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Evaluating the difference in the effect of distance on the seismic demand estimated using nonlinear dynamic analysis and Bayesian statistics in near and far fields | ||
| International Journal of Nonlinear Analysis and Applications | ||
| دوره 12، Special Issue، اسفند 2021، صفحه 173-187 اصل مقاله (1.21 M) | ||
| نوع مقاله: Research Paper | ||
| شناسه دیجیتال (DOI): 10.22075/ijnaa.2021.5019 | ||
| نویسندگان | ||
| Saman Asadi1؛ Mehdi Mahdavi Adeli* 2 | ||
| 1Shakhes Pajouh Research Institute, Tehran, Iran | ||
| 2Assistant Professor, Department of Civil Engineering, Shoushtar Branch, Islamic Azad University, Shoushtar, Iran | ||
| تاریخ دریافت: 30 خرداد 1399، تاریخ بازنگری: 13 آبان 1399، تاریخ پذیرش: 26 دی 1399 | ||
| چکیده | ||
| Seismic demand estimation of structures (which is considered as one of the main components of performance-based designing) is along with various uncertainties, the most important of which is fault-to-site distance. In fact, with the variation in fault-to-site distance of an accelerogram, its effect on seismic demand estimation would differ. However, it seems that this distance impact on the seismic demand will be different in far and near fields concerning the distinct nature of near field. The main aim of this study is to verify this issue and determine the impact of fault-to-site distance on seismic demand of steel moment resisting frames in near and far fields using nonlinear dynamic analysis and Bayesian statistics. Nonlinear dynamic analysis is used to cover the actual nonlinear behavior of the structure in near-collapse performance level and the Bayesian approach to cover all uncertainties. Concerning the research objectives, two generic steel moment resisting frames of 3-storey with rigid behavior and 15-storey with flexible behavior have been selected and nonlinearly modeled in Open Sees. At the next stage, these frames were analyzed through incremental nonlinear dynamic analysis under five groups of 40 accelerograms that were similar in terms of all features except for fault-to-site distance and the results were used for determining their seismic demand. In so far as the only variable in this analysis is fault-to-site distance, the difference in the results could be attributed to this variable. According to the results, from statistical approach, there is some difference between the impact of distance variation on seismic demand in near and far fields which is subject to some variables such as the behavior of the frame and its performance level. | ||
| کلیدواژه‌ها | ||
| Nonlinear Dynamic Analysis؛ Bayesian Statistics؛ Near and Far Fields Earthquake؛ Seismic Demand؛ Fault-to-Site Distance | ||
| مراجع | ||
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[1] M. Ansari, M. Ansari and A. Safiey, Evaluation of seismic performance of mid-rise reinforced concrete frames subjected to far-field and near-field ground motions, 15(8) (2018) 453–462.[2] D. Bindi, M. Picozzi, D. Spallarossa, F. Cotton and S. R. Kotha, Impact of magnitude selection on aleatory variability associated with ground-motion prediction equations: Part II—analysis of the between-event distribution in central Italy, Bull. Seis. Soc. Amer. 109(1) (2019) 251—262. doi.org/10.1785/0120180239. [3] A. Brezger and S. Lang, Generalized structured additive regression based on Bayesian P-Splines, Comput. Stat. Data Anal. 50 (2006) 967–991. [4] A. Brezger and S. Lang, Simultaneous Probability statements for Bayesian P-Splines, Stat. Mod. 8 (2008) 141–168. [5] A. Chaudhuri and S. Chakraborty, Reliability of linear structures with parameter uncertainty under non-stationary earthquake, Struc. Saf. 28(3) (2006) 231–246. [6] B. R. Ellingwood, Earthquake risk assessment of building structures, Rel. Engin. Syst. Saf. 74(3) (2001) 251–262, doi.org/10.1016/S0951-8320(01)00105-3. [7] S. Ghosh, S. Ghosh and S. Chakraborty, Seismic fragility analysis in the probabilistic performancebased earthquake engineering framework: an overview, Int. J. Adv. Engin. Sci. Appl. Math. (2017). https://doi.org/10.1007/s12572-017-0200-y [8] J. Hou, Y. An, S. Wang, Zh. Wang, L. Jankowski and J. Ou, Structural damage localization and quantification based on additional virtual masses and Bayesian theory, J. Engin. Mech. 144(10) (2018). [9] F. Jalayer, R. De Risi and G. Manfredi, Bayesian cloud analysis: efficient structural fragility assessment using linear regression, Bull Earthquake Engin. 