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1 Department of Geological
Sciences
San Diego State University
San Diego, California 92182
Assessing accuracy of numerical methods for spontaneous rupture simulation is
challenging because we lack analytical solutions for reference. Previous
comparison of a boundary integral method (BI) and finite-difference
method (called DFM) that explicitly incorporates the fault
discontinuity at velocity nodes (traction- at-split-node scheme) shows that both
converge to a common, grid-independent solution and exhibit nearly identical
power-law convergence rates with respect to grid spacing
x. We
use this solution as a reference for assessing two other proposed
finite-difference methods, the thick fault (TF) and stress glut
(SG) methods, both of which approximate the fault-jump conditions
through inelastic increments to the stress components (inelastic-zone schemes).
The TF solution fails to match the qualitative rupture behavior of
the reference solution and has quantitative misfits in root- mean-square rupture
time of
30% for the smallest computationally feasible
x
(with
9 grid-point resolution of cohesive zone, denoted
c = 9). For
sufficiently small values of
x, the SG method
reproduces the qualitative features of the reference solution, but rupture
velocity remains systematically low for SG relative to the reference
solution, and SG lacks the well-defined power-law convergence seen
for BI and DFM. The rupture-time error for SG,
with
c
9, remains well above uncertainty in the reference solution, and the
split-node method attains comparable accuracy with
c
1/4 as large (and computation timescales as
(
c)4). Thus,
accuracy is highly sensitive to the formulation of the fault-jump conditions:
The split-node method attains power-law convergence. The SG
inelastic-zone method achieves solutions that are qualitatively meaningful and
quantitatively reliable to within a few percent, but convergence is uncertain,
and SG is computationally inefficient relative to the split-node
approach. The TF inelastic-zone method does not achieve
qualitatively meaningful solutions to the 3D test problem and is sufficiently
computationally inefficient that it is not feasible to explore convergence
quantitatively.
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