MELCOR – DAKOTA Coupling for Uncertainty Analyses, in a SNAP Environment/Architecture (NUREG/IA-0532)

On this page:

• Publication Information
• Abstract

Download complete document

• NUREG/IA-0532 (PDF – 20.39 MB)

Publication Information

Manuscript Completed: March 2022
Date Published: April 2023

Prepared by:
Fulvio Mascari*, Andrea Bersano*, Giuseppe Agnello**, Michela Angelucci***, Jesse Phillips****, David Luxat****

*ENEA, Via Martiri di Monte Sole 4, Bologna, 40129, Italy
**University of Palermo, Department of Engineering, Viale delle Scienze, Edificio 6, 90128, Palermo, Italy
***University of Pisa, Department of Civil and Industrial Engineering (DICI), Via Diotisalvi 2, Pisa Italy
****Sandia National Laboratories, 1515 Eubank SE Albuquerque, New Mexico 87123

H. Hossein, NRC Project Manager

Division of Systems Analysis
Office of Nuclear Regulatory Research
U.S. Nuclear Regulatory Commission
Washington, DC 20555-0001

Prepared as part of:
The Agreement on Research Participation and Technical Exchange
Under the Cooperative Severe Accident Research Program (CSARP)

Published by:
U.S. Nuclear Regulatory Commission
Washington, DC 20555-0001

Availability Notice

Abstract

Uncertainty estimation to assess figure-of-merits characterizing evolution of a severe accident transient is a topic of current investigation in development of best-estimate plus uncertainty methodology. The probabilistic method to propagate input uncertainty is one of the methodologies used to develop Uncertainty Analyses (UAs). Using this methodology, UAs are performed by sampling probability distributions that describe the range of possible values that computer simulation model inputs can have. For each sample (or realization) of a set of uncertain input parameters, a computer simulation is performed. From the range of code simulation results obtained for each input realization, a distribution of code results is obtained. In this process, the distribution of input uncertainties is propagated to obtain a distribution of possible code results (i.e., the code output uncertainty). This probabilistic methodology is facilitated using Uncertainty Tools (UTs), which can be coupled with the accident analysis computer code to perform an UA. One of the UTs currently available is DAKOTA, developed by Sandia National Laboratories. DAKOTA is also provided as a SNAP plug-in. SNAP is a graphical user interface designed to support the use of USNRC codes. This report demonstrates the workflow within SNAP to assist other interested analysts with their applications given they are members of the USNRC Cooperative Severe Accident Research Program (CSARP). Two sample applications are shown.