Development of an Automated Testing System for Verification and Validation of Nuclear Data

摘要

Verification and validation of nuclear data is critical to the accuracy of both stochastic and deterministic particle transport codes. In order to effectively test a set of nuclear data, the data must be applied to a wide variety of transport problems. Performing this task in a timely, efficient manner is tedious. The nuclear data team at Los Alamos National Laboratory (LANL) in collaboration with the University of Florida is developing a methodology to automate the process of nuclear data verification and validation. The International Criticality Safety Benchmark Experiment Project (ICSBEP) provides a set of criticality problems that may be used to evaluate nuclear data. This process tests a number of data libraries using cases from the ICSBEP benchmark set to demonstrate how automation of these tasks may reduce errors and increase efficiency. The process is driven by an integrated set of Python scripts. Material and geometry data may be read from an existing code input file to generate a standardized template or the template may be generated directly by the user. The user specifies the desired precision and other vital problem parameters. The Python scripts generate input decks for multiple transport codes from these templates, run and monitor individual jobs, and parse the relevant output. This output can then be used to generate reports directly or can be stored into a database for later analysis. This methodology eases the burden on the user by reducing the amount of time and effort required for obtaining and compiling calculation results.