Abstract
This paper puts forth a wavelet-based methodology for generating endurance time (ET) excitations. Conventional simulating practice expresses signals by acceleration values which are then computed via unconstrained nonlinear optimization. Dynamic characteristics of signals, including frequency content, are not represented directly in this type of variable definition. In this study, a new algorithm is developed to generate ET excitations in discrete wavelet transform (DWT) space. In this algorithm, signals are represented by transform coefficients. In addition, objective functions are modified in order to obtain transform coefficients and return the objective function values. The proposed method makes the filtering of the optimization variables possible so that insignificant variables can be eliminated. New excitations are generated in filtered DWT space. Different generating scenarios are used, and the results are then compared. Results show improvement in the generated excitations. It is also observed that a filtered DWT space brings about higher match with target acceleration spectra. Further, significance of generating more matched ET excitations in dynamic response assessment is examined through analyzing a multidegree of freedom structure.
Similar content being viewed by others
References
Amiri GG, Bagheri A (2008) Application of wavelet multiresolution analysis and artificial intelligence for generation of artificial earthquake accelerograms. Struct Eng Mech 28(2):153–166
Amiri GG, Ashtari P, Rahami H (2006) New development of artificial record generation by wavelet theory. Struct Eng Mech 22(2):185–195
Amiri GG, Bagheri A, Razaghi SA (2009) Generation of multiple earthquake accelerograms compatible with spectrum via the wavelet packet transform and stochastic neural networks. J Earthq Eng 13(7):899–915. https://doi.org/10.1080/13632460802687728
Amiri GG, Abdolahi RA, Aghajari S, Khanmohamadi HN (2012) Generation of near-field artificial ground motions compatible with median-predicted spectra using PSO-based neural network and wavelet analysis. Comput Aided Civ Infrastruct 27(9):711–730. https://doi.org/10.1111/j.1467-8667.2012.00783.x
Asadi A, Fadavi M, Bagheri A, Amiri GG (2011) Application of neural networks and an adapted wavelet packet for generating artificial ground motion. Struct Eng Mech 37(6):575–592
Basim MC, Estekanchi HE (2015) Application of endurance time method in performance-based optimum design of structures. Struct Saf 56:52–67. https://doi.org/10.1016/j.strusafe.2015.05.005
Basu B, Gupta VK (2000) Stochastic seismic response of single-degree-of-freedom systems through wavelets. Eng Struct 22:1714–1722
Daubechies I (1992) Ten lectures on wavelets. CBMS-NSF conference series in applied mathematics, vol 61. SIAM, Montpelier, Vermont
Estekanchi HE, Vafai A, Sadeghazar M (2004) Endurance time method for seismic analysis and design of structures. Sci Iran 11(4):361–370
Estekanchi HE, Valamanesh V, Vafai A (2007) Application of endurance time method in linear seismic analysis. Eng Struct 29(10):2551–2562. https://doi.org/10.1016/j.engstruct.2007.01.009
Estekanchi HE, Harati M, Mashayekhi M (2018) An investigation on the interaction of moment-resisting frames and shear walls in RC dual systems using endurance time method. Struct Des Tall Spec Build 27(12):1–16. https://doi.org/10.1002/tal.1489
FEMA P-695 (2009) Quantification of building seismic performance factors. FEMA P-695, Washington, DC
FEMA-273 (1997) NEHRP guidelines for seismic rehabilitation of buildings, report FEMA-273. Prepared by the SAC Joint Venture for the Federal Emergency Management Agency, Washington, DC
FEMA-356 (2000) Prestandard and commentary for the seismic rehabilitation of buildings. Federal Emergency and Managment Agency, Washington, DC
