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Front. Eng    2021, Vol. 8 Issue (1) : 122-134    https://doi.org/10.1007/s42524-019-0072-x
RESEARCH ARTICLE
Regional seismic-damage prediction of buildings under mainshock–aftershock sequence
Xinzheng LU1(), Qingle CHENG2, Zhen XU3, Chen XIONG4
1. Key Laboratory of Civil Engineering Safety and Durability of China Education Ministry, Department of Civil Engineering, Tsinghua University, Beijing 100084, China
2. Beijing Engineering Research Center of Steel and Concrete Composite Structures, Tsinghua University, Beijing 100084, China
3. Beijing Key Laboratory of Urban Underground Space Engineering, School of Civil and Resource Engineering, University of Science and Technology Beijing, Beijing 100083, China
4. Guangdong Provincial Key Laboratory of Durability for Marine Civil Engineering, Shenzhen University, Shenzhen 518060, China
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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     
Corresponding Author(s): Xinzheng LU   
Just Accepted Date: 19 December 2019   Online First Date: 17 January 2020    Issue Date: 15 January 2021
 Cite this article:   
Xinzheng LU,Qingle CHENG,Zhen XU, et al. Regional seismic-damage prediction of buildings under mainshock–aftershock sequence[J]. Front. Eng, 2021, 8(1): 122-134.
 URL:  
https://academic.hep.com.cn/fem/EN/10.1007/s42524-019-0072-x
https://academic.hep.com.cn/fem/EN/Y2021/V8/I1/122
Fig.1  Framework for predicting regional seismic damage of buildings under an MS–AS sequence.
Fig.2  (a) Nonlinear MDOF shear model; (b) MDOF flexural–shear model; (c) tri-linear backbone curve; and (d) single-parameter hysteretic model used in city-scale nonlinear THA (Lu and Guan, 2017).
ID Building name Mainshock (Mw) Aftershock (Mw) Number of stories Structural type Year built PGA of MS (m/s2) PGA of AS (m/s2)
1 Bishop two-story office building M4.8 Big Pine earthquake of 16 Feb 2016 M4.3 Big Pine earthquake of 16 Feb 2016 2 S1L 1976 0.06 0.05
2 Oakland 11-story residential building M4.0 Berkeley earthquake of 20 Oct 2011 M3.8 Berkeley earthquake of 20 Oct 2011 11 C2H 1972 0.53 0.63
3 Walnut Creek 10-story commercial building M5.9 Livermore earthquake of 24 Jan 1980 M5.8 Livermore earthquake of 26 Jan 1980 10 C2H 1970 0.29 0.54
4 Walnut Creek 10-story commercial building M4.0 Berkeley earthquake of 20 Oct 2011 M3.8 Berkeley earthquake of 20 Oct 2011 10 C2H 1970 0.07 0.07
5 Fortuna one-story supermarket building M7.1 Petrolia earthquake of 25 Apr 1992 M6.5 Petrolia aftershock 1 of 26 Apr 1992 1 RM1L 1979 1.36 1.57
6 Oakland 24-story residential building M4.0 Berkeley earthquake of 20 Oct 2011 M3.8 Berkeley earthquake of 20 Oct 2011 24 C2H 1964 0.22 0.17
7 Berkeley two-story hospital M4.0 Berkeley earthquake of 20 Oct 2011 M3.8 Berkeley earthquake of 20 Oct 2011 2 S2L 1984 0.62 0.38
8 Piedmont three-story school office building M4.0 Berkeley earthquake of 20 Oct 2011 M3.8 Berkeley earthquake of 20 Oct 2011 3 C2L 1973 0.35 0.29
9 Oakland three-story commercial building M4.0 Berkeley earthquake of 20 Oct 2011 M3.8 Berkeley earthquake of 20 Oct 2011 3 S5L 1972 0.18 0.27
10 San Francisco-six-story gov office building M4.0 Berkeley earthquake of 20 Oct 2011 M3.8 Berkeley earthquake of 20 Oct 2011 6 S5M 1987 0.25 0.29
Tab.1  Information of buildings and MS–AS
Fig.3  Comparison between as-recorded seismic responses and results calculated by MDOF models.
Fig.4  Comparison of roof displacement histories for building #3 shown in Table 1.
