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Development of frequency-content based framework to extract fragility curves using real ground motion records

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Abstract

A new non-parametric procedure is presented for extracting seismic fragility curves by considering frequency content of real ground motion records. The implemented non-parametric method is based on parametric methods averaging and clustering the input data based on an intensity measure (IM) using K-means clustering method. As an advantage, it can considerably decrease the number of analyses via an optimization process and using Monte Carlo procedure. The proposed method's accuracy is evaluated for real ground motion records. Results show that although the random selection of records among different clusters can be effective for synthetic records, but it’s not suitable for selecting the real ones and can lead to large errors in estimations. Therefore, a classification procedure based on frequency content of the records is used in this study to select an appropriate set of real ground motion records for providing the required IM observations in the method. Then, a set of 472 real ground motion records corresponding to 60 earthquakes is chosen as input data for extracting the fragility curves of the case study structure for evaluating the accuracy and applicability of the non-parametric method. Mean period (\(T_{m}\)) of the ground motions is considered as a suitable frequency content measure to classify the real ground motion records while this classification can lead to better and more accurate results rather than the Monte Carlo procedure. According to the results, with using the classification procedure, the optimized non-parametric method may require less than 70 nonlinear analyses to extract the fragility curves.

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References

  • Altieri D, Patelli E (2020) An efficient approach for computing analytical non-parametric fragility curves. Struct Saf 85:101956

    Article  Google Scholar 

  • Berge-Thierry C, Svay A, Laurendeau A, Chartier T, Perron V, Guyonnet-Benaize C et al (2017) Toward an integrated seismic risk assessment for nuclear safety improving current French methodologies through the SINAPS@ research project. Nucl Eng Des 323:185–201

    Article  Google Scholar 

  • Bommer JJ, Acevedo AB (2004) The use of real earthquake accelerograms as input to dynamic analysis. J Earthq Eng 8(Special issue 1):43–92

    Article  Google Scholar 

  • Cheng Y, Dong YR, Bai GL, Wang YY (2021) IDA-based seismic fragility of high-rise frame-core tube structure subjected to multi-dimensional long-period ground motions. J Build Eng 43:102917

    Article  Google Scholar 

  • Davies DL, Bouldin DW (1979) Cluster separation measure. IEEE Trans Pattern Anal Mach Intell 1(2):95–104

    Google Scholar 

  • Gidaris I, Taflanidis AA, Mavroeidis GP (2015) Kriging metamodeling in seismic risk assessment based on stochastic ground motion models: seismic risk assessment through kriging metamodeling. Earthq Eng Struct Dyn 44:2377–2399

    Article  Google Scholar 

  • Jain AK, Murty MN, Flynn PJ (1999) Data clustering: a review. ACM Comput Surv 31:264–323

    Article  Google Scholar 

  • Jalayer F, Cornell C (2009) Alternative non-linear demand estimation methods for probability-based seismic assessments. Earthq Eng Struct Dyn 38:951–972

    Article  Google Scholar 

  • Kalantari A, Roohbakhsh H (2020) Expected seismic fragility of code-conforming RC moment resisting frames under twin seismic events. J Build Eng 28:101098

    Article  Google Scholar 

  • Khaloo A, Nozhati S, Masoomi H, Faghihmaleki H (2016) Influence of earthquake record truncation on fragility curves of RC frames with different damage indices. J Build Eng 7:23–30

    Article  Google Scholar 

  • Kumar M, Castro JM, Stafford PJ, Elghazouli AY (2011) Influence of the mean period of ground motion on the inelastic dynamic response of single and multi-degree of freedom systems. Earthq Eng Struct Dyn 40:237–256

    Article  Google Scholar 

  • Lallemant D, Kiremidjian A, Burton H (2015) Statistical procedures for developing earthquake damage fragility curves: statistical procedures for damage fragility curves. Earthq Eng Struct Dyn 44(9):1373–1389

    Article  Google Scholar 

  • Mai C, Konakli K, Sudret B (2017) Seismic fragility curves for structures using non-parametric representations. Front Struct Civ Eng 11:169–186

    Article  Google Scholar 

  • MATLAB (1997) The Language of Technical Computing, Version 5.0. The Math works Inc., Natick

  • Noh HY, Lignos DG, Nair KK, Kiremidjian A (2012) Development of fragility functions as a damage classification/prediction method for steel moment-resisting frames using a wavelet-based damage sensitive feature. Earthq Eng Struct Dyn 41:681–696

    Article  Google Scholar 

  • Noh HY, Lallemant D, Kiremidjian A (2014) Development of empirical and analytical fragility functions using kernel smoothing methods. Earthq Eng Struct Dyn 44:1163–1180

