Measurement-based support for post-earthquake assessment of buildings

References

• Ambraseys, N., Smit, P., Douglas, J., Margaris, B., Sigbjrnsson, R., Olafsson, S., … Costa, G. (2004). Internet site for European strong-motion data. Bollettino di Geofisica Teorica ed Applicata, 45(3), 113–129.
   Google Scholar
• Astorga, A., Guéguen, P., & Kashima, T. (2018). Nonlinear elasticity observed in buildings during a long sequence of earthquakes. Bulletin of the Seismological Society of America, 108(3A), 1185–1198. doi:10.1785/0120170289
   Web of Science ®Google Scholar
• Baggio, C., Bernardini, A., Colozza, R., Corazza, L., Della Bella, M., Di Pasquale, G., … Zuccaro, G. (2007). Field manual for post-earthquake damage and safety assessment and short term countermeasures (AeDES). European Commission, Joint Research Centre, Institute for the Protection and Security of the Citizen, EUR, 22868.
   Google Scholar
• Balafas, K., & Kiremidjian, A. S. (2015). Development and validation of a novel earthquake damage estimation scheme based on the continuous wavelet transform of input and output acceleration measurements. Earthquake Engineering & Structural Dynamics, 44(4), 501–522. doi:10.1002/eqe.2529
   Web of Science ®Google Scholar
• Beck, J. L., & Yuen, K.-V. (2004). Model selection using response measurements: Bayesian probabilistic approach. Journal of Engineering Mechanics, 130(2), 192–203. doi:10.1061/(ASCE)0733-9399(2004)130:2(192)
   Web of Science ®Google Scholar
• Behmanesh, I., & Moaveni, B. (2015, March). Probabilistic identification of simulated damage on the Dowling Hall footbridge through Bayesian finite element model updating. Structural Control and Health Monitoring, 22(3), 463–483. doi:10.1002/stc.1684
   Web of Science ®Google Scholar
• Bensi, M., Kiureghian, A. D., & Straub, D. (2014). Framework for post-earthquake risk assessment and decision making for infrastructure systems. ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering, 1(1), 04014003. doi:10.1061/AJRUA6.0000810
   Google Scholar
• Beyer, K., Tondelli, M., Petry, S., & Peloso, S. (2015). Dynamic testing of a four-storey building with reinforced concrete and unreinforced masonry walls: prediction, test results and data set. Bulletin of Earthquake Engineering, 13(10), 3015–3064. doi:10.1007/s10518-015-9752-z
   Web of Science ®Google Scholar
• Calvi, G. M., Pinho, R., & Crowley, H. (2006). State-of-the-knowledge on the period elongation of RC buildings during strong ground shaking. PROC (CD) First European Conference on Earthquake Engineering and seismology (pp. 3–8), Geneva, Switzerland.
   Google Scholar
• Chellini, G., De Roeck, G., Nardini, L., & Salvatore, W. (2010). Damage analysis of a steelconcrete composite frame by finite element model updating. Journal of Constructional Steel Research, 66(3), 398–411. doi:10.1016/j.jcsr.2009.10.004
   Web of Science ®Google Scholar
• Clinton, J. F., Bradford, S. C., Heaton, T. H., & Favela, J. (2006). The observed wander of the natural frequencies in a structure. Bulletin of the Seismological Society of America, 96(1), 237–257. doi:10.1785/0120050052
   Web of Science ®Google Scholar
• D’Ayala, D. F., & Paganoni, S. (2010). Assessment and analysis of damage in L’Aquila historic city centre after 6th April 2009. Bulletin of Earthquake Engineering, 9(1), 81–104. doi:10.1007/s10518-010-9224-4
   Web of Science ®Google Scholar
• Dunand, F., Ait Meziane, Y., Guéguen, P., Chatelain, J.-L., Guillier, B., Ben Salem, R., … Remas, A (2004). Utilisation du bruit de fond pour l’analyse des dommages des bâtiments de boumerdes suite au séisme du 21 mai 2003. Mémoires du Service Géologique de L’Algérie, 12, 177–191.
   Google Scholar
• Elwood, K., Marder, K., Pampanin, S., Ramirez, A. C., Kral, M., Smith, P., … Stannard, M. (2016, April 1–3). Draft framework for assessing residual capacity of earthquake-damaged concrete buildings. Proceedings of the annual New Zealand Society for Earthquake Engineering (NZSEE) Conference, Christchurch, New Zealand.
