Static and dynamic strength properties of highly structured clay-rich diatomite in Shengzhou, China
Source abstract
Abstract
Diatomite is a widespread geological substance found in coastal and lake areas worldwide. Although diatomites are increasingly used in geotechnical engineering construction, a significant knowledge gap exists regarding their mechanical responses to static and dynamic loadings, particularly in high-speed railway projects. This study investigates the static and dynamic behaviors of diatomites through extensive experiments, considering both natural and remolded states. It focuses on representative diatomite specimens obtained from the Shengzhou region in China, an area intersected by the Hang-Shao-Tai high-speed railway. The results of uniaxial compression and undrained triaxial shear tests show that the structural degradation of diatomite significantly impacts its stress-strain responses, failure patterns, and mechanical parameters under static and dynamic loading conditions. The structural effects of natural diatomite tend to degrade as the confining pressure level increases, resulting in corresponding changes in its mechanical parameters. Undrained triaxial shear tests conducted on natural diatomite reveal that the inclinations of the shear band closely correspond to those predicted by the Mohr-Coulomb solution. Additionally, we present a modified hyperbolic-type model to evaluate the damping ratio of diatomites. Furthermore, a power-law model based on Hardin`s formula was used to predict the maximum shear modulus of diatomites under varying stress levels and void ratios. Microstructural and chemical analyses were conducted using scanning electron microscopy and X-ray diffraction to gain insights into the observed structural effects at the microscale.
Source: expertdata · Quality: candidate unverified · Source record ↗
Research context
OpenAlex topics: Grouting, Rheology, and Soil Mechanics · Diatoms and Algae Research · Geotechnical Engineering and Soil Mechanics
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
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