Community-Driven Code Comparisons for Three-Dimensional Dynamic Modeling of Sequences of Earthquakes and Aseismic Slip
Jiang, J.; Erickson, B.A.; Lambert, V.R.; Ampuero, Jean Paul; Ando, R.; Barbot, S.D.; Cattania, C.; Zilio, L.D.; Duan, B.; Dunham, E.M.; Gabriel, A.-A.; Lapusta, N.; Li, D.; Li, M.; Liu, D.; Liu, Y.; Ozawa, S.; Pranger, C.; van Dinther, Y.
(2022) Journal of Geophysical Research: Solid Earth, volume 127, issue 3, pp. 1 - 30
(Article)
Abstract
Dynamic modeling of sequences of earthquakes and aseismic slip (SEAS) provides a self-consistent, physics-based framework to connect, interpret, and predict diverse geophysical observations across spatial and temporal scales. Amid growing applications of SEAS models, numerical code verification is essential to ensure reliable simulation results but is often infeasible due to
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the lack of analytical solutions. Here, we develop two benchmarks for three-dimensional (3D) SEAS problems to compare and verify numerical codes based on boundary-element, finite-element, and finite-difference methods, in a community initiative. Our benchmarks consider a planar vertical strike-slip fault obeying a rate- and state-dependent friction law, in a 3D homogeneous, linear elastic whole-space or half-space, where spontaneous earthquakes and slow slip arise due to tectonic-like loading. We use a suite of quasi-dynamic simulations from 10 modeling groups to assess the agreement during all phases of multiple seismic cycles. We find excellent quantitative agreement among simulated outputs for sufficiently large model domains and small grid spacings. However, discrepancies in rupture fronts of the initial event are influenced by the free surface and various computational factors. The recurrence intervals and nucleation phase of later earthquakes are particularly sensitive to numerical resolution and domain-size-dependent loading. Despite such variability, key properties of individual earthquakes, including rupture style, duration, total slip, peak slip rate, and stress drop, are comparable among even marginally resolved simulations. Our benchmark efforts offer a community-based example to improve numerical simulations and reveal sensitivities of model observables, which are important for advancing SEAS models to better understand earthquake system dynamics.
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Keywords: aseismic slip, code verification, community benchmarks, crustal faulting, earthquake source processes, numerical modeling, Geophysics, Geochemistry and Petrology, Earth and Planetary Sciences (miscellaneous), Space and Planetary Science
ISSN: 2169-9313
Publisher: Wiley
Note: Funding Information: We thank Michael Barall for maintaining the SEAS online platform and Ruth Harris for providing experience from the SCEC/USGS code verification exercises for dynamic rupture simulations. We thank Steve Day, Ruth Harris, Associate Editor, and Editor Rachel Abercrombie for reviewing this manuscript. J. Jiang and B. A. Erickson designed the benchmark problems and organized the workshops for code verification exercises. J. Jiang analyzed all simulation results and led the writing of the manuscript. All remaining authors provided feedback on benchmark design, participated in the benchmark exercises (listed in Table 2 ), and/or helped with revising the manuscript. V. Lambert additionally helped with the early tests of benchmark problems; the other authors are listed alphabetically. The work of J. Jiang and B. A. Erickson on this project and SEAS‐themed workshops have been supported by the Southern California Earthquake Center (SCEC). This research is SCEC Contribution No. 11680. SCEC is funded by National Science Foundation (NSF) Cooperative Agreement EAR‐1600087 and United States Geological Survey (USGS) Cooperative Agreement G17AC00047. The simulations with BICyclE (J. Jiang) were conducted with the award EAR170014 from the Extreme Science and Engineering Discovery Environment (XSEDE), which is supported by NSF Grant No. ACI‐1548562. The simulations with BICyclE (V. Lambert and N. Lapusta) were carried out on the High Performance Computing Center cluster of the California Institute of Technology with the grant support from SCEC. The simulations with Unicycle and Motorcycle are supported in part by the NSF Grant No. EAR‐1848192. The simulations with ESAM are supported by Natural Sciences and Engineering Research Council of Canada (NSERC) Discovery Grant RGPIN‐2018‐05389. The simulations with HBI are supported in part by Japan Society for the Promotion of Science (JSPS) KAKENHI Grant No. 19K04031.The simulations with GARNET are supported by the Dutch Research Council (NWO) grant DEEP.NL.2018.037, Swiss National Science Foundation (SNSF) Grant 200021‐169880, EU‐MC ITN Grant 604713, and EU ERC StG 852992. The simulations with TriBIE are supported by the European Union's Horizon 2020 research and innovation program (TEAR ERC Starting Grant No. 852992) and NSF Grant No. EAR‐2121666. The simulations with EQsimu were conducted with the advanced computing resources provided by Texas A&M High Performance Research Computing and by the Texas Advanced Computing Center (TACC) at the University of Texas at Austin. Funding Information: We thank Michael Barall for maintaining the SEAS online platform and Ruth Harris for providing experience from the SCEC/USGS code verification exercises for dynamic rupture simulations. We thank Steve Day, Ruth Harris, Associate Editor, and Editor Rachel Abercrombie for reviewing this manuscript. J. Jiang and B. A. Erickson designed the benchmark problems and organized the workshops for code verification exercises. J. Jiang analyzed all simulation results and led the writing of the manuscript. All remaining authors provided feedback on benchmark design, participated in the benchmark exercises (listed in Table?2), and/or helped with revising the manuscript. V. Lambert additionally helped with the early tests of benchmark problems; the other authors are listed alphabetically. The work of J. Jiang and B. A. Erickson on this project and SEAS-themed workshops have been supported by the Southern California Earthquake Center (SCEC). This research is SCEC Contribution No. 11680. SCEC is funded by National Science Foundation (NSF) Cooperative Agreement EAR-1600087 and United States Geological Survey (USGS) Cooperative Agreement G17AC00047. The simulations with BICyclE (J. Jiang) were conducted with the award EAR170014 from the Extreme Science and Engineering Discovery Environment (XSEDE), which is supported by NSF Grant No. ACI-1548562. The simulations with BICyclE (V. Lambert and N. Lapusta) were carried out on the High Performance Computing Center cluster of the California Institute of Technology with the grant support from SCEC. The simulations with Unicycle and Motorcycle are supported in part by the NSF Grant No. EAR-1848192. The simulations with ESAM are supported by Natural Sciences and Engineering Research Council of Canada (NSERC) Discovery Grant RGPIN-2018-05389. The simulations with HBI are supported in part by Japan Society for the Promotion of Science (JSPS) KAKENHI Grant No. 19K04031.The simulations with GARNET are supported by the Dutch Research Council (NWO) grant DEEP.NL.2018.037, Swiss National Science Foundation (SNSF) Grant 200021-169880, EU-MC ITN Grant 604713, and EU ERC StG 852992. The simulations with TriBIE are supported by the European Union's Horizon 2020 research and innovation program (TEAR ERC Starting Grant No. 852992) and NSF Grant No. EAR-2121666. The simulations with EQsimu were conducted with the advanced computing resources provided by Texas A&M High Performance Research Computing and by the Texas Advanced Computing Center (TACC) at the University of Texas at Austin. Publisher Copyright: © 2022 The Authors.
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