Abstract
Earthquake-induced building collapses and casualties have been effectively controlled in the last two decades. However, earthquake-induced economic losses have continued to rise. Following the objective and procedure of next-generation performance-based seismic design, the economic loss prediction method proposed by FEMA-P58 is extended to regional earthquake loss prediction in this study. The engineering demand parameters for a large number of buildings within a region are efficiently obtained through nonlinear time history analysis using multi-story concentrated-mass shear models. The building data, including structural and nonstructural components, are obtained through field investigation, structural and architectural drawings, and default database published in the FEMA-P58 document. A case study of Tsinghua University campus in Beijing is performed to demonstrate the implementation and advantage using proposed FEMA-P58 method for regional earthquake loss prediction. The results show the advancement in loss simulation for a region, and in identifying the influence of the different ground motion characteristics (e.g., velocity pulse) on the regional loss.
Similar content being viewed by others
Notes
In this work, the economic losses of different years are adjusted into 2011 US$ considering inflation. The adjustment factors are calculated according to the Consumer Price Index (CPI) statistics provided by U.S. Department of Labor Bureau of Labor Statistics or by referring to Coin News (2015). The adjustment factor from 2010 to 2011 is 1.03.
References
American Society of Civil Engineers (ASCE) (2010) Minimum design loads for buildings and other structures, ASCE/SEI 7-10, Reston, VA
ATC (1996) Seismic evaluation and retrofit of concrete buildings (ATC-40). Applied Technology Council, Redwood City
China Ministry of Construction (CMC) (2010) Code for seismic design of buildings, GB50011-2010. China Architecture and Building Press, Beijing (in Chinese)
Coin News (2015) US Inflation Calculator. http://www.usinflationcalculator.com/
Cornell CA, Krawinkler H (2000) Progress and challenges in seismic performance assessment. PEER Center News 3(2):1–3
D’Ayala D, Meslem A, Vamvatsikos D, Porter K, Rossetto T, Crowley H, Silva V (2015) Guidelines for analytical vulnerability assessment of low/mid-rise buildings, GEM technical report 2015-08 V1.0.0
Federal Emergency Management Agency (FEMA) (1999) Earthquake loss estimation methodology—Hazus99, Technical Manual, Washington, DC
Federal Emergency Management Agency (FEMA) (2006) Next-generation performance-based seismic design guidelines program plan for new and existing buildings. Technical report FEMA-445, Washington DC
Federal Emergency Management Agency (FEMA) (2009) Quantification of building seismic performance factors. Technical report FEMA-P695, Washington DC
Federal Emergency Management Agency (FEMA) (2012a) Multi-Hazard loss estimation methodology Hazus-MH 2.1 Advanced Engineering Building Module (AEBM) Technical and User’s Manual. Washington, DC
Federal Emergency Management Agency (FEMA) (2012b) Seismic performance assessment of buildings volume 1—methodology, Technical report FEMA-P58, Washington, DC
Federal Emergency Management Agency (FEMA) (2012c) Seismic performance assessment of buildings volume 2—implementation guide, Technical report FEMA-P58, Washington, DC
Federal Emergency Management Agency (FEMA) (2013) Multi-hazard loss estimation methodology—earthquake model, Hazus-MH 2.1, Technical Manual, Washington, DC
Guha-Sapir D, Vos F, Below R, Ponserre S (2011) Annual disaster statistical review 2010: the numbers and trends. Centre for Research on the Epidemiology of Disasters (CRED), Brussels
Kircher CA, Whitman RV, Holmes WT (2006) Hazus earthquake loss estimation methods. Nat Hazards Rev 7(2):45–59
Krawinkler H, Seneviratna GDPK (1998) Pros and cons of a pushover analysis of seismic performance evaluation. Eng Struct 20(4):452–464
Lu X, Ye LP, Lu XZ, Li MK, Ma XW (2013) An improved ground motion intensity measure for super high-rise buildings. Sci China Technol Sci 56(6):1525–1533
Lu XZ, 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. Adv Eng Softw 70:90–103
Luco N, Mori Y, Funahashi Y, Cornell CA, Nakashima M (2003) Evaluation of predictors of non-linear seismic demands using ‘fishbone’ models of SMRF buildings. Earthq Eng Struct D 32(14):2267–2288
