Methods for quantifying uncertainty in fast reactor analyses.

Abstract

Liquid-metal-cooled fast reactors in the form of sodium-cooled fast reactors have been successfully built and tested in the U.S. and throughout the world. However, no fast reactor has operated in the U.S. for nearly fourteen years. More importantly, the U.S. has not constructed a fast reactor in nearly 30 years. In addition to reestablishing the necessary industrial infrastructure, the development, testing, and licensing of a new, advanced fast reactor concept will likely require a significant base technology program that will rely more heavily on modeling and simulation than has been done in the past. The ability to quantify uncertainty in modeling and simulations will be an important part of any experimental program and can provide added confidence that established design limits and safety margins are appropriate. In addition, there is an increasing demand from the nuclear industry for best-estimate analysis methods to provide confidence bounds along with their results. The ability to quantify uncertainty will be an important component of modeling that is used to support design, testing, and experimental programs. Three avenues of UQ investigation are proposed. Two relatively new approaches are described which can be directly coupled to simulation codes currently being developed under the Advanced Simulation and Modeling program within the Reactor Campaign. A third approach, based on robust Monte Carlo methods, can be used in conjunction with existing reactor analysis codes as a means of verification and validation of the more detailed approaches. Methods for Quantifying Uncertainty in Fast Reactor Analyses vi