Study on the Correlation Between Fractal Dimension of Sedimentary Soil Layer and Shear Wave Velocity in Yuxi Basin

TIefei Li (), Xueliang Chen and Sen Qiao
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TIefei Li: China Earthquake Administration, China, Institute of Geophysics
Xueliang Chen: China Earthquake Administration, China, Institute of Geophysics
Sen Qiao: China Earthquake Administration, China, Institute of Geophysics

A chapter in Proceedings of the 10th Annual Meeting of Risk Analysis Council of China Association for Disaster Prevention (RAC 2022), 2023, pp 69-76 from Springer

Abstract: ABSTRACT Grain size characteristics of soil layers are closely related to their engineering properties, especially shear wave velocity, and are therefore often taken as the main criteria for soil engineering classification. In this paper, fractal theory is used as a method to study the gradation characteristics of soil particles in order to reflect the characteristics of sediment particles in the process of water flow handling and sediment, and to establish the relationship between the characteristics of soil particles in the hydrodynamic environment. Dimensional analysis results of 36 typical soil samples from six boreholes in Yuxi Basin are given in this paper. It is considered that the granular soils formed in the river sedimentary environment have obvious fractal characteristics. Dimensional values of coarse-grained soils such as gravel and gravel sand layers in Yuxi Basin are similar, which indicates that they may be formed in the river sedimentary environment dominated by Yuxi Dahe River. In areas dominated by sedimentary environments such as slope deposit and flood deposit, the fractal dimension characteristics of granular soils are not obvious, which may be due to complex and repeated water flow transport of particles. At the same time, the shear velocity of the gravel layer in Yuxi Basin is negatively correlated with the grain dimension.

Keywords: Sedimentary Environment; Particle Size; Fractal Dimension; Shear-wave Velocity (search for similar items in EconPapers)
Date: 2023
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DOI: 10.2991/978-94-6463-194-4_11

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