A sparse-grid probabilistic scheme for approximation of the runaway probability of electrons in fusion tokamak simulation
Minglei Yang, Guannan Zhang, Diego del-Castillo-Negrete, Miroslav, Stoyanov, Matthew Beidler

TL;DR
This paper introduces a sparse-grid probabilistic numerical scheme to efficiently compute the runaway electron probability in fusion reactors, addressing the challenge of sharp transition layers in phase space.
Contribution
The paper presents a novel integration of sparse-grid methods into probabilistic schemes for solving the adjoint Fokker-Planck equation in runaway electron analysis.
Findings
Achieves d7(b4t) convergence rate.
Effectively handles sharp transition layers.
Demonstrates applicability to real fusion plasma scenarios.
Abstract
Runaway electrons (RE) generated during magnetic disruptions present a major threat to the safe operation of plasma nuclear fusion reactors. A critical aspect of understanding RE dynamics is to calculate the runaway probability, i.e., the probability that an electron in the phase space will runaway on, or before, a prescribed time. Such probability can be obtained by solving the adjoint equation of the underlying Fokker-Planck equation that controls the electron dynamics. In this effort, we present a sparse-grid probabilistic scheme for computing the runaway probability. The key ingredient of our approach is to represent the solution of the adjoint equation as a conditional expectation, such that discretizing the differential operator reduces to the approximation of a set of integrals. Adaptive sparse grid interpolation is utilized to approximate the map from the phase space to the…
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Taxonomy
TopicsMagnetic confinement fusion research · Nuclear reactor physics and engineering
