SHARE WAVE VELOCITY MODEL TO A DEPTH OF 30 METER (Vs30) USING HORIZONTAL VERTICAL TIME FREQUENCY ANALYSIS (HVTFA) METHOD

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Abstract

A share wave velocity model to a depth of 30 meter (vs30) can be used to find the type of the ground as a preventive action against earthquake disaster mitigation. Vs30 is obtained from the inversion of ellipticity curve using HVTFA method. HVTFA method is a method that can minimize the love curve in the ellipticity curve. Therefore, a more reliable share wave velocity can be obtained. It is necessary to find reliability of a model in a further research. The objectives of this research were to find the reliability of HVTFA and HVSR methods and determine the reliability of vs30 model from the result of inversion of Rayleigh-wave ellipticity curve using HVTFA method with duration of microtremor measurement of 0.5 hour, 1 hour, 2 hours, 3 hours, 4 hours, 5 hours and 6 hours. Data used in this research were microtremor data. The microtremor data were processed using HVTFA and HVSR method in Geopsy software to find the ellicpticity curve. Next, the inversion of ellipticity was carried out in dinver software to obtain the share wave velocity model. After that, the error value from the model was calculated using vs%Miss, Boun%Miss, Ev, and Eb. The error value of HVTFA method still met the requirement of reliable model, but not the error value of HVSR method. The high error value in HVSR method was found in Bound%Miss and Eb. It meant that the share wave velocity of HVSR method had a high error value in the estimation of surface depth and thickness. Therefore, HVTFA method produced a more reliable vs30 model than HVSR method. In addition, the velocity model of HVTFA method from microtremor data with duration of 0.5 hour, 1 hour, 2 hours, 3 hours, 4 hours, 5 hours and 6 hours also had reliable model.

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APA

Ridha, S., Syafitri, M., … Martha, A. A. (2023). SHARE WAVE VELOCITY MODEL TO A DEPTH OF 30 METER (Vs30) USING HORIZONTAL VERTICAL TIME FREQUENCY ANALYSIS (HVTFA) METHOD. Journal of Enviromental Engineering and Sustainable Technology, 9(1), 01–09. https://doi.org/10.21776/ub.jeest.2022.009.01.1

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