ID Number of stories Structural type MS–AS information References
1 20 Steel frame 2010/2011 Canterbury earthquakes Ruiz-García et al. (2018)
2 3 Steel frame 1980 Mammoth Lakes earthquakes
3 9 Steel frame 1980 Mammoth Lakes earthquakes
4 3 Steel frame 2011 Tohoku earthquakes
5 9 Steel frame 2011 Tohoku earthquakes
6 4 Steel frame 1980 Mammoth Lakes earthquakes Ruiz-García and Negrete-Manriquez (2011)
7 8 Steel frame 1980 Mammoth Lakes earthquakes
8 12 Steel frame 1980 Mammoth Lakes earthquakes
9 3 RC frame Imperial Valley earthquakes (MS–AS) Hatzivassiliou and Hatzigeorgiou (2015)
10 3 RC frame Imperial Valley earthquake (mainshock)
Tab.2  Building information and MS–AS sequences selected from the literature
Fig.5  Comparison of IDRs provided in the literature and calculated by the MDOF model for buildings with steel frame shown in Table 2.
Fig.6  Typical comparisons of IDRs provided in the literature and calculated by the MDOF model for buildings #1, #2, and #7 shown in Table 2.
Fig.7  Comparison of responses for the RC frame (buildings #9 and #10 shown in Table 2) under an MS–AS sequence and a mainshock, respectively.
Fig.8  Comparison between as-recorded PSAs and simulation results.
Magnitude Mw Location Focal depth (km)
Mainshock 4.0 37.86 N, 122.25 W 8.0
Aftershock 3.8 37.87 N, 122.25 W 9.6
Tab.3  Mainshock and aftershock information of the 2011 Berkeley earthquake
Fig.9  Ground motions recorded at the ORB station.
Fig.10  Comparison between the predicted and actual response spectrum of ground motion recorded at the ORB station.
Fig.11  Target response spectrum and the response spectrum of the selected ground motions.
Magnitude (Mw) Rupture distance (km) Focal depth (km) Significant duration DS5–95 (s)
Mainshock 6.1 14.9 12.0 -
Aftershock 1 6.1 14.9 12.0 5.55
Aftershock 2 5.5 14.9 12.0 4.57
Aftershock 3 5.0 14.9 12.0 3.73
Aftershock 4 5.5 13.0 12.0 4.28
Tab.4  Mainshock and aftershock information
Fig.12  Ground motions recorded at Longtoushan station.
Fig.13  Response spectrums of different aftershocks.
Fig.14  Seismic damage results of buildings for different earthquake scenarios.
Fig.15  Seismic damage results of buildings with different structural types.
ID Structural type Number of stories Mainshock MS–AS 1 MS–AS 2 MS–AS 3 MS–AS 4
1 RM2L 3 0.0206 0.0474 0.0231 0.0206 0.0232
Extensive Complete Extensive Extensive Extensive
2 RM2L 2 0.0203 0.0452 0.0226 0.0203 0.0227
Extensive Complete Extensive Extensive Extensive
Tab.5  Maximum IDR and damage states of typical buildings
1 C Amadio, M Fragiacomo, S Rajgelj (2003). The effects of repeated earthquake ground motions on the non-linear response of SDOF systems. Earthquake Engineering & Structural Dynamics, 32(2): 291–308
https://doi.org/10.1002/eqe.225
2 T D Ancheta, R B Darragh, J P Stewart, E Seyhan, W J Silva, B S J Chiou, K E Wooddell, R W Graves, A R Kottke, D M Boore, T Kishida, J L Donahue (2014). NGA-West2 database. Earthquake Spectra, 30(3): 989–1005
https://doi.org/10.1193/070913EQS197M
3 Applied Technology Council (1985). Earthquake damage evaluation data for California. Final Report. Redwood City, CA: Applied Technology Council
4 J J Bommer, A Martínez-Pereira (1999). The effective duration of earthquake strong motion. Journal of Earthquake Engineering, 3(2): 127–172
https://doi.org/10.1080/13632469909350343
5 J J Bommer, P J Stafford, J E Alarcón (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
https://doi.org/10.1785/0120080298
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 H Chen, Q C Xie, Z Q Li, W Xue, K Liu (2017). Seismic damage to structures in the 2015 Nepal earthquake sequences. Journal of Earthquake Engineering, 21(4): 551–578
https://doi.org/10.1080/13632469.2016.1185055
9 B Chiou, R Darragh, N Gregor, W Silva (2008). NGA project strong-motion database. Earthquake Spectra, 24(1): 23–44