   Google Scholar
• Enright, M. P., & Frangopol, D. M. (1999). Condition prediction of deteriorating concrete bridges using Bayesian updating. Journal of Structural Engineering, 125(10), 1118–1125. doi:10.1061/(ASCE)0733-9445(1999)125:10(1118)
   Web of Science ®Google Scholar
• Esteva, L., Díaz-López, O. J., Vásquez, A., & León, J. A. (2016). Structural damage accumulation and control for life cycle optimum seismic performance of buildings. Structure and Infrastructure Engineering, 12(7), 848–860. doi:10.1080/15732479.2015.1064967
   Web of Science ®Google Scholar
• Galloway, B., Hare, J., Brunsdon, D., Wood, P., Lizundia, B., & Stannard, M. (2014). Lessons from the post-earthquake evaluation of damaged buildings in Christchurch. Earthquake Spectra, 30(1), 451–474. doi:10.1193/022813EQS057M
   Web of Science ®Google Scholar
• Gentile, A., & Messina, A. (2003). On the continuous wavelet transforms applied to discrete vibrational data for detecting open cracks in damaged beams. International Journal of Solids and Structures, 40(2), 295–315. doi:10.1016/S0020-7683(02)00548-6
   Web of Science ®Google Scholar
• Ghosh, J., Padgett, J. E., & Sánchez-Silva, M. (2015). Seismic damage accumulation in highway bridges in earthquake-prone regions. Earthquake Spectra, 31(1), 115–135. doi:10.1193/120812EQS347M
   Web of Science ®Google Scholar
• Goretti, A., & Di Pasquale, G. (2002). An overview of post-earthquake damage assessment in Italy. Eeri invitational workshop. An action plan to develop earthquake damage and loss data protocols, California.
   Google Scholar
• Goretti, A., 6Hutt, C. M., & Hedelund, L. (2017). Post-earthquake safety evaluation of buildings in Portoviejo, Manabí province, following the mw7. 8 Ecuador earthquake of April 16, 2016. International Journal of Disaster Risk Reduction, 24, 271–283. doi:10.1016/j.ijdrr.2017.06.011
   Web of Science ®Google Scholar
• Goulet, J.-A., Michel, C., & Kiureghian, A. D. (2015). Data-driven post-earthquake rapid structural safety assessment. Earthquake Engineering & Structural Dynamics, 44(4), 549–562. doi:10.1002/eqe.2541
   Web of Science ®Google Scholar
• Goulet, J.-A., Michel, C., & Smith, I. F. C. (2013). Hybrid probabilities and error-domain structural identification using ambient vibration monitoring. Mechanical Systems and Signal Processing, 37(1–2), 199–212. doi:10.1016/j.ymssp.2012.05.017
   Web of Science ®Google Scholar
• Goulet, J.-A., & Smith, I. F. C. (2013). Structural identification with systematic errors and unknown uncertainty dependencies. Computers & Structures, 128, 251–258. doi:10.1016/j.compstruc.2013.07.009
   Web of Science ®Google Scholar
• Grünthal, G., Musson, R. M. V., Schwarz, J., & Stucchi, M. (2001). European Macroseismic Scale 1998, EMS-98. Cahiers du Centre Européen de Géodynamique et de Séismologie, 19.
   Google Scholar
• Huang, C. S., Hung, S. L., Wen, C. M., & Tu, T. T. (2003). A neural network approach for structural identification and diagnosis of a building from seismic response data. Earthquake Engineering & Structural Dynamics, 32(2), 187–206. doi:10.1002/eqe.219
   Web of Science ®Google Scholar
• Iervolino, I., Giorgio, M., & Chioccarelli, E. (2014). Closed-form aftershock reliability of damage-cumulating elastic-perfectly-plastic systems. Earthquake Engineering & Structural Dynamics, 43(4), 613–625. doi:10.1002/eqe.2363
   Web of Science ®Google Scholar
• 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 Laquila earthquake, 2009. Bulletin of Earthquake Engineering, 9(4), 997–1014. doi:10.1007/s10518-010-9230-6
   Web of Science ®Google Scholar
• Jalayer, F., & Ebrahimian, H. (2017). Seismic risk assessment considering cumulative damage due to aftershocks. Earthquake Engineering & Structural Dynamics, 46(3), 369–389. doi:10.1002/eqe.2792
   Web of Science ®Google Scholar
• Jeon, J.-S., DesRoches, R., Lowes, L. N., & Brilakis, I. (2015). Framework of aftershock fragility assessment–case studies: older California reinforced concrete building frames. Earthquake Engineering & Structural Dynamics, 44(15), 2617–2636. doi:10.1002/eqe.2599
