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

Journal Article · · Journal of Aerospace Information Systems
DOI:https://doi.org/10.2514/1.I010256· OSTI ID:1141704
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  1. Sandia National Lab. (SNL-CA), Livermore, CA (United States)
  2. Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
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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.
Research Organization:
Sandia National Laboratories (SNL-CA), Livermore, CA (United States); Sandia National Laboratories Albuquerque, NM (United States)
Sponsoring Organization:
USDOE National Nuclear Security Administration (NNSA)
Grant/Contract Number:
AC04-94AL85000
OSTI ID:
1141704
Report Number(s):
SAND--2014-2425J; 506477
Journal Information:
Journal of Aerospace Information Systems, Journal Name: Journal of Aerospace Information Systems Journal Issue: 1 Vol. 12; ISSN 2327-3097
Publisher:
American Institute of Aeronautics and Astronautics (AIAA)Copyright Statement
Country of Publication:
United States
Language:
English

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