Within this dissertation, we develop tools and techniques to demonstrate the feasibility of real-time optimization of a magnetohydrodynamics generator. To ease computational complexity, we work on the kinematic magnetohydrodynamic system, prescribing the fluid-flow and model the material response of the system through an updated Generalized Ohm’s law. We focus on...
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...
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...
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...
The theory behind magnetohydrodynamics (MHD) is utilized to present a 3-D solution to how the induced magnetic field changes with respect to time. Several MHD-based assump- tions are made to simplify the coupling of Maxwell’s equations with two constitutive laws and Ohm’s law. The velocity field is assumed to be...