Hancock J, Watson-Lamprey J, Abrahamson NA, Bommer JJ, Markatis A, Mccoy F, Mendis R (2006) An improved method of matching response spectra of recorded earthquake ground motion using wavelets. J Earthq Eng 10:67–89. https://doi.org/10.1080/13632460609350629
Hariri-Ardebili MA, Sattar S, Estekanchi HE (2014) Performance-based seismic assessment of steel frames using endurance time analysis. Eng Struct 69:216–234. https://doi.org/10.1016/j.engstruct.2014.03.019
Iyama J (2005) Estimate of input energy for elasto-plastic SDOF systems during earthquakes based on discrete wavelet coefficients. Earthq Eng Struct D 34(15):1799–1815. https://doi.org/10.1002/eqe.511
Iyama J, Kuwamura H (1999) Application of wavelets to analysis and simulation of earthquake motions. Earthq Eng Struct D 28:255–272
Kaveh A, Mahdavi VR (2012) Generation of endurance time acceleration functions using the wavelet transform. Int J Optim Civ Eng 2(2):203–219
Kaveh A, Kalateh M, Estekanchi HE (2013) Production of enduarnce time excitations functions: the CAV evolution strategy approach. Iran J Sci Technol Trans Civ Eng 37:383–394
Mallat SG (1989) Multi resolution approximation and wavelet orthogonal bases of L2(R). Trans Am Math Soc 315:69–87
Mashayekhi M, Estekanchi HE (2013a) Investigation of strong-motion duration consistency in endurance time excitation functions. Sci Iran 20(4):1085–1093
Mashayekhi M, Estekanchi HE (2013b) Investigation of non- linear cycles’ properties in structures subjected to endurance time excitation functions. Int J Optim Civ Eng 3(2):239–257
Mirzaee A, Estekanchi HE (2015) Performance-based seismic retrofitting of steel frames by the endurance time method. Earthq Spectra 31(1):383–402. https://doi.org/10.1193/081312EQS262M
Mirzaee A, Estekanchi HE, Vafai A (2012) Improved methodology for endurance time analysis: from time to seismic hazard return period. Sci Iran 19(5):1180–1187. https://doi.org/10.1016/j.scient.2012.06.023
Montejo LA, Kowalsky MJ (2008) Estimation of frequency-dependent strong motion duration via wavelets and its influence on nonlinear seismic response. Comput Aided Civil Infrastruct 23:253–264
Moré JJ, Sorensen DC (1983) Computing a Trust Region Step. SIAM J Sci Stat Comput 3:553–572. https://doi.org/10.1137/0904038
Mukherjee S, Gupta VK (2002a) Wavelet-based characterization of design ground motions. Earthq Eng Struct D 31(5):1173–1190. https://doi.org/10.1002/eqe.155
Mukherjee S, Gupta VK (2002b) Wavelet-based generation of spectrum-compatible time-histories. Soil Dyn Earhq Eng 22:799–804
Newland D (1993) Random vibrations, spectral and wavelet analysis, 3rd edn. Longman Scientific and Technical, New York
Nozari A, Estekanchi HE (2011) Optimization of Endurance Time acceleration functions for seismic assessment of structures. Int J Optim Civ Eng 2:257–277
Riahi HT, Estekanchi HE (2010) Seismic assessment of steel frames with the endurance time method. J Construct Steel Res 66(6):780–792. https://doi.org/10.1016/j.jcsr.2009.12.001
Riahi HT, Estekanchi HE, Vafai A (2009) Application of endurance time method in nonlinear seismic analysis of SDOF systems. J Appl Sci 9(10):1817–1832
Suárez LE, Montejo LA (2005) Generation of artificial earthquakes via the wavelet transform. Int J Solid Struct 42:5905–5919. https://doi.org/10.1016/j.ijsolstr.2005.03.025
Vamvatsikos D, Cornell CA (2002) Incremental dynamic analysis. Earthq Eng Struct D 31(3):491–514. https://doi.org/10.1002/eqe.141
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Mashayekhi, M., Estekanchi, H.E. & Vafai, H. Simulation of Endurance Time Excitations via Wavelet Transform. Iran J Sci Technol Trans Civ Eng 43, 429–443 (2019). https://doi.org/10.1007/s40996-018-0208-y
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s40996-018-0208-y