Jean C. Ragusa

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We describe a modern approach for solving coupled multiphysics problems where the different physical components are solved on individual meshes. These meshes are adaptively refined independently from each other in order to obtain an accurate solution with the lowest number of degrees of freedom possible. We consider a time-dependent two-dimensional problem(More)
Mesh refinement techniques rely on the use of a posteriori error estimators, which allow the measure, control and minimization of approximation errors. In the a posteriori error estimator theory, the computed solution itself is used to provide inexpensively local error estimations, whereby the numerical solution itself is used to assess the accuracy [2]. By(More)
High-fidelity modeling of nuclear reactors requires the solution of nonlinear coupled multi-physics stiff problems with widely varying time and length scales that need to be resolved correctly. A numerical method that converges the implicit nonlinear terms to a small tolerance is often referred to as nonlinearly consistent (or tightly coupled). This(More)
Classification problems arise in so many different parts of life – from sorting machine parts to diagnosing a disease. Humans make these classifications utilizing vast amounts of data, filtering observations for useful information, and then making a decision based on a subjective level of cost/risk of classifying objects incorrectly. This study investigates(More)
Implicit Runge Kutta (IRK) methods were applied to solve the nonlinear point reactor kinetic equations with feedback. These methods preserve their high accuracy order, even for stiff nonlinear problems and are viable candidates for implementation into multiphysics simulation software. Adaptive time stepping strategies associated with these methods can(More)