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Journal Article
Published: 10 September 2024
Seismological Research Letters (2025) 96 (1): 207–218.
... (RSQSim) to simulate the eastern Taiwan fault system, integrating fault geometry from the multidisciplinary Taiwan Earthquake Model. We applied long‐term simulations spanning 400,000 yr to conduct earthquake sequences and recurrence intervals on five distinct faults in eastern Taiwan: Milun fault...
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Journal Article
Published: 10 June 2015
Seismological Research Letters (2015) 86 (4): 1102–1109.
... fracture. Here, we present a modeling approach for simulating seismicity induced by fluid injection in 3D over multiple earthquake cycles. We developed a method to simulate injection‐induced seismicity that couples the regional scale, multicycle earthquake simulator, RSQSim, to reservoir models...
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Journal Article
Published: 01 November 2012
Seismological Research Letters (2012) 83 (6): 983–990.
... issue, and their general features are described in Tullis et al. (2012a) . This paper describes features specific to one of those four, RSQSim. It also presents results that are relevant to particularly unique features of RSQSim: comparisons with fully dynamic single‐event simulations and the spatial...
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Distribution of earthquake events. (a) Cumulative earthquake events for RSQ...
Published: 10 September 2024
Figure 4. Distribution of earthquake events. (a) Cumulative earthquake events for RSQSim. The blue line is the whole events of RSQSim. The orange line is events of rigorously selected historical earthquake catalog. The red line is events of unrigorously selected historical earthquake catalog
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Recurrence interval on each fault, <span class="search-highlight">RSQSim</span> results are showing in blue, best...
Published: 10 September 2024
Figure 6. Recurrence interval on each fault, RSQSim results are showing in blue, best‐fitting normal distributions are showing in red. (a) Each fault recurrence interval in this faults system. (b) The recurrence interval for each stand‐alone fault. The color version of this figure is available
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Magnitude–probability of <span class="search-highlight">RSQSim</span> simulation bar charts fitting with Weibull,...
Published: 10 September 2024
Figure 8. Magnitude–probability of RSQSim simulation bar charts fitting with Weibull, gamma, and lognormal distribution. (a) Comparing with rigorously selected catalog. (b) Comparing with unrigorously selected catalog. The color version of this figure is available only in the electronic edition.
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(a) Schematic diagram of the fault plane used in the <span class="search-highlight">RSQSim</span> simulations. Th...
Published: 19 April 2024
Figure 1. (a) Schematic diagram of the fault plane used in the RSQSim simulations. The color represents a pattern of preexisting shear stress on the fault surface prior to injection (see Fig.  2 ). Additional representations of the stress field can be found in Figure  2 . The location
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(a) Space versus time separation of subsequent events for the  CISN  Califo...
Published: 01 November 2012
Figure 5. (a) Space versus time separation of subsequent events for the CISN California catalog, 1911–2010.5. (b) 20,000‐year RSQSim catalog for event magnitudes 5≤ M <6, 6≤ M <7, and M >7. Horizontal streaks in RSQSim plots are an effect of the fault element size.
Journal Article
Published: 05 January 2021
Bulletin of the Seismological Society of America (2021) 111 (2): 898–915.
... and dynamic stresses, are still computationally intractable for the large simulation domains and many seismic cycles required to perform PSHA. Instead, we employ the Rate‐State earthquake simulator (RSQSim) to efficiently simulate hundreds of thousands of years of M ≥ 6.5 earthquake sequences...
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Comparison of ruptures in MCQsim, <span class="search-highlight">RSQSim</span>, and DYNA3D (digitized from  Richa...
Published: 20 April 2023
Figure 7. Comparison of ruptures in MCQsim, RSQSim, and DYNA3D (digitized from Richards‐Dinger and Dieterich, 2012 ). (a) Distribution of normal stress, artificial nucleation site, and profile line for slip and stress changes. Below the setup, follow contour plots of first time of rupture
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Rate at which ruptures from the <span class="search-highlight">RSQSim</span> comparison model fail the plausibili...
