Uncertainty Analysis of Consequence Management (CM) Data Products.

Technical Report · Sun Dec 31 23:00:00 EST 2017

DOI:https://doi.org/10.2172/1417787· OSTI ID:1417787

Hunt, Brian D. ^[1]; Eckert-Gallup, Aubrey Celia ^[1]; Cochran, Lainy Dromgoole ^[1]; Kraus, Terrence D. ^[1]; Fournier, Sean Donovan ^[1]; Allen, Mark B. ^[1]; Schetnan, Richard Reed ^[1]; Simpson, Matthew D. ^[2]; Okada, Colin E. ^[3]; Bingham, Avery A. ^[3]

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1. Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
2. Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
3. Remote Sensing Lab. (RSL), Nellis AFB, Las Vegas, NV (United States)

The goal of this project is to develop and execute methods for characterizing uncertainty in data products that are deve loped and distributed by the DOE Consequence Management (CM) Program. A global approach to this problem is necessary because multiple sources of error and uncertainty from across the CM skill sets contribute to the ultimate p roduction of CM data products. This report presents the methods used to develop a probabilistic framework to characterize this uncertainty and provides results for an uncertainty analysis for a study scenario analyzed using this framework.

• Research Organization: Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States)
• Sponsoring Organization: USDOE National Nuclear Security Administration (NNSA)
• DOE Contract Number: AC04-94AL85000
• OSTI ID: 1417787
• Report Number(s): SAND2018-0329; 659902
• Country of Publication: United States
• Language: English

Related Subjects

97 MATHEMATICS AND COMPUTING