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Title: Probabilistic methods for sensitivity analysis and calibration in the NASA challenge problem

In this study, a series of algorithms are proposed to address the problems in the NASA Langley Research Center Multidisciplinary Uncertainty Quantification Challenge. A Bayesian approach is employed to characterize and calibrate the epistemic parameters based on the available data, whereas a variance-based global sensitivity analysis is used to rank the epistemic and aleatory model parameters. A nested sampling of the aleatory–epistemic space is proposed to propagate uncertainties from model parameters to output quantities of interest.
Authors:
 [1] ;  [1] ;  [1] ;  [1] ;  [1] ;  [2] ;  [2]
  1. Sandia National Lab. (SNL-CA), Livermore, CA (United States)
  2. Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Publication Date:
OSTI Identifier:
1141704
Report Number(s):
SAND--2014-2425J
Journal ID: ISSN 2327-3097; 506477
Grant/Contract Number:
AC04-94AL85000
Type:
Accepted Manuscript
Journal Name:
Journal of Aerospace Information Systems
Additional Journal Information:
Journal Volume: 12; Journal Issue: 1; Related Information: Proposed for publication in Journal of Aerospace Information Systems.; Journal ID: ISSN 2327-3097
Publisher:
American Institute of Aeronautics and Astronautics (AIAA)
Research Org:
Sandia National Laboratories Albuquerque, NM (United States); Sandia National Laboratories (SNL-CA), Livermore, CA (United States)
Sponsoring Org:
USDOE National Nuclear Security Administration (NNSA)
Country of Publication:
United States
Language:
English
Subject:
97 MATHEMATICS AND COMPUTING