problem, the results generated by the stochastic analysis are used to generate risk-informed insights such as conditions under which different strategies can be followed.