Probabilistic methods for sensitivity analysis and calibration in the NASA challenge problem
Journal Article
·
· Journal of Aerospace Information Systems
- Sandia National Lab. (SNL-CA), Livermore, CA (United States)
- Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
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 Albuquerque, NM (United States); Sandia National Lab. (SNL-CA), Livermore, CA (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, Vol. 12, Issue 1; Related Information: Proposed for publication in Journal of Aerospace Information Systems.; ISSN 2327-3097
- Publisher:
- American Institute of Aeronautics and Astronautics (AIAA)Copyright Statement
- Country of Publication:
- United States
- Language:
- English
Cited by: 10 works
Citation information provided by
Web of Science
Web of Science
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