13(4) (2015) 1183-–1203. [10] A. Kaveh, R. Mahdipou Moghanni and S.M. Javadi, Ground notion record selection using multi-objective optimization algorithms: a comparative study, Periodica Polytechnica Civil Engin. 63(3) (2019) 812–822. [11] Sh. Kwag and A. Gupta, Probabilistic risk assessment framework for structural systems under multiple hazards using Bayesian statistics, Nuclear Engin. Des. 315 (2017) 20–34. [12] Sh. Kwag, J. Oh and J. M. Lee, Application of Bayesian statistics to seismic probabilistic safety assessment for research reactor, Nuclear Engin. Des. 328 (2018) 166–181. [13] X. X. Liu, ZY. Wu and F. Liang, Multidimensional performance limit state for probabilistic seismic demand analysis, Bull Earthquake Engin. 14 (2016) 3389—3408. [14] T. T. Liu, D. G. Lu and X. H. Yu, Development of a compound intensity measure using partial least-squares regression and its statistical evaluation based on probabilistic seismic demand analysis, Soil Dyn. Earthquake Engin. 125 (2019) 105725. [15] L. Macedo and J.M. Castro, SelEQ: An advanced ground motion record selection and scaling framework, Adv. Engin. Soft. 114 (2017) 32–47. [16] M. Mahdavi Adeli, A. Deylami, M. Banazadeh and M. M. Alinia, A Bayesian approach to construction of probabilistic seismic demand models for steel moment-resisting frames, Sci. Iran. 18(4) (2011) 885—894. [17] M. Mahdavi Adeli, M. Banazadeh, A. Deylami and M.M. Alinia, Introducing a new Spectral intensity measure parameter to estimate the seismic demand of steel moment-resisting frames using Bayesian statistics, Adv. Struc. Engin. 15(2) (2016) 231–247. [18] M. Mahdavi Adeli, M. Banazadeh and A. Deylami, Bayesian approach for determination of drift hazard curves for generic steel moment-resisting frames in territory of Tehran, Int. J. Civil Engin. 9(3) (2011) 145–154. [19] M. Maleki, R. Ahmady Jazany, M. S. Ghobadi, Probabilistic Seismic Assessment of SMFs with Drilled Flange Connections Subjected to Near-Field Ground Motions. International Journal of Steel Structures, 19 (2019) 224–240. https://doi.org/10.1007/s13296-018-0112-0. [20] R. A. Medina and H. Krawinkler, Evaluation of drift demands for the seismic performance assessment of frames, J. Struc. Engin. 131(7) (2005) 1003–1013. [21] M. Onvani and A. Yahyaabadi, Probabilistic seismic demand analysis of steel moment frames by utilizing Bayesian statistics, European J. Envir. Civil Engin. (2018), DOI: 10.1080/19648189.2018.1538905. [22] G. J. O’Reilly and G. M. Calvi, Conceptual seismic design in performance-based earthquake engineering, Earthquake Engin. Struc. Dyn. 48(4) (20187) 389–411. [23] Sh. Shahbazi, I. Mansouri, J. W. Hu, N. Sam Daliri and A. Karami, Seismic response of steel SMFs subjected to vertical components of far and near-field earthquakes with forward directivity effects, Adv. Civil Engin. (2019). doi.org/10.1155/2019/2647387. [24] L. Tian, H. Pan and R. Ma, Probabilistic seismic demand model and fragility analysis of transmission tower subjected to near-field ground motions, J. Const. Steel Res. 156 (2019) 266–275. [25] P. Tothong and N. Luco, Probabilistic seismic demand analysis using advanced ground motion intensity measures, Earthquake Engin. Struc. Dyn. 36(13) (2007) 1837—1860. [26] D. Vamvatsikos and M. Fragiadakis, Incremental dynamic analysis for estimating seismic performance sensitivity and uncertainty, Earthquake Engin. Struct. Dyn. 39(2) (2010) 141—163. | ||
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