Investigation of Site Characterization in Akdeniz Region by Using Seismic Refraction and Surface Wave Methods

Abstract

Multichannel Analysis of Surface Waves (MASW), Refraction Microtremor (ReMi), and Microtremor measurements was performed to predict site characterization at 65 strong-motion stations of AFAD (Disaster and Emergency Management Presidency) in the Akdeniz region in Turkey. Reliable field response information is required to investigate the region's impacts and assess the risk of the area. The soil conditions of the Akdeniz region are specified from MASW, ReMi, and Microtremor studies of AFAD's strong motion stations in this area. HVSR technique was conducted to determine dominant frequency values at different amplification levels. The Akdeniz region was classified according to Vs 30 based NEHRP Provisions [1], Eurocode-8 [2] and TBDY-2018 [3] and Rodrigez-Marek [4]. According to the [1], one station is classified as class A, 7 stations as B and 38 stations as C and 19 stations to be class D. According to [2], 6 stations correspond to class A, 39 stations B, and 20 stations D. The soil classes in the NEHRP system correspond to that of TBDY-2018 [3]. According to [4], 8 stations are classified as A, 17 stations B, 8 stations C-1, 13 stations C-2, 5 stations C-3,11 stations D-1, 1station D-2, 1 station D-3, 1 station E and 1 station is undistinguished. The predominant period of the region ranges from 0.07 to 1.47s, and the dominant magnification values vary between 0.79 and 8.5.

Use of Machine Learning Algorithms in Location Determination for Safe Construction

“…In this study, Seismic refraction, Multi-Channel Surface Wave Analysis (MASW), refractive microtremor (ReMi) and microtremor studies were carried out to investigate the distribution of S-wave velocity in shallow soils at 65 strong mobile stations in the Mediterranean region of southern Turkey. Shear wave velocity Vs30(m/s) H/V amplitude spectrum of dominant frequency Dominant period To(s) values were calculated [11] and these values were used as input to classification algorithms. Soil classification was made according to TBDY (Turkish Building Regulations, 2018) given in Figure 1 using different algorithms [12].…”