RAVEN (https://github.com/idaholab/raven) is a flexible and multi-purpose uncertainty quantification, regressionRD100_2023_Winner_Logo.png analysis, probabilistic risk assessment, data analysis and model optimization framework. Depending on the tasks to be accomplished and on the probabilistic characterization of the problem, RAVEN perturbs (e.g., Monte-Carlo, latin hypercube, reliability surface search) the response of the system under consideration by altering its own parameters. The system is modeled by third party software (e.g., RELAP5-3D, MAAP5, BISON, etc.) and accessible to RAVEN either directly (software coupling) or indirectly (via input/output files). The data generated by the sampling process is analyzed using classical statistical and more advanced data mining approaches. RAVEN also manages the parallel dispatching (i.e. both on desktop/workstation and large High Performance Computing machines) of the software representing the physical model. RAVEN heavily relies on artificial intelligence algorithms to construct surrogate models of complex physical systems in order to perform uncertainty quantification, reliability analysis (limit state surface) and parametric studies.




The development of RAVEN started in 2012 to satisfy the need to provide a modern risk evaluation framework. RAVEN’s principal assignment is to provide the necessary software and algorithms in order to employ the concept developed by the Risk Informed Safety Margin Characterization (RISMC) path-way (now called Risk-Informed System Analysis - RISA). RISMC/RISA is one of the pathways defined within the Light Water Reactor Sustainability (LWRS) program. In the RISMC/RISA approach, the goal is not just specifically identifying the frequency of an event potentially leading to a system failure, but also to analyze the “distance” and the drivers toward the happening of key safety-related events. This approach may be used in identifying and increasing the safety margins related to those events. A safety margin is a numerical value quantifying the probability that a safety metric (e.g. as peak pressure in a pipe) is exceeded under certain conditions. The initial development of RAVEN has been focused on providing dynamic risk assessment capability to system codes (RELAP7, RELAP5, etc). Most of the capabilities have been agnostically implemented. For this reason,  RAVEN has been coupled with several software; for example:

Program Credits

As already mentioned, RAVEN development has been initiated within the RISMC path-way; during the past years, other projects have contributed to its development, among which, the main contributors are:

  • Light Water Reactor Sustainability (LWRS), under the RISMC path-way (website)

  • Nuclear Energy Advanced Modeling and Simulation Program (NEAMS)

  • Nuclear-Renewable Hybrid Energy Systems (NHES) (website)