   Web of Science ®Google Scholar
• Katsanos, E. I., Sextos, A. G., & Elnashai, A. S. (2014). Prediction of inelastic response periods of buildings based on intensity measures and analytical model parameters. Engineering Structures, 71, 161–177. doi:10.1016/j.engstruct.2014.04.007
   Web of Science ®Google Scholar
• Lagomarsino, S., & Giovinazzi, S. (2006). Macroseismic and mechanical models for the vulnerability and damage assessment of current buildings. Bulletin of Earthquake Engineering, 4(4), 415–443. doi:10.1007/s10518-006-9024-z
   Web of Science ®Google Scholar
• Lestuzzi, P., Belmouden, Y., & Trueb, M. (2007). Non-linear seismic behavior of structures with limited hysteretic energy dissipation capacity. Bulletin of Earthquake Engineering, 5(4), 549–569. doi:10.1007/s10518-007-9050-5
   Web of Science ®Google Scholar
• Maity, D., & Saha, A. (2004). Damage assessment in structure from changes in static parameter using neural networks. Sadhana, 29(3), 315–327. doi:10.1007/BF02703781
   Web of Science ®Google Scholar
• Marquis, F., Kim, J. J., Elwood, K. J., & Chang, S. E. (2017). Understanding post-earthquake decisions on multi-storey concrete buildings in Christchurch, New Zealand. Bulletin of Earthquake Engineering, 15(2), 731–758. doi:10.1007/s10518-015-9772-8
   Web of Science ®Google Scholar
• Marshall, J. D., Jaiswal, K., Gould, N., Turner, F., Lizundia, B., & Barnes, J. C. (2013). Post-earthquake building safety inspection: Lessons from the Canterbury, New Zealand, earthquakes. Earthquake Spectra, 29(3), 1091–1107. doi:10.1193/1.4000151
   Web of Science ®Google Scholar
• Michel, C., Zapico, B., Lestuzzi, P., Molina, F. J., & Weber, F. (2011). Quantification of fundamental frequency drop for unreinforced masonry buildings from dynamic tests. Earthquake Engineering & Structural Dynamics, 40(11), 1283–1296. doi:10.1002/eqe.1088
   Web of Science ®Google Scholar
• Mitrani-Resier, J., Wu, S., & Beck, J. L. (2016). Virtual inspector and its application to immediate pre-event and post-event earthquake loss and safety assessment of buildings. Natural Hazards, 81(3), 1861–1878. doi:10.1007/s11069-016-2159-6
   Web of Science ®Google Scholar
• Moaveni, B., Conte, J. P., & Hemez, F. M. (2009). Uncertainty and sensitivity analysis of damage identification results obtained using finite element model updating. Computer-Aided Civil and Infrastructure Engineering, 24(5), 320–334. doi:10.1111/j.1467-8667.2008.00589.x
   Web of Science ®Google Scholar
• Moaveni, B., He, X., Conte, J. P., & Restrepo, J. I. (2010). Damage identification study of a seven-story full-scale building slice tested on the UCSD-NEES shake table. Structural Safety, 32(5), 347–356. doi:10.1016/j.strusafe.2010.03.006
   Web of Science ®Google Scholar
• Mucciarelli, M., Masi, A., Gallipoli, M. R., Harabaglia, P., Vona, M., Ponzo, F., … Dolce, M. (2004). Analysis of RC building dynamic response and soil-building resonance based on data recorded during a damaging earthquake (Molise, Italy, 2002). Bulletin of the Seismological Society of America, 94(5), 1943–1953. doi:10.1785/012003186
   Web of Science ®Google Scholar
• Özer, E., & Soyöz, S. (2013, September). Vibration-based damage detection and seismic performance assessment of bridges. Earthquake Spectra, 31(1), 137–157. doi:10.1193/080612EQS255M
   Web of Science ®Google Scholar
• Pai, S. G. S., Nussbaumer, A., & Smith, I. F. C. (2018). Comparing structural identification methodologies for fatigue life prediction of a highway bridge. Frontiers in Built Environment, 3, 73.
   Google Scholar
• Paparo, A., & Beyer, K. (2013). Seismic behaviour of mixed RC-URM wall structures: Comparison between numerical results and experimental evidence. Proceedings of the Vienna Congress on Recent Advances in Earthquake Engineering and Structural Dynamics, Vienna.