Published: 25 May 2022
Figure 5. Rate at which ruptures from the RSQSim comparison model fail the plausibility filters used in UCERF3 (solid gray line) and proposed here (solid black line), as a function of magnitude. This excludes the minimum number of subsections per cluster filter, which is common to both models
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All    7  ≤  M  ≤  7.5    San Andreas (Mojave) <span class="search-highlight">RSQSim</span> events (black histogr...
Published: 05 January 2021
Figure 9. All 7 ≤ M ≤ 7.5 San Andreas (Mojave) RSQSim events (black histogram) for a site at USC, 3‐s RotD50 ground‐motion histograms of accelerations. (a) 1D velocity structure in the SCEC BBP. (b) 3D velocity structure for a site at USC. GMM predicted lognormal distributions
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<span class="search-highlight">RSQSim</span> simulation hazard curves at USC. CyberShake (3D) is plotted with thi...
Published: 05 January 2021
Figure 15. RSQSim simulation hazard curves at USC. CyberShake (3D) is plotted with thick, black lines. (a) ASK2014 GMM comparisons curves in blue, with the complete hazard curve plotted as a thick solid line. GMM curves computed from truncated lognormal distributions at 3‐, 2‐, and 1‐ σ
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2D side view of the    M    7.5 simulated <span class="search-highlight">RSQSim</span> rupture from Figure  3 . T...
Published: 05 January 2021
Figure 4. 2D side view of the M  7.5 simulated RSQSim rupture from Figure  3 . The common x axis is the along‐strike distance of the rupture in kilometers, with zero at the southeast end of the rupture and the maximum at the northwest end. The y axis of each panel is the depth of each
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3D perspective view looking north of a complex synthetic    M    7.8 <span class="search-highlight">RSQSim</span>...
Published: 05 January 2021
Figure 5. 3D perspective view looking north of a complex synthetic M  7.8 RSQSim rupture in the Los Angeles basin. It nucleates on the Compton fault and then spreads to the Newport–Inglewood, Palos Verdes, and other nearby faults. In total, 10 different UCERF3 fault sections participate
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Source contributions for <span class="search-highlight">RSQSim</span> hazard curves computed at USC. Individual f...
Published: 05 January 2021
Figure 16. Source contributions for RSQSim hazard curves computed at USC. Individual fault contributions are shown with thin colored lines. (a) Results computed with CyberShake, with the total CyberShake curve on top, as a thick black line. (b) Results computed with the empirical ASK2014 GMM
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The distribution of earthquake catalogs. The light‐blue star represents ear...
Published: 10 September 2024
structure (CRS) is 19.4 km deep. The Luyeh fault is 4.5 km deep. The Taimali Coastline structure is 10.1 km deep. (a) Rigorously selected historical earthquake catalog. (b) Unrigorously selected historical earthquake catalog. (c) Simulation of Rate and State Earthquake Simulator (RSQSim) trimmed 100 yr. (d
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The    z   ‐score (equation  3 ) distributions (gray histograms) of all rup...
Published: 05 January 2021
line. (a) RSQSim rupture ground motions simulated with BBP and a 1D velocity structure. (b) RSQSim rupture ground motions simulated with the SCEC CyberShake platform and a 3D velocity structure. (c) UCERF2 ruptures extended with the Graves and Pitarka (2014) kinematic rupture generator simulated
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Comparison of ruptures in DYNA3D and <span class="search-highlight">RSQSim</span>. (a) Distribution of initial no...
Published: 01 November 2012
Figure 1. Comparison of ruptures in DYNA3D and RSQSim. (a) Distribution of initial normal stress (initial shear stress is a uniform 75 MPa). The cross near the left end of the fault is the location of artificial nucleation. (b) Contours of time of first rupture. Contour interval is 0.25 s. (c
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Propagation velocity as a function of patch hypocentral distance for four d...
Published: 05 January 2021
Figure 6. Propagation velocity as a function of patch hypocentral distance for four different RSQSim parameterizations, each of which incorporates a new feature over the previous model. The base model is the catalog used in Shaw et al. (2018) , plotted with a dashed line. The first