Seismic zoning of Ardabil city using deterministic hazard analysis and fuzzy system

Document Type : Original Research

Authors
S. Khodadadi Jeyd
S. Pourzeynali
Department of Civil Engineering, Faculty of Engineering, University of Guilan
DOI: 10.22034/22.2.4
Abstract
Zoning and seismic hazard analysis is a powerful tool with useful and valuable information for decision-making. In this study, seismic zoning of Ardabil city on the seismic bedrock level was studied using deterministic hazard analysis method, and fuzzy inference system. The purpose of earthquake hazard analysis is to estimate the strong ground motion parameters in a time period and in a specific site. In all steps of seismic hazard analysis, there are uncertainties that make inevitable use of appropriate methods in seismic hazard assessment. Fuzzy logic is known as a reliable method to evaluate seismic hazards with reliable results in a short time with a simple and flexible process. Iran is one of the most earthquake-prone countries in the world where cities severely suffered during this natural phenomenon. The city of Ardabil with the coordinates of 38.25 North and 48.30 East, is the center of Ardabil province and is located in the northwestern part of Iran. Due to its location among several important active faults with a background of numerous historical destructive earthquakes, its seismicity and hazard analysis seems to be necessary. For this purpose, all the active faults located within a radius of 150 km from the city center along with their seismic history were studied and 20 potential seismic sources were selected for seismic hazard analysis. In the present study, seismic hazard zoning analysis of the Ardabil city is first performed by the conventional deterministic method by meshing the whole area under study with dimensions of 1000 × 1000 meters; then it is performed using the fuzzy inference system for the centers of each mesh, and the results are compared. In deterministic seismic hazard analysis (DSHA), 5 attenuation relationships were used to determine the peak ground acceleration (PGA) and the site-specific response spectrum for the center of each mesh. According to the results obtained by DSHA method, the value of horizontal PGA varies between 0.24g and 0.43g, while using the fuzzy inference system it varies between 0.25g and 0.43g. As a result, the maximum horizontal PGA in this area can be suggested about 0.43g. According to the results obtained from both methods, source No. 3, for which the Bozqoush fault is its main active fault, can be considered the main source potentially causing destructive earthquakes in the future compared to the other sources. Moreover, this source is located at a very close distance to Ardabil city. As well, in general, it can be concluded that the western parts of the city are more prone of sever earthquakes compared to the other parts of the city, and therefore, it is better to build important buildings and infrastructures in areas with lower PGA (eastern parts of the city) and encourage the politicians to urban development to this direction in the future. This study clearly confirms that new techniques such as fuzzy methods can be used to improve and develop the seismic hazards analysis.

