Investigations on Bayesian uncertainty quantification with two examples

Input quantities for the numerical simulation of fusion plasmas involve field quantities which are hampered by noise. In order to compare data from experiment to model results, or to have an estimation of the fluctuation margin of a model prediction, a quantification of the uncertainties is necessar...

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Bibliographic Details
Main Authors: Preuss, R., von Toussaint, U.
Format: Conference Proceeding
Language:English
Subjects:
Bayesian analysis
Computer simulation
Forecasting
Gaussian process
Hermite polynomials
Mathematical models
Noise
Plasmas
Uncertainty
Variations
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Summary:Input quantities for the numerical simulation of fusion plasmas involve field quantities which are hampered by noise. In order to compare data from experiment to model results, or to have an estimation of the fluctuation margin of a model prediction, a quantification of the uncertainties is necessary. Within a discrete projection framework we employ a spectral expansion to represent the random process responsible for the noise. Since Gaussian distributed noise is assumed Hermite polynomials are chosen for the orthonormal basis system. The coefficients are calculated from collocation points defined by Gaussian quadrature in a non-intrusive approach. An instructive example of absorption in media serves for the validation of the procedure. Finally the method is applied to the Vlasov-Poisson model describing electrostatic plasmas, which will be influenced by an uncertain external field.
ISSN:0094-243X
1551-7616
DOI:10.1063/1.4959060