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

Safta, Cosmin; Sargsyan, Khachik; Najm, Habib N.; Chowdhary, Kenny; Debusschere, Bert; Swiler, Laura P.; Eldred, Michael S.

doi:10.2514/1.I010256

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

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Abstract

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:

Safta, Cosmin ^[1]; Sargsyan, Khachik ^[1]; Najm, Habib N. ^[1]; Chowdhary, Kenny ^[1]; Debusschere, Bert ^[1]; Swiler, Laura P. ^[2]; Eldred, Michael S. ^[2]

Sandia National Lab. (SNL-CA), Livermore, CA (United States)
Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

Publication Date:: Thu Jan 01 00:00:00 EST 2015

Research Org.:: Sandia National Laboratories Albuquerque, NM (United States); Sandia National Lab. (SNL-CA), Livermore, CA (United States)

Sponsoring Org.:: USDOE National Nuclear Security Administration (NNSA)

OSTI Identifier:: 1141704

Report Number(s):: SAND-2014-2425J
Journal ID: ISSN 2327-3097; 506477

Grant/Contract Number:: AC04-94AL85000

Resource 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)

Country of Publication:: United States

Language:: English

Subject:: 97 MATHEMATICS AND COMPUTING

Citation Formats


                    Safta, Cosmin, Sargsyan, Khachik, Najm, Habib N., Chowdhary, Kenny, Debusschere, Bert, Swiler, Laura P., and Eldred, Michael S. Probabilistic methods for sensitivity analysis and calibration in the NASA challenge problem.  United States: N. p., 2015. 
Web.  doi:10.2514/1.I010256.

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                    Safta, Cosmin, Sargsyan, Khachik, Najm, Habib N., Chowdhary, Kenny, Debusschere, Bert, Swiler, Laura P., & Eldred, Michael S. Probabilistic methods for sensitivity analysis and calibration in the NASA challenge problem.  United States.  https://doi.org/10.2514/1.I010256

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                    Safta, Cosmin, Sargsyan, Khachik, Najm, Habib N., Chowdhary, Kenny, Debusschere, Bert, Swiler, Laura P., and Eldred, Michael S. Thu .  
"Probabilistic methods for sensitivity analysis and calibration in the NASA challenge problem".  United States.  https://doi.org/10.2514/1.I010256.  https://www.osti.gov/servlets/purl/1141704.

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@article{osti_1141704,

  title        = {Probabilistic methods for sensitivity analysis and calibration in the NASA challenge problem},

  author       = {Safta, Cosmin and Sargsyan, Khachik and Najm, Habib N. and Chowdhary, Kenny and Debusschere, Bert and Swiler, Laura P. and Eldred, Michael S.},

  abstractNote = {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.},

  doi          = {10.2514/1.I010256},

  journal      = {Journal of Aerospace Information Systems},

  number       = 1,

  volume       = 12,

  place        = {United States},

  year         = {Thu Jan 01 00:00:00 EST 2015},

  month        = {Thu Jan 01 00:00:00 EST 2015}

}

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