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.

Keywords

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

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

[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

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

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

[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

[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

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

[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

[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

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

[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

[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

[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

[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

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

[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

[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

[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

[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

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

[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

[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

[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

[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

[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

[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

[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

[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

[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): 419–439

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

[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

[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

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

[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

[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

[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

[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

[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

[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

[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

[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

[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

[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

[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

RIGHTS & PERMISSIONS

Higher Education Press