https://doi.org/10.1193/1.2894831
10 W Q Du, G Wang (2017). Prediction equations for ground—motion significant durations using the NGA-West2 database. Bulletin of the Seismological Society of America, 107(1): 319–333
https://doi.org/10.1785/0120150352
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 M Fragiacomo, C Amadio, L Macorini (2004). Seismic response of steel frames under repeated earthquake ground motions. Engineering Structures, 26(13): 2021–2035
https://doi.org/10.1016/j.engstruct.2004.08.005
13 K Goda (2012). Nonlinear response potential of mainshock–aftershock sequences from Japanese earthquakes. Bulletin of the Seismological Society of America, 102(5): 2139–2156
https://doi.org/10.1785/0120110329
14 K Goda, M R Salami (2014). Inelastic seismic demand estimation of wood-frame houses subjected to mainshock–aftershock sequences. Bulletin of Earthquake Engineering, 12(2): 855–874
https://doi.org/10.1007/s10518-013-9534-4
15 K Goda, C A Taylor (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
https://doi.org/10.1002/eqe.2188
16 H Haddadi, A Shakal, M Huang, J Parrish, C Stephens, W U Savage, W S Leith (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 G D Hatzigeorgiou, D E Beskos (2009). Inelastic displacement ratios for SDOF structures subjected to repeated earthquakes. Engineering Structures, 31(11): 2744–2755
https://doi.org/10.1016/j.engstruct.2009.07.002
18 M Hatzivassiliou, G D Hatzigeorgiou (2015). Seismic sequence effects on three-dimensional reinforced concrete buildings. Soil Dynamics and Earthquake Engineering, 72: 77–88
https://doi.org/10.1016/j.soildyn.2015.02.005
19 M Hori, T Ichimura, L Wijerathne, H Ohtani, J Chen, K Fujita, H Motoyama (2018). Application of high performance computing to earthquake hazard and disaster estimation in urban area. Frontiers in Built Environment, 4: 1
https://doi.org/10.3389/fbuil.2018.00001
20 F Hosseinpour, A E Abdelnaby (2017). Effect of different aspects of multiple earthquakes on the nonlinear behavior of RC structures. Soil Dynamics and Earthquake Engineering, 92: 706–725
https://doi.org/10.1016/j.soildyn.2016.11.006
21 S Hu, P Gardoni, L Xu (2018). Stochastic procedure for the simulation of synthetic main shock–aftershock ground motion sequences. Earthquake Engineering & Structural Dynamics, 47(11): 2275–2296
https://doi.org/10.1002/eqe.3068
22 F Jalayer, D Asprone, A Prota, G Manfredi (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
https://doi.org/10.1007/s10518-010-9230-6
23 F Jalayer, H Ebrahimian (2017). Seismic risk assessment considering cumulative damage due to aftershocks. Earthquake Engineering & Structural Dynamics, 46(3): 369–389
https://doi.org/10.1002/eqe.2792
24 H H Jamnani, J V Amiri, H Rajabnejad (2018). Energy distribution in RC shear wall-frame structures subject to repeated earthquakes. Soil Dynamics and Earthquake Engineering, 107: 116–128
https://doi.org/10.1016/j.soildyn.2018.01.010
25 B Kim, M Shin (2017). A model for estimating horizontal aftershock ground motions for active crustal regions. Soil Dynamics and Earthquake Engineering, 92: 165–175
https://doi.org/10.1016/j.soildyn.2016.09.040
26 Q W Li, B R Ellingwood (2007). Performance evaluation and damage assessment of steel frame buildings under mainshock–aftershock earthquake sequences. Earthquake Engineering & Structural Dynamics, 36(3): 405–427
https://doi.org/10.1002/eqe.667
27 X Z Lu, H Guan (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 X Z Lu, B Han, M Hori, C Xiong, Z Xu (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
https://doi.org/10.1016/j.advengsoft.2014.01.010
29 T Onur, C E Ventura, W D L Finn (2006). A comparison of two regional seismic damage estimation methodologies. Canadian Journal of Civil Engineering, 33(11): 1401–1409
https://doi.org/10.1139/l06-084