    Article  Google Scholar 

  • Parolai S, Haas M, Pittore M, Fleming K (2018) Bridging the gap between seismology and engineering: towards real-time damage assessment. In: Pitilakis K (ed) Recent advances in earthquake engineering in Europe, vol 46. Springer, Cham, pp 253–261

    Chapter  Google Scholar 

  • Patil A, Jung S, Kwon O-S (2016) Structural performance of a parked wind turbine towersubjected to strong ground motions. Eng Struct 120:92–102

    Article  Google Scholar 

  • PEER (2013) Pacific earthquake engineering research center: ground motion database. http://peer.berkleley.edu/peerground motion database

  • Porter K, Kennedy R, Bachman R (2007) Creating fragility functions for performance based earthquake engineering. Earthq Spectra 23:471–489

    Article  Google Scholar 

  • Quilligan A, O’Connor A, Pakrashi V (2012) Fragility analysis of steel and concrete wind turbine towers. Eng Struct 36:270–282

    Article  Google Scholar 

  • Rathje EM, Abrahamson NA, Bray JD (1998) Simplified frequency content estimates of earthquake ground motions. J Geotech Geoenviron Eng 124(2):150–159

    Article  Google Scholar 

  • Rathje EM, Faraj F, Russell S, Bray JD (2004) Empirical relationships for frequency content parameters of earthquake ground motions. Earthq Spectra 20(1):119–144

    Article  Google Scholar 

  • Rossetto T, Ioannou I, Grant DN, Maqsood T (2014) GEM guidelines for empirical vulnerability assessment. In: Global earthquake model report, pp 1–108. vulnerability-assessment. Accessed June 2014

  • Saha SK, Matsagar V, Chakraborty S (2016) Uncertainty quantification and seismic fragility of base-isolated liquid storage tanks using response surface models. Probab Eng Mech 43:20–35

    Article  Google Scholar 

  • Shinozuka M, Feng MQ, Lee J, Naganuma T (2000) Statistical analysis of fragility curves. J Eng Mech 126:1224–1231

    Google Scholar 

  • Silva V, Crowley H, Bazzurro P (2016) Exploring risk-targeted hazard maps for Europe. Earthq Spectra 32:1165–1186

    Article  Google Scholar 

  • Trevlopoulos K, Zentner I (2019) Seismic fragility curve assessment based on synthetic ground motions with conditional spectra. Pure Appl Geophys 177:2375–2390

    Article  Google Scholar 

  • Trevlopoulos K, Feau C, Zentner I (2019) Parametric models averaging for optimized non-parametric fragility curve estimation based on intensity measure data clustering. Struct Saf 81:101865

    Article  Google Scholar 

  • Tsiavos A, Amrein P, Bender N, Stojadinovic B (2021) Compliance-based estimation of seismic collapse risk of an existing reinforced concrete frame building. Bull Earthq Eng 19:6027–6048

    Article  Google Scholar 

  • Tsionis G, Mignan D, Pinto A, Giardini D (2016) European Commission, Joint Research Centre. Harmonized approach to stress tests for critical infrastructures against natural hazards. Publications Office, Luxembourg

  • Yaghmaei-Sabegh S (2015) New models for frequency content prediction of earthquake records based on Iranian ground motion data. J Seismol 19(4):831–848

    Article  Google Scholar 

  • Yaghmaei-Sabegh S (2017) A novel approach for classification of earthquake ground-motion records. J Seismol 21(4):885–907

    Article  Google Scholar 

  • Yaghmaei-Sabegh S (2020) Frequency-content parameters of the ground motions from the 2017 Mw 7.3 Ezgeleh earthquake in Iran. Nat Hazards 101(6):349–365

    Article  Google Scholar 

  • Yaghmaei-Sabegh S, Pavel F, Shahvar M, Talha Qadri SM (2022) Empirical frequency content models based on intermediate-depth earthquake ground-motions. Soil Dyn Earthq Eng 155:107173

    Article  Google Scholar 

  • Zentner I (2017) A general framework for the estimation of analytical fragility functions based on multivariate probability distributions. Struct Saf 64:54–61

    Article  Google Scholar 

  • Zhang J, Huo Y (2009) Evaluating effectiveness and optimum design of isolation devices for highway bridges using the fragility function method. Eng Struct 31:1648–1660

    Article  Google Scholar 

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Correspondence to Saman Yaghmaei-Sabegh.

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A new framework has been proposed to extract fragility curve considering frequency content of ground motion records.

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Yaghmaei-Sabegh, S., Neekmanesh, S. Development of frequency-content based framework to extract fragility curves using real ground motion records. Bull Earthquake Eng 20, 8011–8030 (2022). https://doi.org/10.1007/s10518-022-01510-z

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