Vs30 değerine bağlı koherans modeli

Abstract

Depremlerin yol açtığı kuvvetli yer hareketi uzun yapıların her yerinde aynı olmayacaktır. Yer hareketindeki bu farklılığın, uzun yapıların tasarımı üzerinde önemli bir etkisi vardır. Depreme dayanıklı tasarımın, son yüzyıllarda deprem yer hareketinin değişkenliğini araştırmada etkisi olmuştur. Kuvvetli yer hareketinin bu değişkenliği, frekans veya zaman açısından tanımlanabilir. Bu çalışmada, koherans adı verilen frekans tanım alanı yönünden deprem yer hareketlerinin değişkenliği ele alındı. Bugüne kadar genelde, zemin etkisi dikkate alınmadan çeşitli koherans modelleri oluşturulmuştur. Bu bağlamda, 30 m derinliğin üstündeki ortalama kayma dalgası hızına (Vs30) bağlı olarak deprem yer hareketinin mekansal değişimi analiz edildi. İlk olarak, koherans değerleri İstanbul Deprem Acil Müdahale Sistemi tarafından kaydedilen altı depremin veriler kullanılarak hesaplandı. Koherans modelini elde etmek için duraklamalı koherans verileri dikkate alındı. Modelin kayıtlı verilerde en iyi sağlaması için doğrusal olmayan regresyon analizi kullanıldı. İkili istasyon gruplarının Vs30 değerlerine dayanarak bir katsayı tanımlandı. Bu Vs30 katsayısına bağlı koherans modeli; EW, NS ve dikey bileşenler için oluşturuldu. Beklendiği üzere, frekans ve istasyonlar arası mesafesinin artmasıyla koherans fonksiyonunun azaldığı gözlendi. Vs30 katsayısındaki azalma, koherans değerlerinde artışa neden oldu. EW ve NS bileşenleri için üretilen koherans modelleri arasındaki fark oldukça küçüktür. Düşey bileşen için üretilen model yatay için üretilenden farklıdır. Gelecekteki çalışmalarda, elde edilen koherans modeli uzun yapıların depreme dayanıklı tasarımı için mekansal değişen yer hareketlerini simüle etmek için kullanılır.

Keywords

• Depremler,İstanbul Deprem Erken Uyarı sistemi,Koherans Modeli,Vs30

Vs30-based Coherency Model

Abstract

Strong ground motion caused by earthquakes at every point of extended structures would not be same. This difference in ground movement has an important effect on the design of these types of structures. Meanwhile, the seismic resistant design has been lead to investigate the variability of earthquake ground motion over last decades. This variability of strong ground motion can define in terms of frequency or time. In this study, frequency domained variability named coherency is considered. Several coherency models have been proposed without considering soil effect. In this context, spatial variation of seismic ground motion based on the average shear wave velocity over the upper 30 m of depth, Vs30 is analyzed. Initially, coherency values are calculated using data triggered during six earthquakes recorded by the Istanbul Earthquake Rapid Response System. Lagged coherency data is considered in the process to get the coherency model. Nonlinear regression analysis is used for the model to obtain a good-fit to observed data. A coefficient is defined based on Vs30 values of the station-pairs. The cohereny model based on this coefficient of Vs30 is derived for EW and NS components. It is expected that coherency function decreases with the increase of frequency and separation distance. The decrease in the coefficient of Vs30 causes decrease in coherency. The variance in the coherency model between EW and NS components is small. This coherency model is used to simulate spatial variable ground motion for the accurate seismic design of elongated structures for the future studies.

Keywords

• Earthquakes,Istanbul Earthquake Rapid Response System,Coherency Model,Vs30

References

1. Abrahamson, N. A., Schneider, J. F., & Stepp, J. C. (1991). Empirical Spatial Coherency Functions for Applications to Soil-Structure Interaction Analyses. Earthq Spectra, 7, 1-27.
2. Abrahamson, N. A. (1992). Generation of Spatially Incoherent Strong Motion Time Histories. Proc Tenth World Conf Earthq Eng, Madrid, Spain.
3. Abrahamson, N. A. (1993). Spatial Variation of Multiple Support Inputs. Proc the First U.S. Semin Seism Eval Retrofit Steel Bridges, San Francisco.
4. Abrahamson, N. A. (2005). Effect of Local Site Condition on Spatial Coherency. Electric Power Research Institute, Rpt. No.RP2978-05.
5. Bayrak, E. (2019). Doğu Anadolu Bölgesi için En Büyük Yer İvmesi Tahmini. Avrupa Bilim ve Teknoloji Dergisi, (17), 676-681.
6. Cacciola, P., & Deodatis, G. (2011). A method for generating fully non-stationary and spectrum-compatible ground motion vector processes. Soil Dyn Earthq Eng, 2011; 31: 351-360.
7. Conte, J. P., Pister, K. S., & Mahin, S. A. (1992). Non-Stationary ARMA Modeling of Seismic Ground Motions. Soil Dyn Earthq Eng, 11, 411-426.
8. Der Kiureghian, A. (1996). A coherency model for spatially varying ground motions. Earthq Eng Struct Dyn, 25, 99-111.

