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Pure and Applied Geophysics

, Volume 174, Issue 9, pp 3369–3391 | Cite as

Quantification of Fault-Zone Plasticity Effects with Spontaneous Rupture Simulations

  • D. Roten
  • K. B. Olsen
  • S. M. Day
  • Y. Cui
Article

Abstract

Previous studies have shown that plastic yielding in crustal rocks in the fault zone may impose a physical limit to extreme ground motions. We explore the effects of fault-zone non-linearity on peak ground velocities (PGVs) by simulating a suite of surface-rupturing strike-slip earthquakes in a medium governed by Drucker–Prager plasticity using the AWP-ODC finite-difference code. Our simulations cover magnitudes ranging from 6.5 to 8.0, three different rock strength models, and average stress drops of 3.5 and 7.0 MPa, with a maximum frequency of 1 Hz and a minimum shear-wave velocity of 500 m/s. Friction angles and cohesions in our rock models are based on strength criteria which are frequently used for fractured rock masses in civil and mining engineering. For an average stress drop of 3.5 MPa, plastic yielding reduces near-fault PGVs by 15–30% in pre-fractured, low strength rock, but less than 1% in massive, high-quality rock. These reductions are almost insensitive to magnitude. If the stress drop is doubled, plasticity reduces near-fault PGVs by 38–45% and 5–15% in rocks of low and high strength, respectively. Because non-linearity reduces slip rates and static slip near the surface, plasticity acts in addition to, and may partially be emulated by, a shallow velocity-strengthening layer. The effects of plasticity are exacerbated if a fault damage zone with reduced shear-wave velocities and reduced rock strength is present. In the linear case, fault-zone trapped waves result in higher near-surface peak slip rates and ground velocities compared to simulations without a low-velocity zone. These amplifications are balanced out by fault-zone plasticity if rocks in the damage zone exhibit low-to-moderate strength throughout the depth extent of the low-velocity zone (\(\sim\)5 km). We also perform dynamic non-linear simulations of a high stress drop (8 MPa) M 7.8 earthquake rupturing the southern San Andreas fault along 250 km from Indio to Lake Hughes. Non-linearity in the fault damage zone and in near-surface deposits would reduce peak ground velocities in the Los Angeles basin by 15–50%, depending on the strength of crustal rocks and shallow sediments. These results show that non-linear effects may be relevant even at long periods, in particular in earthquakes with high stress drop and in the presence of a low-velocity fault damage zone.

Keywords

Spontaneous rupture simulation fault-zone plasticity non-linear soil behavior 

Notes

Acknowledgements

Computations were performed on Blue Waters at NCSA, using resources provided through the PRAC (Petascale Computing Resource Allocation) program, and on Titan, which is part of the Oak Ridge Leadership Facility at the Oak Ridge National Laboratory supported by DOE Contract No. DE-AC05-00OR22725. This research was supported by SCEC through by NSF Cooperative Agreement EAR-0529922 and USGS Cooperative Agreement 07HQAG0008, by USGS award G15AP00077, and by NSF awards EAR-1226343, OCI-114849, OCI-1450451, and EAR-1135455. We used the PyNGA package for Python by Feng Wang to compute spectral accelerations predicted by the two GMPEs. The authors thank two anonymous reviewers and the guest editor for valuable suggestions that helped to improve the manuscript.

