Regional seismic-damage prediction of buildings under mainshock—aftershock sequence

Abstract

Strong aftershocks generally occur following a significant earthquake. Aftershocks further damage buildings weakened by mainshocks. Thus, the accurate and efficient prediction of aftershock-induced damage to buildings on a regional scale is crucial for decision making for post-earthquake rescue and emergency response. A framework to predict regional seismic damage of buildings under a mainshock-aftershock (MS-AS) sequence is proposed in this study based on city-scale nonlinear time-history analysis (THA). Specifically, an MS-AS sequence-generation method is proposed to generate a potential MS-AS sequence that can account for the amplification, spectrum, duration, magnitude, and site condition of a target area. Moreover, city-scale nonlinear THA is adopted to predict building seismic damage subjected to MS-AS sequences. The accuracy and reliability of city-scale nonlinear THA for an MS-AS sequence are validated by as-recorded seismic responses of buildings and simulation results in published literature. The town of Longtoushan, which was damaged during the Ludian earthquake, is used as a case study to illustrate the detailed procedure and advantages of the proposed framework. The primary conclusions are as follows. (1) Regional seismic damage of buildings under an MS-AS sequence can be predicted reasonably and accurately by city-scale nonlinear THA. (2) An MS-AS sequence can be generated reasonably by the proposed MS-AS sequence-generation method. (3) Regional seismic damage of buildings under different MS-AS scenarios can be provided efficiently by the proposed framework, which in turn can provide a useful reference for earthquake emergency response and scientific decision making for earthquake disaster relief.

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References

  1. Amadio C, Fragiacomo M, Rajgelj S (2003). The effects of repeated earthquake ground motions on the non-linear response of SDOF systems. Earthquake Engineering & Structural Dynamics, 32(2): 291–308

    Article  Google Scholar 

  2. Ancheta T D, Darragh R B, Stewart J P, Seyhan E, Silva W J, Chiou B S J, Wooddell K E, Graves R W, Kottke A R, Boore D M, Kishida T, Donahue J L (2014). NGA-West2 database. Earthquake Spectra, 30(3): 989–1005

    Article  Google Scholar 

  3. Applied Technology Council (1985). Earthquake damage evaluation data for California. Final Report. Redwood City, CA: Applied Technology Council

    Google Scholar 

  4. Bommer J J, Martínez-Pereira A (1999). The effective duration of earthquake strong motion. Journal of Earthquake Engineering, 3(2): 127–172

    Google Scholar 

  5. Bommer J J, Stafford P J, Alarcón J E (2009). Empirical equations for the prediction of the significant, bracketed, and uniform duration of earthquake ground motion. Bulletin of the Seismological Society of America, 99(6): 3217–3233

    Article  Google Scholar 

  6. CESMD (2019a). Berkeley Earthquake of 20 Oct 2011 (4.0 Mw, 14:41:04 PM PDT, 37.86 N 122.25 W, Depth 8.0 km). CESMD Internet Data Report

  7. CESMD (2019b). Berkeley Earthquake of 20 Oct 2011 (3.8 Mw, 20:16:05 PM PDT, 37.87 N 122.25 W, Depth 9.6 km). CESMD Internet Data Report

  8. Chen H, Xie Q C, Li Z Q, Xue W, Liu K (2017). Seismic damage to structures in the 2015 Nepal earthquake sequences. Journal of Earthquake Engineering, 21(4): 551–578

    Article  Google Scholar 

  9. Chiou B, Darragh R, Gregor N, Silva W (2008). NGA project strong-motion database. Earthquake Spectra, 24(1): 23–44

    Article  Google Scholar 

  10. Du W Q, Wang G (2017). Prediction equations for ground-motion significant durations using the NGA-West2 database. Bulletin of the Seismological Society of America, 107(1): 319–333

    MathSciNet  Article  Google Scholar 

  11. Federal Emergency Management Agency (FEMA) (2012). Multi-Hazard Loss Estimation Methodology—Earthquake Model, HAZUS-MH 2.1 Technical Manual. Washington DC: Department of Homeland Security, Federal Emergency Management Agency, Mitigation Division

    Google Scholar 

  12. Fragiacomo M, Amadio C, Macorini L (2004). Seismic response of steel frames under repeated earthquake ground motions. Engineering Structures, 26(13): 2021–2035

    Article  Google Scholar 

  13. Goda K (2012). Nonlinear response potential of mainshock-aftershock sequences from Japanese earthquakes. Bulletin of the Seismological Society of America, 102(5): 2139–2156

    Article  Google Scholar 

  14. Goda K, Salami M R (2014). Inelastic seismic demand estimation of wood-frame houses subjected to mainshock-aftershock sequences. Bulletin of Earthquake Engineering, 12(2): 855–874

