Estimasi Kecepatan Gelombang Geser (Vs) Melalui Inversi Kurva Horizontal to Vertical Spectrum Ratio Pada Jalur Sesar Grindulu

Caesardi, Muhammad Azmi (2018) Estimasi Kecepatan Gelombang Geser (Vs) Melalui Inversi Kurva Horizontal to Vertical Spectrum Ratio Pada Jalur Sesar Grindulu. Undergraduate thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Sesar Grindulu beberapa kali menyebabkan gempa bumi di Kabupaten Pacitan. Getaran yang ditimbulkan gempa bumi dapat menyebabkan kerusakan bangunan yang tergantung pada karakteristik tanah setempat dan kondisi bangunan. Oleh karena itu, penelitian pencitraan Sesar Grindulu menggunakan kecepatan gelombang geser (Vs) perlu dilakukan. Dalam penelitian ini, nilai Vs 1D diestimasi menggunakan algoritma Monte Carlo. Selanjutnya, Vs 2D didapatkan melalui interpolasi dari beberapa Vs 1D. Analisis Vs 2D ini menunjukkan bahwa keberadaan sesar-sesar tersebut dapat teridentifikasi (sesuai dengan peta geologi). Hasil Vs 2D didukung oleh hasil analisa intepretasi kualitatif (kurva HVSR). ============================================================ The Grindulu fault have caused several earthquakes in Pacitan City. Vibration is caused by earthquakes can cause damage to buildings that depend on local soil characteristics and building conditions. Therefore, research on Grindulu Fault imaging using shear wave velocity (Vs) is needed. In this study, Vs 1D values have estimated using the Monte Carlo algorithm. Furthermore, Vs 2D is obtained through interpolation of several Vs 1D. The 2D Vs analysis shows that the existence of these faults can be identified (correlated to the geological map). The 2D Vs results are supported by the results of qualitative interpretation analysis (HVSR curve).

Item Type: Thesis (Undergraduate)
Additional Information: RSFi 622.159 2 Cae e
Uncontrolled Keywords: inversi HVSR, Sesar Grindulu, mikrotremor, Kecepatan Gelombang Geser (Vs)
Subjects: G Geography. Anthropology. Recreation > GB Physical geography
Q Science
T Technology > TN Mining engineering. Metallurgy
Divisions: Faculty of Science and Data Analytics (SCIENTICS) > Chemistry > 47101-(S2) Master Thesis
Depositing User: Muhammad Azmi Caesardi
Date Deposited: 18 Nov 2020 04:36
Last Modified: 18 Nov 2020 04:36
URI: http://repository.its.ac.id/id/eprint/59169

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