Abstract
Fragility curve evaluation using ground motions compatible with conditional spectra allows for ground motion selection with good consistency with the hazard. However, this evaluation requires selecting ground motions from a database, which is not straightforward. Moreover, it relies on a fragility curve fitting procedure, which may fail to give a solution. Lastly, it estimates the statistical uncertainty of the curve based on simple bootstrap resampling. This paper proposes a novel framework for estimating fragility curves with two major improvements. First, the proposed fragility curve fitting procedure is not iterative and does not require an initial estimation of the curve parameters, unlike the existing curve fitting procedure. Second, the statistical uncertainty of fragility curves is estimated based on the Fisher’s information matrix, which is a rigorous alternative to bootstrap resampling. Moreover, stochastic ground motions compatible with the conditional spectra are generated and used as excitations. This is a practical alternative, as it does not require a ground motion database for scenario-specific selection. Results obtained with the developed framework are compared to results based on existing procedures in a case study of in-structure components in an industrial building. We analyze cases in which our curve fitting procedure gives a solution more reliably than the existing. Moreover, the developed procedure for estimating the uncertainty of fragility curves leads, in this case study, to better estimations for the statistical uncertainty of the fragility curves.
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Ay, B. Ö., Fox, M. J., & Sullivan, T. J. (2017). Technical Note: Practical challenges facing the selection of conditional spectrum-compatible accelerograms. Journal of Earthquake Engineering,21(1), 169–180. https://doi.org/10.1080/13632469.2016.1157527.
Baker, J. W. (2011). Conditional mean spectrum: Tool for ground-motion selection. Journal of Structural Engineering,137(3), 322–331. https://doi.org/10.1061/(ASCE)ST.1943-541X.0000215.
Baker, J. W. (2015). Efficient analytical fragility function fitting using dynamic structural analysis. Earthquake Spectra,31(1), 579–599. https://doi.org/10.1193/021113EQS025M.
Baker, J. W., & Jayaram, N. (2008). Correlation of spectral acceleration values from NGA ground motion models. Earthquake Spectra,24(1), 299–317. https://doi.org/10.1193/1.2857544.
Baker, J. W., & Lee, C. (2018). An improved algorithm for selecting ground motions to match a conditional spectrum. Journal of Earthquake Engineering,22(4), 708–723. https://doi.org/10.1080/13632469.2016.1264334.
Bazzurro, P., & Allin Cornell, C. (1999). Disaggregation of seismic hazard. Bulletin of the Seismological Society of America,89(2), 501–520.
Bernier, C., Monteiro, R., & Paultre, P. (2016). Using the conditional spectrum method for improved fragility assessment of concrete gravity dams in Eastern Canada. Earthquake Spectra,32(3), 1449–1468. https://doi.org/10.1193/072015EQS116M.
Bradley, B. A. (2010). A generalized conditional intensity measure approach and holistic ground-motion selection. Earthquake Engineering & Structural Dynamics. https://doi.org/10.1002/eqe.995.
Bradley, B. A., Burks, L. S., & Baker, J. W. (2015). Ground motion selection for simulation-based seismic hazard and structural reliability assessment: Simulation-based ground motion selection. Earthquake Engineering and Structural Dynamics,44(13), 2321–2340. https://doi.org/10.1002/eqe.2588.
Calvi, P. M. (2014). Relative displacement floor spectra for seismic design of non structural elements. Journal of Earthquake Engineering,18(7), 1037–1059. https://doi.org/10.1080/13632469.2014.923795.
Campbell, K. W., & Bozorgnia, Y. (2008). NGA ground motion model for the geometric mean horizontal component of PGA, PGV, PGD and 5% damped linear elastic response spectra for periods ranging from 0.01 to 10 s. Earthquake Spectra,24(1), 139–171. https://doi.org/10.1193/1.2857546.
Clouteau, D., Cottereau, R., & Lombaert, G. (2013). Dynamics of structures coupled with elastic media—A review of numerical models and methods. Journal of Sound and Vibration,332(10), 2415–2436. https://doi.org/10.1016/j.jsv.2012.10.011.
code_aster. (2017). Version 13.2. http://code-aster.org. Accessed 11 June 2019.
D’Ayala, D., Meslem, A., Vamvatsikos, D., Porter, K., Rossetto, T., & Silva, V. (2015). Guidelines for analytical vulnerability assessment—Low/mid-rise (Technical Report No. 2014– 12 V1.0.0). GEM. https://storage.globalquakemodel.org/media/publication/GEM-GC-VLM-AVALMGuidelines-201412v01.pdf. Accessed 11 June 2019.
Dabaghi, M., & Der Kiureghian, A. (2017). Stochastic model for simulation of near-fault ground motions: Stochastic model for simulation of near-fault ground motions. Earthquake Engineering and Structural Dynamics,46(6), 963–984. https://doi.org/10.1002/eqe.2839.