Keywords

Subjects

[1] Website, International Institute of Earthquake Engineering and seismology. Available at: www.iiees.ac.ir.
[2] Boostan E., Mirzaei N., Eskandari Ghadi M. & Shafiee A. 2011 Seismic zoning of Tehran Region using fuzzy sets. Journal of the Earth and Space Physics, 38(2), 29-44 (In Persian).
[3] Juang C. H. & Eltont D. J. 1986 Fuzzy logic for estimation of earthquake intensity based on building damage records. Civil Engineering Systems, 3(4), 187-191.
[4] Chen D., Dong W. & Shah HC. 1988 Earthquake recurrence relationships from fuzzy earthquake magnitudes. Soil Dynamics and Earthquake Engineering, 7(3), 136-142.
[5] Frangpol Μ., Ikejima K. & Hong K. 1988 Seismic Hazard Prediction Using A Probabilistic-Fuzzy Approach. Structural Safety, 5(2), 109-117.
[6] Sánchez-Silva M. & García L. 2001 Earthquake Damage Assessment Based on Fuzzy Logic and Neural Networks. Earthquake Spectra, 17(1), 89–112.
[7] Vojoudi M., Zare M. & Nourzad A. 2007 Fuzzy inference model for earthquake hazard analysis. 02nd International Conference on Integrated Natural Disaster Management, Tehran, (In Persian).
[8] Sen Z. 2010 Rapid visual earthquake hazard evaluation of existing buildings by fuzzy logic modeling. Expert Systems with Applications, 37(8), 5653–5660.
[9] Jorjiashvili N., Yokoi T. & Javakhishvili Z. 2011 Assessment of uncertainties related to seismic hazard using fuzzy analysis. Natural Hazards, 60, 501–515.
[10] Ghodrati Amiri G., Asmari Saad Abad S. & Zare Hossein Zadeh A. 2013 Earthquake Risk Assessment Using Fuzzy Inference Systems and its Application in Seismic Rehabilitation Studies. Modares Civil Engineering Journal (M.C.E.J), 13(4), 71-84 (In Persian).
[11] Fayezi A. & Moharrami H. 2014 Optimal Control of Structures Equipped with MR Dampers Using ANFIS. Modares Civil Engineering Journal (M.C.E.J), 14(20), 101-113 (In Persian).
[12] Boostan E., Tahernia N. & Shafiee A. 2015 Fuzzy-probabilistic seismic hazard assessment case study: Tehran region, Iran. Natural Hazards, 77(2), 525-541.
[13] Ahumada A., Altunkaynak A. & Ayoub A. 2015 Fuzzy logic-based attenuation relationships of strong motion earthquake records. Expert Systems with Applications, 42(3) 1287-1297.
[14] Tavakoli B. & Ghafory-Ashtiany M. 1999 Seismic hazard assessment of Iran. J Annali DiGeofisica, 42(6), 1013-1022.
[15] 2015 Iranian Code of Practice for Seismic Resistance Design of Buildings: Standard No. 2800. 4th Edition. Building and Housing Research Center (In Persian).
[16] Mousavi Bafrouei S. H., Mirzaei N., Shabani E. & Eskandari-Ghadi M. 2014 Seismic hazard zoning in Iran and estimating peak ground acceleration in provincial capitals. Journal of the Earth and Space Physics, 40(4), 15-38 (In Persian).
[17] Berberian M. 1976 Documented earthquake faults in Iran. Geological Survey of Iran, 39, 143-186.
[18] Ambraseys N. N. & Melville C. P. 1982 A History of Persian Earthquakes. Cambridge: Cambridge University Press, 240 Pages.
[19] Hessami Kh., Jamali F. & Tabassi H. 2003 Major Active Faults of Iran. Tehran: International Institute of Earthquake Engineering and seismology (IIEES). 1 Page.
[20] Website, Geological Survey & Mineral Explorations of Iran. Available at: www.gsi.ir.
[21] Berberian M. 2014 Chapter 13 - 1964–1997 Coseismic Surface Faulting. Developments in Earth Surface Processes, 17, 293-371.
[22] Berberian M. 1976 Geological Survey of Iran Generalized Fault Map of Iran. 1 Page.
[23] Su S. S. 1988 Seismic Hazard Analysis for The Philippines. Natural Hazards. 27-44.
[24] Alizadeh A., Afsari N. & Taghizadeh F. Farahmand. 2019 Evaluation of Deterministic seismic hazard in Nowshahr Port by using the fuzzy system. Journal of Natural Environmental Hazards, 8(19), 175-194 (In Persian).
[25] Kramer S. L. 1996 Geotechnical Earthquake Engineering. New Jersey: Prentice Hall.