References

  1. Andrews, D. (1976). Rupture velocity of plane strain shear cracks. Journal Geophysical Research, 81(32), 5679–5687.CrossRefGoogle Scholar
  2. Andrews, D. (2005). Rupture dynamics with energy loss outside the slip zone. Journal of Geophysical Research, 110(B1), 307.CrossRefGoogle Scholar
  3. Andrews, D., Hanks, T., & Whitney, J. (2007). Physical limits on ground motion at Yucca Mountain. Journal Geophysical Research, 97(6), 1771–1792.Google Scholar
  4. Barall, M. (2010). Tpv26 and tpv27 vertical fault with viscoplasticity benchmarks. Report: Invisible Software Inc.Google Scholar
  5. Baumann, C., & Dalguer, L. (2014). Evaluating the compatibility of dynamic rupture-based synthetic ground motion with empirical ground-motion prediction equation. Bulletin of the Seismological Society of America, 104(2),Google Scholar
  6. Bizzarri, A. (2010). How to promote earthquake ruptures: Different nucleation strategies in a dynamic model with slip-weakening friction. Journal Geophysical Research, 100(3), 923–940.Google Scholar
  7. Bommer, J., & Abrahamson, N. (2006). Why do modern probabilistic seismic-hazard analyses often lead to increased hazard estimates? Journal Geophysical Research, 96(6), 1967–1977.Google Scholar
  8. Bommer, J., Abrahamson, N., Strasser, F., Pecker, A., Bard, P.-Y., Bungum, H., et al. (2004). The challenge of defining upper bounds on earthquake ground motions. Journal Geophysical Research, 75(1), 82–95.Google Scholar
  9. Boore, D. M., Stewart, J. P., Seyhan, E., & Atkinson, G. M. (2014). NGA-West2 equations for predicting PGA, PGV, and 5% damped PSA for shallow crustal earthquakes. Journal Geophysical Research, 30(3), 1057–1085.Google Scholar
  10. Campbell, K. W., & Bozorgnia, Y. (2014). NGA-West2 ground motion model for the average horizontal components of PGA, PGV, and 5% damped linear acceleration response spectra. Journal Geophysical Research, 30(3), 1087–1115.Google Scholar
  11. Chang, C., Zoback, M. D., & Khaksar, A. (2006). Empirical relations between rock strength and physical properties in sedimentary rocks. Journal Geophysical Research, 51(3), 223–237.Google Scholar
  12. Cochran, E. S., Li, Y.-G., Shearer, P. M., Barbot, S., Fialko, Y., & Vidale, J. E. (2009). Seismic and geodetic evidence for extensive, long-lived fault damage zones. Geology, 37(4), 315–318.CrossRefGoogle Scholar
  13. Cui, Y., Olsen, K., Lee, K., Zhou, J., Small, P., Roten, D., Ely, G., Panda, D., Chourasia, A., Levesque, J., Day, S., & Maechling, P. (2010). Scalable earthquake simulation on petascale supercomputers. In Proceedings of SC10. New Orleans, LA.Google Scholar
  14. Dalguer, L., & Day, S. (2007). Staggered-grid split-node method for spontaneous rupture simulation. Journal of Geophysical Research, 112(B02), 302.Google Scholar
  15. Dalguer, L., & Mai, P. (2012). Prediction of near-source ground motion exceeding 1\(g\) at low frequencies (\(<\) 2 Hz) from \(M_w\) \(\sim\) 6.5 deterministic and numerical simulations physics-based dynamic rupture simulations. In Proceedings of 15th World Conference on Earthquake Engineering. Lisbon: Int. Assoc. for Earthquake Eng.Google Scholar
  16. Dalguer, L., Day, S., Olsen, K., & Cruz-Atienza, V. (2008a). Rupture models and ground motion for Shakeout and other southern San Andreas fault scenarios. In Proceedings of 14th World Conference on Earthquake Engineering. Beijing: Int. Assoc. for Earthquake Eng.Google Scholar
  17. Dalguer, L. A., & M. Mai. (2008). Implications of Style-of-Faulting and Loading Characteristics on the Dynamic Rupture Process. In AGU Fall Meeting Abstracts (pp. D1798).Google Scholar
  18. Dalguer, L. A., Miyake, H., Day, S. M., & Irikura, K. (2008b). Surface rupturing and buried dynamic-rupture models calibrated with statistical observations of past earthquakes. Geology, 98(3), 1147–1161.Google Scholar