Luo KH, Wang YY (2012) Researches about the conversion relationships among the parameters of ground motions in the seismic design codes of China, America and Europe. In: Proceedings of the 15th world conference on earthquake engineering, Lisbon, Portugal
Meslem A, D’Ayala D (2012) Toward worldwide guidelines for the development of analytical vulnerability functions and fragility curves at regional level. In: Proceedings of the 15th world conference on earthquake engineering, Lisbon, Portugal
Mid-America Earthquake Center (MAE Center) (2010) The Maule (Chile) earthquake of February 27, 2010: consequence assessment and case studies. Report No. 10-04, Urbana, IL
Moehle J, Deierlein GG (2004) A framework methodology for performance-based earthquake engineering, paper no. 679. In: Proceedings of the 13th world conference on earthquake engineering, Vancouver, BC, Canada
Nakashima M, Ogawa K, Inoue K (2002) Generic frame model for simulation of earthquake responses of steel moment frames. Earthq Eng Struct D 31(3):671–692
Peterson J, Small MJ (2012) Methodology for benefit-cost analysis of seismic codes. Nat Hazards 63:1039–1053
Ponserre S, Guha-Sapir D, Vos F, Below R (2012) Annual disaster statistical review 2011: the numbers and trends. Centre for Research on the Epidemiology of Disasters (CRED), Brussels
Remo JW, Pinter N (2012) Hazus-MH earthquake modeling in the central USA. Nat Hazards 63:1055–1081
Shi W, Lu XZ, Guan H, Ye LP (2014) Development of seismic collapse capacity spectra and parametric study. Adv Struct Eng 17(9):1241–1256
Shome N, Jayaram N, Krawinkler H, Rahnama M (2015) Loss estimation of tall buildings designed for the peer tall building initiative project. Earthq Spectra 31(3):1309–1336
Shoraka MB, Yang TY, Elwood KJ (2013) Seismic loss estimation of non-ductile reinforced concrete buildings. Earthq Eng Struct D 42(2):297–310
Smyrou E, Tasiopoulou P, Bal HE, Gazetas G (2011) Ground motions versus geotechnical and structural damage in the February 2011 Christchurch earthquake. Seismol Res Lett 82(6):882–892
Sobhaninejad G, Hori M, Kabeyasawa T (2011) Enhancing integrated earthquake simulation with high performance computing. Adv Eng Softw 42(5SI):286–292
Xiong C, Lu XZ, Guan H, Xu Z (2016) A nonlinear computational model for regional seismic simulation of tall buildings. Bull Earthq Eng 14(4):1047–1069
Xu Z, Lu XZ, Guan H, Han B, Ren AZ (2014) Seismic damage simulation in urban areas based on a high-fidelity structural model and a physics engine. Nat Hazards 71(3):1679–1693
Xu Z, Lu XZ, Guan H, Tian Y, Ren AZ (2016) Simulation of earthquake-induced hazards of falling exterior non-structural components and its application to emergency shelter design. Nat Hazards 80(2):935–950
Yang TY, Murphy M (2015) Performance evaluation of seismic force resisting systems for low-rise steel buildings in Canada. Earthq Spectra 31(4):1969–1990
Yang TY, Moehle JP, Stojadinovic B, Der Kiureghian A (2009) Seismic performance evaluation of facilities: methodology and implementation. J Struct Eng-ASCE 135(10):1146–1154
Yang TY, Moehle JP, Bozorgnia Y, Zareian F, Wallace JW (2012) Performance assessment of tall concrete core-wall building designed using two alternative approaches. Earthq Eng Struct D 41(11):1515–1531
Yang TY, Atkinson JC, Tobber L (2014) Detailed seismic performance assessment of high-value contents laboratory facility. Earthq Spectra. doi:10.1193/092313EQS259M
Acknowledgments
The authors are grateful for the help from Runhua Gong, Qiuhan Huang, Huiping Li, Jian Liu, Shixuan Liu, Yizhe Meng, Yao Ming, Jian Yang, and Zhebiao Yang in the investigation and collection of basic building data, building design drawings, and property distribution, which forms the data basis of this work. The authors are also grateful for the financial support received from the National Natural Science Foundation of China (Nos. 51578320, 51378299), the National Key Technology R&D Program (No. 2015BAK14B02), and the National Non-profit Institute Research Grant of IGP-CEA (Grant No: DQJB14C01).
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Zeng, X., Lu, X., Yang, T.Y. et al. Application of the FEMA-P58 methodology for regional earthquake loss prediction. Nat Hazards 83, 177–192 (2016). https://doi.org/10.1007/s11069-016-2307-z
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11069-016-2307-z