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Creator:: Rajbhandari, Evan, Gibson, Nathan L., and Woodside, C. Rigel
Abstract:: We explore one numerical method for dealing with uncertainty quantification, stochastic collocation. We adapt this method for the uncertain kinematic magnetohydrodynamic system. We then demonstrate well-posedness of the uncertain forward problem. We also describe the method in detail, and perform an error analysis of the method, describing the necessary assumptions...
Resource Type:: Preprint

Creator:: Rajbhandari, Evan, Gibson, Nathan L., and Woodside, C. Rigel
Abstract:: We discuss an efficient numerical method for the uncertain kinematic magnetohydrodynamic system. We include aleatoric uncertainty in the parameters, and then describe a stochastic collocation method to handle this randomness. Numerical demonstrations of this method are discussed. We find that the shape of the parameter distributions affect not only the...
Resource Type:: Preprint

Creator:: Rajbhandari, Evan, Gibson, Nathan L., and Woodside, C. Rigel
Abstract:: We discuss the well-posedness of the forward problem for the magnetohydrodynamic system with the inclusion of the ion-slip parameter. We also demonstrate the convergence of a parameter estimation scheme. Focusing on power-generation, we implement and the validate a numerical model with an engineering multi-physics software, COMSOL, using ideal-power equations. We...
Resource Type:: Preprint

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