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Novel method to estimate horizontal variability of shear wave velocity through multichannel analysis of surface waves

Authors
Chang, Yen-HsiangTsai, Chi-ChinGe, LouisPark, Duhee
Issue Date
Dec-2024
Publisher
Elsevier BV
Keywords
Coefficient of variation; Multichannel analysis of surface waves; Scale of fluctuation; Shear wave velocity; Spatial variability
Citation
Engineering Geology, v.343, pp 1 - 15
Pages
15
Indexed
SCIE
SCOPUS
Journal Title
Engineering Geology
Volume
343
Start Page
1
End Page
15
URI
https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/212632
DOI
10.1016/j.enggeo.2024.107799
ISSN
0013-7952
1872-6917
Abstract
Scale of fluctuations (SOFs) of spatially variable soil properties have been regarded as one of the important parameters for performing reliability-based design in geotechnical engineering. However, the information required to estimate the SOFs in practice is limited, especially in the horizontal direction. In this study, the potential use of Multichannel Analysis of Surface Waves (MASW) to estimate the SOFs of shear wave velocity (VS) in horizontal direction is investigated through a series of numerical investigations. 2D random field models with a vertically increasing trend of VS were first simulated with different levels of variability controlled by the coefficient of variation (COV) and SOF. Afterwards, a large number of numerical MASW tests were performed using a 2D finite difference method, where the survey lines were progressively shifted. Results show that the COV of VS can be determined from the scatter of the dispersion curves, whereas the horizontal SOF of VS can be appropriately estimated from the phase velocity profile presented in the wavelength form. Additionally, in-situ MASW tests were conducted to estimate the horizontal SOF, and the obtained results align with those estimated by different methods. It is highlighted that the accuracy of the estimation depends on survey length. The interpretation using a long array reflects an averaged site condition of the survey area, thus losing the variability information. Favorable predictions are produced when survey length is shorter than 1.0 SOF. However, it should be noted that use of short survey length may limit the depth of investigation.
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