  19. Day, S., & Bradley, C. (2001). Memory-efficient simulation of anelastic wave propagation. Geology, 91(3), 520.Google Scholar
  20. Denolle, M., Dunham, E., Prieto, G., & Beroza, G. (2013). Strong Ground Motion Prediction using Virtual Earthquakes. Science, 343, 2013.Google Scholar
  21. Duan, B., & Day, S. (2010). Sensitivity study of physical limits on ground motion at Yucca Mountain. Science, 100(6), 2996–3019.Google Scholar
  22. Dunham, E. M., Belanger, D., Cong, L., & Kozdon, J. E. (2011a). Earthquake ruptures with strongly rate-weakening friction and off-fault plasticity, Part 1: planar faults. Science, 101(5), 2296–2307.Google Scholar
  23. Dunham, E. M., Belanger, D., Cong, L., & Kozdon, J. E. (2011b). Earthquake ruptures with strongly rate-weakening friction and off-fault plasticity, Part 2: Nonplanar faults. Science, 101(5), 2308–2322.Google Scholar
  24. Fialko, Y. (2004). Probing the mechanical properties of seismically active crust with space geodesy: Study of the coseismic deformation due to the 1992 M\(_w\) 7. 3 Landers (southern California) earthquake. Journal of Geophysical Research: Solid. Earth, 109(B3),Google Scholar
  25. Fialko, Y., Sandwell, D., Simons, M., & Rosen, P. (2005). Three-dimensional deformation caused by the Bam. Science, 435(7040), 295–299.Google Scholar
  26. Field, E., Kramer, S., Elgamal, A.-W., Bray, J., Matasovic, N., Johnson, P., et al. (1998). Nonlinear site response: Where we’re at (a report from a SCEC/PEER seminar and workshop). Science, 69(3), 230–234.Google Scholar
  27. Gabriel, A.-A., Ampuero, J.-P., Dalguer, L. A., & Mai, P. M. (2013). Source properties of dynamic rupture pulses with off-fault plasticity. Journal Geophysical Research, 118(8), 4117–4126. doi: 10.1002/jgrb.50213.Google Scholar
  28. Graves, R., & R. Pitarka. (2016). Kinematic ground motion simulations on rough faults including effects of 3D stochastic velocity perturbations. Bulletin of the Seismological Society of America (submitted to).Google Scholar
  29. Graves, R. W., Aagaard, B. T., Hudnut, K. W., Star, L. M., Stewart, J. P., & Jordan, T. H. (2008). Broadband simulations for Mw 7.8 southern San Andreas earthquakes: Ground motion sensitivity to rupture speed. Geophysical Research Letters, 35(22), 302.CrossRefGoogle Scholar
  30. Hanks, T., Abrahamson, N., Board, M., Boore, D., Brune, J., & Cornell, C. (2005). Observed ground motions, extreme ground motions, and physical limits to ground motions. In Directions in Strong Motion Instrumentation (pp. 55–59).Google Scholar
  31. Harris, R., Barall, M., Archuleta, R., Dunham, E., Aagaard, B., Ampuero, J., et al. (2009). The SCEC/USGS dynamic earthquake rupture code verification exercise. Journal Geophysical Research, 80(1), 119–126.Google Scholar
  32. Harris, R. A., & Day, S. M. (1997). Effects of a low-velocity zone on a dynamic rupture. Journal Geophysical Research, 87(5), 1267–1280.Google Scholar
  33. Harris, R. A., Barall, M., Andrews, D., Duan, B., Ma, S., Dunham, E., et al. (2011). Verifying a computational method for predicting extreme ground motion. Journal Geophysical Research, 82(5), 638–644.Google Scholar
  34. Hoek, E., Carranza-Torres, C., & Corkum, B. (2002). Hoek-Brown failure criterion - 2002 edition. Journal Geophysical Research, 1, 267–273.Google Scholar
  35. Horsrud, P. (2001). Estimating mechanical properties of shale from empirical correlations. Journal Geophysical Research, 16(2), 68–73.Google Scholar
  36. Huang, Y., Ampuero, J.-P., & Helmberger, D. V. (2014). Earthquake ruptures modulated by waves in damaged fault zones. Journal Geophysical Research, 119(4), 3133–3154.Google Scholar
  37. Leonard, M. (2010). Earthquake fault scaling: self-consistent relating of rupture length, width, average displacement, and moment release. Journal Geophysical Research, 100(5A), 1971–1988.Google Scholar