Ellingwood, B. R., & Kinali, K. (2009). Quantifying and communicating uncertainty in seismic risk assessment. Structural Safety,31(2), 179–187. https://doi.org/10.1016/j.strusafe.2008.06.001.
EPRI. (1994). Methodology for developing seismic fragilities (No. TR-103959). https://www.epri.com/#/pages/product/TR-103959/. Accessed 11 June 2019.
FEMA. (2012a). Seismic performance assessment of buildings, volume 1-Methodology (FEMA P-58-1). Washington, DC. https://www.atcouncil.org/files/FEMAP-58-1_Volume%201_Methodology.pdf. Accessed 11 June 2019.
FEMA. (2012b). Seismic performance assessment of buildings, volume 2-Implementation guide (FEMA P-58-2). Washington, DC. https://www.atcouncil.org/files/FEMAP-58-2_Volume%202_Implementation.pdf. Accessed 11 June 2019.
Frieden, B. R., & Gatenby, R. A. (2007). Exploratory data analysis using Fisher information. London: Springer. https://doi.org/10.1007/978-1-84628-777-0. (Accessed 26 September 2018).
Huang, Y.-N., Yen, W.-Y., & Whittaker, A. S. (2016). Correlation of horizontal and vertical components of strong ground motion for response-history analysis of safety-related nuclear facilities. Nuclear Engineering and Design,310, 273–279. https://doi.org/10.1016/j.nucengdes.2016.09.036.
Iervolino, I. (2017). Assessing uncertainty in estimation of seismic response for PBEE. Earthquake Engineering and Structural Dynamics,46(10), 1711–1723. https://doi.org/10.1002/eqe.2883.
Jalayer, F., & Cornell, C. A. (2009). Alternative non-linear demand estimation methods for probability-based seismic assessments. Earthquake Engineering and Structural Dynamics,38(8), 951–972. https://doi.org/10.1002/eqe.876.
Jayaram, N., Lin, T., & Baker, J. W. (2011). A computationally efficient ground-motion selection algorithm for matching a target response spectrum mean and variance. Earthquake Spectra,27(3), 797–815. https://doi.org/10.1193/1.3608002.
Johnson, T. P., & Dowell, R. K. (2017). Evaluation of the overstrength factor for nonstructural component anchorage into concrete via dynamic shaking table tests. Journal of Building Engineering,11, 205–215. https://doi.org/10.1016/j.jobe.2017.04.017.
Kennedy, R. P., Cornell, C. A., Campbell, R. D., Kaplan, S., & Perla, H. F. (1980). Probabilistic seismic safety study of an existing nuclear power plant. Nuclear Engineering and Design,59(2), 315–338. https://doi.org/10.1016/0029-5493(80)90203-4.
Kohrangi, M., Bazzurro, P., Vamvatsikos, D., & Spillatura, A. (2017). Conditional spectrum-based ground motion record selection using average spectral acceleration: Conditional spectrum-based record selection. Earthquake Engineering and Structural Dynamics,46(10), 1667–1685. https://doi.org/10.1002/eqe.2876.
Kuhlemeyer, R. L., & Lysmer, J. (1973). Finite element method accuracy for wave propagation problems. Journal of the Soil Mechanics and Foundations Division,99(5), 421–427.
Lallemant, D., Kiremidjian, A., & Burton, H. (2015). Statistical procedures for developing earthquake damage fragility curves: Statistical procedures for damage fragility curves. Earthquake Engineering and Structural Dynamics,44(9), 1373–1389. https://doi.org/10.1002/eqe.2522.
Lin, T., Harmsen, S. C., Baker, J. W., & Luco, N. (2013a). Conditional spectrum computation incorporating multiple causal earthquakes and ground-motion prediction models. Bulletin of the Seismological Society of America,103(2A), 1103–1116. https://doi.org/10.1785/0120110293.
Lin, T., Haselton, C. B., & Baker, J. W. (2013b). Conditional spectrum-based ground motion selection. Part I: Hazard consistency for risk-based assessments: Conditional spectrum-based ground motion selection-I. Earthquake Engineering & Structural Dynamics,42(12), 1847–1865. https://doi.org/10.1002/eqe.2301.
Lysmer, J., Ostadan, F., & Chin, C. C. (1999). SASSI 2000 theoretical manual—A system of analysis of soil-structure interaction. Berkeley: University of California.
Mahrenholtz, P., Eligehausen, R., Hutchinson, T. C., & Hoehler, M. S. (2016). Behavior of post-installed anchors tested by stepwise increasing cyclic load protocols. ACI Structural Journal. https://doi.org/10.14359/51689023.
