Numerical simulations of sequences of earthquakes and aseismic slip (SEAS) have made
great progress over past decades to address important questions in earthquake physics.
However, significant challenges in SEAS modeling remain in resolving multiscale interactions
between earthquake nucleation, dynamic rupture, and aseismic slip, and understanding
physical factors controlling observables such as seismicity and ground
deformation. The increasing complexity of SEAS modeling calls for extensive efforts
to verify codes and advance these simulations with rigor, reproducibility, and broadened
impact. In 2018, we initiated a community code-verification exercise for SEAS simulations,
supported by the Southern California Earthquake Center. Here, we report the
findings from our first two benchmark problems (BP1 and BP2), designed to verify different
computational methods in solving a mathematically well-defined, basic faulting
problem. We consider a 2D antiplane problem, with a 1D planar vertical strike-slip fault
obeying rate-and-state friction, embedded in a 2D homogeneous, linear elastic halfspace.
Sequences of quasi-dynamic earthquakes with periodic occurrences (BP1) or
bimodal sizes (BP2) and their interactions with aseismic slip are simulated. The comparison
of results from 11 groups using different numerical methods show excellent agreements
in long-term and coseismic fault behavior. In BP1, we found that truncated
domain boundaries influence interseismic stressing, earthquake recurrence, and coseismic
rupture, and that model agreement is only achieved with sufficiently large domain
sizes. In BP2, we found that complexity of fault behavior depends on how well physical
length scales related to spontaneous nucleation and rupture propagation are resolved.
Poor numerical resolution can result in artificial complexity, impacting simulation results
that are of potential interest for characterizing seismic hazard such as earthquake size
distributions, moment release, and recurrence times. These results inform the development
of more advanced SEAS models, contributing to our further understanding of
earthquake system dynamics.