    Article  Google Scholar 

  15. Goda K, Taylor C A (2012). Effects of aftershocks on peak ductility demand due to strong ground motion records from shallow crustal earthquakes. Earthquake Engineering & Structural Dynamics, 41(15): 2311–2330

    Google Scholar 

  16. Haddadi H, Shakal A, Huang M, Parrish J, Stephens C, Savage W U, Leith W S (2012). Report on progress at the Center for Engineering Strong Motion Data (CESMD). In: The 15th World Conference on Earthquake Engineering. Lisbon, Portugal, 24–28

  17. Hatzigeorgiou G D, Beskos D E (2009). Inelastic displacement ratios for SDOF structures subjected to repeated earthquakes. Engineering Structures, 31(11): 2744–2755

    Article  Google Scholar 

  18. Hatzivassiliou M, Hatzigeorgiou G D (2015). Seismic sequence effects on three-dimensional reinforced concrete buildings. Soil Dynamics and Earthquake Engineering, 72: 77–88

    Article  Google Scholar 

  19. Hori M, Ichimura T, Wijerathne L, Ohtani H, Chen J, Fujita K, Motoyama H (2018). Application of high performance computing to earthquake hazard and disaster estimation in urban area. Frontiers in Built Environment, 4: 1

    Article  Google Scholar 

  20. Hosseinpour F, Abdelnaby A E (2017). Effect of different aspects of multiple earthquakes on the nonlinear behavior of RC structures. Soil Dynamics and Earthquake Engineering, 92: 706–725

    Article  Google Scholar 

  21. Hu S, Gardoni P, Xu L (2018). Stochastic procedure for the simulation of synthetic main shock-aftershock ground motion sequences. Earthquake Engineering & Structural Dynamics, 47(11): 2275–2296

    Article  Google Scholar 

  22. Jalayer F, Asprone D, Prota A, Manfredi G (2011). A decision support system for post-earthquake reliability assessment of structures subjected to aftershocks: An application to L’Aquila earthquake, 2009. Bulletin of Earthquake Engineering, 9(4): 997–1014

    Article  Google Scholar 

  23. Jalayer F, Ebrahimian H (2017). Seismic risk assessment considering cumulative damage due to aftershocks. Earthquake Engineering & Structural Dynamics, 46(3): 369–389

    Article  Google Scholar 

  24. Jamnani H H, Amiri J V, Rajabnejad H (2018). Energy distribution in RC shear wall-frame structures subject to repeated earthquakes. Soil Dynamics and Earthquake Engineering, 107: 116–128

    Article  Google Scholar 

  25. Kim B, Shin M (2017). A model for estimating horizontal aftershock ground motions for active crustal regions. Soil Dynamics and Earthquake Engineering, 92: 165–175

    Article  Google Scholar 

  26. Li Q W, Ellingwood B R (2007). Performance evaluation and damage assessment of steel frame buildings under mainshock-aftershock earthquake sequences. Earthquake Engineering & Structural Dynamics, 36(3): 405–427

    Article  Google Scholar 

  27. Lu X Z, Guan H (2017). Nonlinear MDOF models for earthquake disaster simulation of urban buildings. In: Earthquake Disaster Simulation of Civil Infrastructures: From Tall Buildings to Urban Areas. Singapore: Springer, 257–301

    Google Scholar 

  28. Lu X Z, Han B, Hori M, Xiong C, Xu Z (2014). A coarse-grained parallel approach for seismic damage simulations of urban areas based on refined models and GPU/CPU cooperative computing. Advances in Engineering Software, 70: 90–103

    Article  Google Scholar 

  29. Onur T, Ventura C E, Finn W D L (2006). A comparison of two regional seismic damage estimation methodologies. Canadian Journal of Civil Engineering, 33(11): 1401–1409

    Article  Google Scholar 

  30. Pacific Earthquake Engineering Research Center (PEER) (2019). PEER Ground Motion Database. Pacific Earthquake Engineering Research Center

  31. Polese M, Ludovico M D, Prota A, Manfredi G (2013). Damage-dependent vulnerability curves for existing buildings. Advances in Engineering Software, 42: 853–870

    Google Scholar 

  32. Potter S H, Becker J S, Johnston D M, Rossiter K P (2015). An overview of the impacts of the 2010–2011 Canterbury earthquakes. International Journal of Disaster Risk Reduction, 14: 6–14

    Article  Google Scholar 

  33. Raghunandan M, Liel A, Ryu H, Luco N, Uma S (2012). Aftershock fragility curves and tagging assessments for a mainshock-damaged building. In: Proceedings of the 15th World Conference on Earthquake Engineering. Lisbon, Portugal, 23230–23240