[26] Green A. & Hell J. 1994 An Overview of Selected Seismic Hazard Analysis Methodologies. Civil Engineering studies, Urbana-Champaign: Structural Research Series, No. 592, 91 Pages.
[27] Wells D. L. & Coppersmith K. J. 1994 New Empirical Relationships Among magnitude, Rupture length, Rupture Width, Rupture Area and Surface Displacement. Bulletin of the Seismological Society of America, 84(4), 974-1002.
[28] Zare M. 1999 Contribution a 1 etude des movements forts en Iran, du catalogue aux lois d'attention. These pour obtenir le litre de docteur de L'universite Joseph Fourier –Grenoble 1-France.
[29] Mohajer Ashjai A. & Nowroozi A. 1978 Observed and probable intensity zoning of Iran. Tectonophysics, 49(3), 149-160.
[30] Nowroozi A. 1985 Empirical Relations Between Magnitude and Fault Parameters for Earthquakes in Iran. Bulletin of the Seismological Society of America, 75(5), 1327-1338.
[31] Slemmos D. B. 1986 Determination of earthquake size from surface faulting events. Proceeding of international seminar on seismic zonation.
[32] Tavakoli B. 1994 The Basics of Seismic Hazard Analysis. Tehran: International Institute of Earthquake Engineering and Seismology (IIEES), 1-43.
[33] Erdik A., Sesetyan K., Demircioğlu M. B., Tüzün C., Giardini D., Gülen L., Akkar D. S. & Zare M. 2012 Assessment of Seismic Hazard in the Middle East and Caucasus: EMME (Earthquake Model of Middle East) Project. In Proceedings of the 15th world conference on earthquake engineering, Lisbon, Portugal.
[34] 2014 Guideline for Seismic Hazard Analysis, No. 626. Islamic Republic of Iran Vice Presidency for Strategic Planning and Supervision, 48 Pages (In Persian).
[35] Campbell K. W. & Bozorgnia Y. 2014 NGA-West2 Ground Motion Model for the Average Horizontal Components of PGA, PGV, and 5% Damped Linear Acceleration Response Spectra. Earthquake Spectra, 30(3), 1087–1115.
[36] Boore D. M., Stewart J. P., Seyhan E. & Atkinson G. A. 2014 NGA-West2 equations for predicting PGA, PGV, and 5% damped PSA for shallow crustal earthquakes. Earthquake Spectra, 30(3), 1057–1085.
[37] Kale Ö., Akka S., Ansari A. & Hamzehloo H. 2015 A ground-motion predictive model for Iran and Turkey for horizontal PGA, PGV, and 5% damped response spectrum: Investigation of possible regional effects. Bulletin of the Seismological Society of America, 105(2A), 963–980.
[38] Farajpour Z., Zare M. & Pezeshk SH. 2019 A New Empirical Ground-Motion Model for Iran. Bulletin of the Seismological Society of America, 109(2), 732–744.
[39] Darzi A., Zolfaghari M. R., Cauzzi C. & Fäh D. 2019 An Empirical Ground-Motion Model for Horizontal PGV, PGA, and 5% Damped Elastic Response Spectra (0.01–10 s) in Iran. Bulletin of the Seismological Society of America, 109(3), 1041–1057.
[40] Kaklamanos J., Baise L. G. & Boore D. M. 2011 Estimating unknown input parameters when implementing the NGA ground-motion prediction equations in engineering practice. Earthquake Spectra, 27(4), 1219–1235.
[41] Khodadadi, Sh. 2021 Ardabil Earthquake Hazard Zoning in Bedrock Using Deterministic Seismic Hazard Analysis and Fuzzy Logic. Master Thesis. University of Guilan.
[42] L. A. Zadeh. (1965). Fuzzy sets. Inf. Control. 8, pp. 338-353.
[43] Lotfi A. Z. 2015 Fuzzy logic—a personal perspective, Fuzzy Sets and Systems, 281, 4-20.
[44] Lotfi A. Z. 1975 The concept of a linguistic variable and its application to approximate reasoning, Part I. Inf. Sci, 8(3), 199–249.
[45] Chavoshi A. S., Lajevardi S. M. R. & Tahernia N. 2016 Influence of shape of membership functions on fuzzy inference system. Third National Conference on Electrical and Computer Engineering Distributed Systems and Smart Grids, Kashan (In Persian).
Modares Civil Engineering journal
Volume 22, Issue 2
May and June 2022
Pages 57-74