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Scalable Implicit Methods for Magnetic Fusion Modeling
Daniel R. Reynolds
Center for Computational Mathematics
UC San Diego
Abstract
Fusion energy holds the promise of a clean, sustainable and safe
energy source for the future. While research in this field has
been ongoing for the last half century, much work remains before
it may prove a viable source of energy. In this talk, I discuss
some of the scientific and engineering challenges remaining in
fusion energy, and the role of applied mathematics and scientific
computation in helping overcome these obstacles. I then
introduce some of the mathematical models used in studying fusion
stability and refueling, and how solutions to those models may be
approximated. Of particular interest in such approximation
techniques is the ability of the relevant numerical methods to
scale up to resolutions necessary for accurately modeling the
underlying physics. To that end, I discuss some of my recent
work in the development of fully implicit solution approaches for
magnetic fusion modeling, presenting both numerical results and
theoretical analysis demonstrating the benefit of these
approaches over traditional methods.
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