Mai, C., Konakli, K., & Sudret, B. (2017). Seismic fragility curves for structures using non-parametric representations. Frontiers of Structural and Civil Engineering,11(2), 169–186. https://doi.org/10.1007/s11709-017-0385-y.
MATLAB. (2015). Version 8.6 R2015b, MathWorks. https://www.mathworks.com. Accessed 11 June 2019.
Michel, C., Crowley, H., Hannewald, P., Lestuzzi, P., & Fäh, D. (2018). Deriving fragility functions from bilinearized capacity curves for earthquake scenario modelling using the conditional spectrum. Bulletin of Earthquake Engineering,16(10), 4639–4660. https://doi.org/10.1007/s10518-018-0371-3.
Nielson, B. G., & DesRoches, R. (2007). Analytical seismic fragility curves for typical bridges in the central and southeastern United States. Earthquake Spectra,23(3), 615–633. https://doi.org/10.1193/1.2756815.
Obando, J. C., & Lopez-Garcia, D. (2018). Inelastic displacement ratios for nonstructural components subjected to floor accelerations. Journal of Earthquake Engineering,22(4), 569–594. https://doi.org/10.1080/13632469.2016.1244131.
Okada, T., Takanashi, K., Seki, M., & Taniguchi, H. (1980). Nonlinear earthquake response of equipment system anchored on R/C building floor. Bulletin of Earthquake Resistant Structure Research Center,13, 63–85.
Pehlivan, M., Rathje, E. M., & Gilbert, R. B. (2016). Factors influencing soil surface seismic hazard curves. Soil Dynamics and Earthquake Engineering,83, 180–190. https://doi.org/10.1016/j.soildyn.2016.01.009.
Pisharady, A. S., & Basu, P. C. (2010). Methods to derive seismic fragility of NPP components: A summary. Nuclear Engineering and Design,240(11), 3878–3887. https://doi.org/10.1016/j.nucengdes.2010.08.002.
Renault, P. L. A., & Abrahamson, N. A. (2014). Probabilistic seismic hazard analysis for Swiss nuclear power plant sites—PEGASOS refinement project (No. Final Report, 2016:6). Swissnuclear.
Rezaeian, S., & Der Kiureghian, A. (2010). Simulation of synthetic ground motions for specified earthquake and site characteristics. Earthquake Engineering & Structural Dynamics. https://doi.org/10.1002/eqe.997.
Silva, V., Crowley, H., & Bazzurro, P. (2016). Exploring risk-targeted hazard maps for Europe. Earthquake Spectra,32(2), 1165–1186. https://doi.org/10.1193/112514EQS198M.
Tarbali, K., & Bradley, B. A. (2016). The effect of causal parameter bounds in PSHA-based ground motion selection: The effect of causal parameter bounds in ground motion selection. Earthquake Engineering and Structural Dynamics,45(9), 1515–1535. https://doi.org/10.1002/eqe.2721.
United States Geological Survey (USGS). (2017). 2008 PSHA interactive deaggregation. http://geohazards.usgs.gov/deaggint/2008/. Accessed 17 Feb 2017.
Vamvatsikos, D., & Cornell, C. A. (2002). Incremental dynamic analysis. Earthquake Engineering & Structural Dynamics,31(3), 491–514. https://doi.org/10.1002/eqe.141.
Wen, Y. K., & Wu, C. L. (2001). Uniform hazard ground motions for mid-America cities. Earthquake Spectra,17(2), 359–384. https://doi.org/10.1193/1.1586179.
Yamamoto, Y., & Baker, J. W. (2013). Stochastic model for earthquake ground motion using wavelet packets. Bulletin of the Seismological Society of America,103(6), 3044–3056. https://doi.org/10.1785/0120120312.
Zentner, I. (2014). A procedure for simulating synthetic accelerograms compatible with correlated and conditional probabilistic response spectra. Soil Dynamics and Earthquake Engineering,63, 226–233. https://doi.org/10.1016/j.soildyn.2014.03.012.
Acknowledgements
The authors thank Rainer Zinn (Stangenberg und Partner Ingenieur GmbH) for kindly providing the details of the building model used in this study. This work was partially funded by Euratom’s FP7 through the research program NUGENIA + and its pilot project LOSSVAR (Grant agreement no 604965), and by the research project SINAPS@ (ANR-11-RSNR-0022), which is funded by the French National Research Agency in the context of its program “Investments for the Future”. The authors also thank the Guest Editor Dr. Philippe L.A. Renault and the two reviewers for helping to improve the quality of this paper.
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Trevlopoulos, K., Zentner, I. Seismic Fragility Curve Assessment Based on Synthetic Ground Motions with Conditional Spectra. Pure Appl. Geophys. 177, 2375–2390 (2020). https://doi.org/10.1007/s00024-019-02245-w
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DOI: https://doi.org/10.1007/s00024-019-02245-w