30 Pacific Earthquake Engineering Research Center (PEER) (2019). PEER Ground Motion Database. Pacific Earthquake Engineering Research Center
31 M Polese, M D Ludovico, A Prota, G Manfredi (2013). Damage-dependent vulnerability curves for existing buildings. Advances in Engineering Software, 42: 853–870
32 S H Potter, J S Becker, D M Johnston, K P Rossiter (2015). An overview of the impacts of the 2010–2011 Canterbury earthquakes. International Journal of Disaster Risk Reduction, 14: 6–14
https://doi.org/10.1016/j.ijdrr.2015.01.014
33 M Raghunandan, A Liel, H Ryu, N Luco, S Uma (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 M Raghunandan, A B Liel, N Luco (2015). Aftershock collapse vulnerability assessment of reinforced concrete frame structures. Earthquake Engineering & Structural Dynamics, 44(3): 419–439
https://doi.org/10.1002/eqe.2478
35 G Rinaldin, C Amadio (2018). Effects of seismic sequences on masonry structures. Engineering Structures, 166: 227–239
https://doi.org/10.1016/j.engstruct.2018.03.092
36 J Ruiz-García, J C Negrete-Manriquez (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
https://doi.org/10.1016/j.engstruct.2010.11.021
37 J Ruiz-García, S Yaghmaei-Sabegh, E Bojórquez (2018). Three-dimensional response of steel moment-resisting buildings under seismic sequences. Engineering Structures, 175: 399–414
https://doi.org/10.1016/j.engstruct.2018.08.050
38 J S Steelman, J F Hajjar (2009). Influence of inelastic seismic response modeling on regional loss estimation. Engineering Structures, 31(12): 2976–2987
https://doi.org/10.1016/j.engstruct.2009.07.026
39 G Valensise, G Tarabusi, E Guidoboni, G Ferrari (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
https://doi.org/10.1016/j.ijdrr.2017.09.014
40 H Varum, A Furtado, H Rodrigues, J Dias-Oliveira, N Vila-Pouca, A Arêde (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
https://doi.org/10.1007/s10518-016-9999-z
41 Y G Wan, Y K Wan, Z T Jin, S Z Sheng, Z C Liu, F Yang, T Feng (2017). Rupture distribution of the 1976 Tangshan earthquake sequence inverted from geodetic data. Chinese Journal of Geophysics, 60(6): 583–601
https://doi.org/10.1002/cjg2.30070
42 K E Wooddell, N A Abrahamson (2014). Classification of main shocks and aftershocks in the NGA-West2 database. Earthquake Spectra, 30(3): 1257–1267
https://doi.org/10.1193/071913EQS208M
43 C Xiong, X Z Lu, H Guan, Z Xu (2016). A nonlinear computational model for regional seismic simulation of tall buildings. Bulletin of Earthquake Engineering, 14(4): 1047–1069
https://doi.org/10.1007/s10518-016-9880-0
44 C Xiong, X Z Lu, X C Lin, Z Xu, L P Ye (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
https://doi.org/10.1080/13632469.2016.1160009
45 Z Xu, X Z Lu, H Guan, B Han, A Z Ren (2014). Seismic damage simulation in urban areas based on a high-fidelity structural model and a physics engine. Natural Hazards, 71(3): 1679–1693
https://doi.org/10.1007/s11069-013-0972-8
46 C Yepes-Estrada, V Silva, T Rossetto, D D’Ayala, I Ioannou, A Meslem, H Crowley (2016). The global earthquake model physical vulnerability database. Earthquake Spectra, 32(4): 2567–2585
https://doi.org/10.1193/011816EQS015DP
47 C H Zhai, D F Ji, W P Wen, W D Lei, L L Xie, M S Gong (2016). The inelastic input energy spectra for main shock–aftershock sequences. Earthquake Spectra, 32(4): 2149–2166
https://doi.org/10.1193/121315EQS182M
48 C H Zhai, W P Wen, S Li, Z Q Chen, Z W Chang, L L Xie (2014). The damage investigation of inelastic SDOF structure under the mainshock–aftershock sequence-type ground motions. Soil Dynamics and Earthquake Engineering, 59: 30–41
https://doi.org/10.1016/j.soildyn.2014.01.003
49 Y Zheng, S D Ni, Z J Xie, J Lv, H S Ma, P Sommerville (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
https://doi.org/10.5047/eps.2009.06.001
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