9. Dilmaç, H. & Demir, F. (2019). Earthquake Vulnerability Assessment of RC Structures with Variable Infill Wall Properties. Avrupa Bilim ve Teknoloji Dergisi, (17), 176-189.
10. Ellis, G. W., & Cakmak, A. S. (1991). Time Series Modeling of Strong Ground Motion from Multiple Event Earthquakes. Soil Dyn Earthq Eng, 10, 42-54.
11. Fenton, G. A., & Vanmarcke, E.H. (1990). Simulations of Random Fields via Local Average Subdivision. J Eng Mech, 116, 1733-1749.
12. Hao, H, Oliveira, C. S., & Penzien, J. (1989). Multiple-Station Ground Motion Processing and Simulation based on SMART-1 Array Data. Nuclear Eng Des, 111, 293-310.
13. Harichandran, R. S., & Vanmarcke, E. (1986). Stochastic Variation of Earthquake Ground Motion in Space and Time. J Eng Mech ASCE, 112, 154-174.
14. Harichandran, R. S. (1988). Local Spatial Variation of Earthquake Ground Motion, in: Von Thun, J. L. (editor), Earthquake Engineering and Soil Dynamics II - Recent Advances in Ground-Motion Evaluation. American Society of Civil Engineers, New York, 203-217.
15. Harichandran, R. S. (1991). Estimating the Spatial Variation of Earthquake Ground Motion from Dense Array Recordings. Struct Saf, 10, 219-233.
16. Harmandar, E., Durukal, E., Erdik, M., & Özel, O. (2006a). Spatial Variation Strong Ground Motion in Istanbul: Preliminary Results based on Data from the Istanbul Earthquake Rapid Response System. European Geosciences Union (EGU) General Assembly, Vienna, Austria.
17. Harmandar, E., Durukal, E., Erdik, M., & Ozel, O. (2006b). Spatial Variation of Strong Ground Motion in Istanbul. First European Conf Earthq Eng Seism, Geneva.
18. Harmandar, E., Durukal, E., & Erdik, M. (2012). A method for spatial estimation of peak ground acceleration in dense arrays. Geophys J Int, 191, 1272-1284.
19. Loh, C. H., & Yeh, Y. T. (1988). Spatial Variation and Stochastic Modeling of Seismic Differential Ground Movement. Earthq Eng Struct Dyn, 16, 583-596.
20. Loh, C. H., & Lin, S. G. .(1990) Directionality and Simulation in Spatial Variation of Seismic Waves. Eng Structs, 12, 134-143.
21. Mignolet, M. P., & Spanos, P. D. (1992) Simulation of Homogeneous Two-Dimensional Random Fields: Part I—AR and ARMA Models. J Appl Mech, 59, 260-269.
22. Novak, M. (1987). Discussion on Stochastic Variation of Earthquake Ground Motion in Space and Time by R. S. Harichandran and E. H. Vanmarcke. J Eng Mech Div, 113, 1267-1270.
23. Oliveira, C. S., Hao, H., & Penzien, J. (1991). Ground Motion Modeling for Multiple-Input Structural Analysis. Struct Saf, 10, 79-93.
24. Ramadan, O., & Novak, M. (1993). Coherency Functions for Spatially Correlated Seismic Ground Motions. Geotechnical Research Center Report No. GEOT-9-93, University of Western Ontario, London, Canada.
25. Ramadan, O., & Novak, M. (1994). Simulation of Multidimensional Anisotropic Ground Motions. J Eng Mechs, 120, 1773-1785.
26. Rice, S. O. (1944). Mathematical Analysis of Random Noise. Bell Syst Technical J, 23, 282-332.
27. Schneider, J., Stepp, J., Abrahamson, N., (1992). The spatial variation of earthquake ground motion and effects of local site conditions, Proceedings of the Tenth World Conference on Earthquake Engineering, A. A. Balkema, Rotterdam, 2, 967-972.
28. Shama, A. (2007). Simplified Procedure for Simulating Spatially Correlated Earthquake Ground Motions. Eng Structs, 29, 248-258.
29. Shinozuka, M. (1972). Monte Carlo Solution of Structural Dynamics. Computers and Structs, 2, 855-874.
30. Yamamoto, Y. (2011). Stochastic model for earthquake ground motion using wavelet packets, PhD Thesis, Stanford University.
31. Zerva, A., & Harada, T. (1997). Effect of surface layer stochasticity on seismic ground motion coherence and strain estimates. Soil Dyn Earthq Eng, 16, 445-57.
32. Zerva, A., & Zhang, O. (1997). Correlation Patterns in Characteristics of Spatially Variable Seismic Ground Motions. Earthq Eng Struct Dyn, 1997, 26, 19-39.
33. Zerva, A., & Katafygiotis, L. S. (2000). Selection of Simulation Scheme for the Nonlinear Seismic Response of Spatial Structures. Proc Fourth Int Colloq Computation of Shell and Spatial Structs, Chania, Greece.
34. Zerva, A. (2009). Spatial Variation of Seismic Ground Motions: Modeling and Engineering Applications. New York CRC Press.
35. Zerva, A., & Zervas, V. (2002). Spatial Variation of Seismic Ground Motions: An Overview. Appl Mech Rev, 55 (3), 271-297.