  34. Raghunandan M, Liel A B, Luco N (2015). Aftershock collapse vulnerability assessment of reinforced concrete frame structures. Earthquake Engineering & Structural Dynamics, 44(3): 419–s439

    Article  Google Scholar 

  35. Rinaldin G, Amadio C (2018). Effects of seismic sequences on masonry structures. Engineering Structures, 166: 227–239

    Article  Google Scholar 

  36. Ruiz-García J, Negrete-Manriquez J C (2011). Evaluation of drift demands in existing steel frames under as-recorded far-field and near-fault mainshock-aftershock seismic sequences. Engineering Structures, 33(2): 621–634

    Article  Google Scholar 

  37. Ruiz-García J, Yaghmaei-Sabegh S, Bojórquez E (2018). Three-dimensional response of steel moment-resisting buildings under seismic sequences. Engineering Structures, 175: 399–414

    Article  Google Scholar 

  38. Steelman J S, Hajjar J F (2009). Influence of inelastic seismic response modeling on regional loss estimation. Engineering Structures, 31(12): 2976–2987

    Article  Google Scholar 

  39. Valensise G, Tarabusi G, Guidoboni E, Ferrari G (2017). The forgotten vulnerability: A geology- and history-based approach for ranking the seismic risk of earthquake-prone communities of the Italian Apennines. International Journal of Disaster Risk Reduction, 25: 289–300

    Article  Google Scholar 

  40. Varum H, Furtado A, Rodrigues H, Dias-Oliveira J, Vila-Pouca N, Arêde A (2017). Seismic performance of the infill masonry walls and ambient vibration tests after the Ghorka 2015, Nepal earthquake. Bulletin of Earthquake Engineering, 15(3): 1185–1212

    Article  Google Scholar 

  41. Wan Y G, Wan Y K, Jin Z T, Sheng S Z, Liu Z C, Yang F, Feng T (2017). Rupture distribution of the 1976 Tangshan earthquake sequence inverted from geodetic data. Chinese Journal of Geophysics, 60(6): 583–601

    Article  Google Scholar 

  42. Wooddell K E, Abrahamson N A (2014). Classification of main shocks and aftershocks in the NGA-West2 database. Earthquake Spectra, 30(3): 1257–1267

    Article  Google Scholar 

  43. Xiong C, Lu X Z, Guan H, Xu Z (2016). A nonlinear computational model for regional seismic simulation of tall buildings. Bulletin of Earthquake Engineering, 14(4): 1047–1069

    Article  Google Scholar 

  44. Xiong C, Lu X Z, Lin X C, Xu Z, Ye L P (2017). Parameter determination and damage assessment for THA-based regional seismic damage prediction of multi-story buildings. Journal of Earthquake Engineering, 21(3): 461–485

    Article  Google Scholar 

  45. Xu Z, Lu X Z, Guan H, Han B, Ren A Z (2014). Seismic damage simulation in urban areas based on a high-fidelity structural model and a physics engine. Natural Hazards, 71(3): 1679–1693

    Article  Google Scholar 

  46. Yepes-Estrada C, Silva V, Rossetto T, D’Ayala D, Ioannou I, Meslem A, Crowley H (2016). The global earthquake model physical vulnerability database. Earthquake Spectra, 32(4): 2567–2585

    Article  Google Scholar 

  47. Zhai C H, Ji D F, Wen W P, Lei W D, Xie L L, Gong M S (2016). The inelastic input energy spectra for main shock-aftershock sequences. Earthquake Spectra, 32(4): 2149–2166

    Article  Google Scholar 

  48. Zhai C H, Wen W P, Li S, Chen Z Q, Chang Z W, Xie L L (2014). The damage investigation of inelastic SDOF structure under the mainshock-aftershock sequence-type ground motions. Soil Dynamics and Earthquake Engineering, 59: 30–41

    Article  Google Scholar 

  49. Zheng Y, Ni S D, Xie Z J, Lv J, Ma H S, Sommerville P (2010). Strong aftershocks in the northern segment of the Wenchuan earthquake rupture zone and their seismotectonic implications. Earth, Planets, and Space, 62(11): 881–886

    Article  Google Scholar 

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Correspondence to Xinzheng Lu.

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The authors are grateful for the financial support received from the National Key R&D Program (Grant No. 2018YFC1504401) and the National Natural Science Foundation of China (Grant No. 51778341).

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Lu, X., Cheng, Q., Xu, Z. et al. Regional seismic-damage prediction of buildings under mainshock—aftershock sequence. Front. Eng. Manag. 8, 122–134 (2021). https://doi.org/10.1007/s42524-019-0072-x

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Keywords

  • regional seismic damage prediction
  • city-scale nonlinear time-history analysis
  • mainshock-aftershock sequence
  • multiple degree-of-freedom (MDOF) model
  • 2014 Ludian earthquake