  38. Li, Y. G., Vidale, J. E., & Cochran, E. S. (2004). Low-velocity damaged structure of the San Andreas Fault at Parkfield from fault zone trapped waves. Geophysical Research Letters, 31(12),Google Scholar
  39. Ma, S. (2008). A physical model for widespread near-surface and fault zone damage induced by earthquakes. Geochemistry Geophysics Geosystems, 9(11), 009.CrossRefGoogle Scholar
  40. Ma, S., & Andrews, D. (2010). Inelastic off-fault response and three-dimensional dynamics of earthquake rupture on a strike-slip fault. Journal of Geophysical Research: Solid Earth, 115(B4),Google Scholar
  41. Magistrale, H., Day, S., Clayton, R., & Graves, R. (2000). The SCEC Southern California Reference Three-Dimensional Seismic Velocity Model Version 2. Journal Geophysical Research, 90(6B), S65–S76.Google Scholar
  42. Mai, P. M., & Beroza, G. C. (2002). A spatial random field model to characterize complexity in earthquake slip. Journal of Geophysical Research (Solid Earth), 107, 2308.Google Scholar
  43. Marinos, V., Marinos, P., & Hoek, E. (2005). The geological strength index: applications and limitations. Journal Geophysical Research, 64(1), 55–65.Google Scholar
  44. Milliner, C., Dolan, J., Hollingsworth, J., Leprince, S., Ayoub, F., & Sammis, C. (2015). Quantifying near-field and off-fault deformation patterns of the 1992 Mw 7.3 Landers earthquake. Geochemistry, Geophysics, Geosystems, 16, 1577–1598.CrossRefGoogle Scholar
  45. Olsen, K. B. (1994). Simulation of three-dimensional wave propagation in the Salt Lake basin, Ph.D. thesis, University of Utah, Salt Lake City, Utah.Google Scholar
  46. Olsen, K. B., Day, S. M., Minster, J. B., Cui, Y., Chourasia, A., Faerman, M., et al. (2006). TeraShake: Strong shaking in Los Angeles expected from southern San Andreas earthquake. Journal Geophysical Research, 77, 281–282.Google Scholar
  47. Olsen, K. B., Day, S. M., Minster, Y. A., Cui, Y., Chourasia, A. J., Okaya, D., & Maechling, P. (2008). Terashake2; spontaneous rupture simulations of Mw 7.7 earthquakes on the southern San Andreas Fault. Bulletin of the Seismological Society of America, 98(3), 1162–1185, 2008.Google Scholar
  48. Olsen, K. B., Day, S. M., Dalguer, L. A., Mayhew, J., Cui, Y., Zhu, J., et al. (2009). ShakeOut-D: Ground motion estimates using an ensemble of large earthquakes on the southern San Andreas fault with spontaneous rupture propagation. Geophysical Research Letters, 36(4), 303.CrossRefGoogle Scholar
  49. Roten, D., Olsen, K. B., Pechmann, J., Cruz-Atienza, V., & Magistrale, H. (2011). 3D Simulations of \(M\) 7 Earthquakes on the Wasatch fault, Utah, Part I: Long-period (0–1 Hz) ground motions. Journal Geophysical Research, 101(5), 2045–2063.Google Scholar
  50. Roten, D., Olsen, K., Day, S., Cui, Y., & Fäh, D. (2014). Expected seismic shaking in Los Angeles reduced by San Andreas fault zone plasticity. Journal Geophysical Research, 41(8), 2769–2777.CrossRefGoogle Scholar
  51. Shi, Z., & Day, S. M. (2013). Rupture dynamics and ground motion from 3-D rough-fault simulations. Journal Geophysical Research, 118(3), 1122–1141.Google Scholar
  52. Templeton, E., Bhat, H., Dmowska, R., & Rice, J. (2010). Dynamic rupture through a branched fault configuration at Yucca Mountain, and resulting ground motions. Journal Geophysical Research, 100(4), 1485–1497.Google Scholar
  53. Vidale, J. E., & Li, Y.-G. (2003). Damage to the shallow Landers fault from the nearby Hector Mine earthquake. Nature, 421(6922), 524–526.CrossRefGoogle Scholar
  54. Wyllie, D., & Mah, C. (2004). Rock slope engineering. Boca Raton: CRC Press.Google Scholar

Copyright information

© Springer International Publishing 2017

Authors and Affiliations

  1. 1.Department of Geological SciencesSan Diego State UniversitySan DiegoUSA
  2. 2.San Diego Supercomputer CenterLa JollaUSA

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