   Google Scholar
• Paparo, A., & Beyer, K. (2014). Quasi-static cyclic tests of two mixed reinforced concrete–unreinforced masonry wall structures. Engineering Structures, 71, 201–211. doi:10.1016/j.engstruct.2014.04.002
   Web of Science ®Google Scholar
• Pasquier, R., & Smith, I. F. C. (2015a). Robust system identification and model predictions in the presence of systematic uncertainty. Advanced Engineering Informatics, 29(4), 1096–1109. doi:10.1016/j.aei.2015.07.007
   Web of Science ®Google Scholar
• Pasquier, R., & Smith, I. F. C. (2015b). Sources and forms of modelling uncertainties for structural identification. 7th International Conference on Structural Health Monitoring of Intelligent Infrastructure (SHMII).
   Google Scholar
• Pasquier, R., & Smith, I. F. C. (2016). Iterative structural identification framework for evaluation of existing structures. Engineering Structures, 106, 179–194. doi:10.1016/j.engstruct.2015.09.039
   Web of Science ®Google Scholar
• Polese, M., Di Ludovico, M., Marcolini, M., Prota, A., & Manfredi, G. (2015). Assessing reparability: Simple tools for estimation of costs and performance loss of earthquake damaged reinforced concrete buildings. Earthquake Engineering & Structural Dynamics, 44(10), 1539–1557. doi:10.1002/eqe.2534
   Web of Science ®Google Scholar
• Popper, K. R. (1959). The logic of scientific discovery. London: Hutchinson.
   Google Scholar
• 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. doi:10.1002/eqe.2478
   Web of Science ®Google Scholar
• Raphael, B., & Smith, I. F. C. (1998). Finding the right model for bridge diagnosis. In Artificial intelligence in structural engineering (pp. 308–319). Springer: Heidelberg.
   Google Scholar
• Reuland, Y., Lestuzzi, P., & Smith, I. F. C. (2017). Data-interpretation methodologies for non-linear earthquake response predictions of damaged structures. Frontiers in Built Environment, 3, 43.
   Google Scholar
• Robert-Nicoud, Y., Raphael, B., & Smith, I. F. C. (2005). System identification through model composition and stochastic search. Journal of Computing in Civil Engineering, 19(3), 239–247. doi:10.1061/(ASCE)0887-3801(2005)19:3(239)
   Web of Science ®Google Scholar
• Shiradhonkar, S., & Shrikhande, M. (2011). Seismic damage detection in a building frame via finite element model updating. Computers & Structures, 89(23–24), 2425–2438.
   Web of Science ®Google Scholar
• Smith, I. F. C. (2016). Studies of sensor-data interpretation for asset management of the built environment. Frontiers in Built Environment, 2, 8.
   Google Scholar
• Takeda, T., Sozen, M. A., & Nielsen, N. N. (1970). Reinforced concrete response to simulated earthquakes. Journal of the Structural Division, 96(12), 2557–2573.
   Google Scholar
• Trevlopoulos, K., & Guéguen, P. (2016). Period elongation-based framework for operative assessment of the variation of seismic vulnerability of reinforced concrete buildings during aftershock sequences. Soil Dynamics and Earthquake Engineering, 84, 224–237. doi:10.1016/j.soildyn.2016.02.009
   Web of Science ®Google Scholar
• Vidal, F., Navarro, M., Aranda, C., & Enomoto, T. (2013). Changes in dynamic characteristics of Lorca RC buildings from pre-and post-earthquake ambient vibration data. Bulletin of Earthquake Engineering, 1–16.
   Web of Science ®Google Scholar
• Vona, M., Cascini, G., Mastroberti, M., Murgante, B., & Nolè, G. (2017). Characterization of URM buildings and evaluation of damages in a historical center for the seismic risk mitigation and emergency management. International Journal of Disaster Risk Reduction, 24, 251–263. doi:10.1016/j.ijdrr.2017.05.008
   Web of Science ®Google Scholar
• Šidák, Z. (1967). Rectangular confidence regions for the means of multivariate normal distributions. Journal of the American Statistical Association, 62(318), 626–633. doi:10.1080/01621459.1967.10482935
   Web of Science ®Google Scholar
• Yazgan, U., & Dazio, A. (2012). Post-earthquake damage assessment using residual displacements. Earthquake Engineering & Structural Dynamics, 41(8), 1257–1276. doi:10.1002/eqe.1184
   Web of Science ®Google Scholar
• Yeo, G. L., & Cornell, C. A. (2009). Post-quake decision analysis using dynamic programming. Earthquake Engineering & Structural Dynamics, 38(1), 79–93. doi:10.1002/eqe.842
   Web of Science ®Google Scholar
• Zapico, J. L., & Gonzalez, M. P. (2006). Numerical simulation of a method for seismic damage identification in buildings. Engineering Structures, 28(2), 255–263. doi:10.1016/j.engstruct.2005.08.005
   Web of Science ®Google Scholar