RAVEN and dynamic probabilistic risk assessment: Software overview

Risk Analysis Virtual Environment (RAVEN) is a generic software framework to perform parametric and probabilistic analysis based on the response of complex system codes. The initial development was aimed at providing dynamic risk analysis capabilities to the Reactor Excursion and Leak Analysis Program v.7 (RELAP-7) Thermo-Hydraulic code, currently under development at the Idaho National Laboratory (INL). Although the initial goal has been fully accomplished, RAVEN is now a multi-purpose probabilistic and uncertainty quantification platform, capable to agnostically communicate with any system code. This agnosticism includes providing Application Programming Interfaces (APIs). These APIs are used to allow RAVEN to interact with any code as long as all the parameters that need to be perturbed are accessible through input files or via python interfaces. RAVEN is capable of investigating the system response as well as the input space using Monte Carlo, Grid, or Latin Hyper Cube sampling schemes, but its strength is focused toward system feature discovery, such as limit surfaces, separating regions of the input space leading to system failure, using dynamic supervised learning techniques. The paper presents an overview of the software capabilities and their implementation schemes followed by some application examples.