Abstract

Loess is a special geotechnical material with strong structural properties, and the microstructural characteristics of loess significantly influence its macroscopic physical features, mechanical properties, and catastrophic behavior. In this paper, serial samples were extracted from the continuous loess and paleosol strata of the Bai Lu tableland; with these samples, the optical microscopy‐based serial sectioning method was adopted to study the quantitative characterization and variation in the loess microstructure. Three‐dimensional characteristics and quantitative parameters of the particles, pores, and throats of the loess were obtained. The results indicate that the volume, Eq‐Radius, and major‐minor axis ratio of the loess particles satisfy third‐order, third‐order, and second‐order Gaussian distributions, respectively. The Eq‐Radius of the loess pores and throats satisfies a first‐order Gaussian distribution, and the throat channel length satisfies a gamma distribution. With increasing stratum depth, the particles become more flattened, the throat radii become larger and the pore channels become slenderer. The variation in fitting parameters and the correlations between the macrophysical and mechanical properties of loess were then explored. The study of the microstructure of loess contributes to a better understanding of the catastrophic behavior of loess and the physical mechanism of geologic hazards in this area.

Highlights

  • Loess generally shows a high strength when dry, but under conditions of soaking, the skeleton of loess weakens rapidly, which would result in the collapse of loess, settlement of loess ground, and instability of a loess slope [1,2,3]

  • The deformation and failure of loess begins with shear deformation and slippage among particles; on the other hand, the mechanical properties of loess are dominated by its microstructure [4, 6, 7]. e microstructure of loess mainly consisted of pores, particles, and connections, which control the contact system and force chains in the loess and dominate the macrophysical and mechanical properties of loess [8]. e study of the microstructure of loess contributes to a better understanding of the catastrophic behavior and physical mechanism of loess geologic hazards

  • According to the strata data, the loess in the Bai Lu tableland has been depositing since the early Pleistocene, accumulating a thickness of approximately 65–126 m of a continuous loess-paleosol strata sequence. e Bai Lu tableland is a suitable site for studying the variation in microstructural characteristics of the loess-paleosol sequence

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Summary

Research Article

Quantitative Research and Characterization of the Loess Microstructure in the Bai Lu Tableland, Shaanxi Province, China. Loess is a special geotechnical material with strong structural properties, and the microstructural characteristics of loess significantly influence its macroscopic physical features, mechanical properties, and catastrophic behavior. Serial samples were extracted from the continuous loess and paleosol strata of the Bai Lu tableland; with these samples, the optical microscopy-based serial sectioning method was adopted to study the quantitative characterization and variation in the loess microstructure. Reedimensional characteristics and quantitative parameters of the particles, pores, and throats of the loess were obtained. E study of the microstructure of loess contributes to a better understanding of the catastrophic behavior of loess and the physical mechanism of geologic hazards in this area The particles become more flattened, the throat radii become larger and the pore channels become slenderer. e variation in fitting parameters and the correlations between the macrophysical and mechanical properties of loess were explored. e study of the microstructure of loess contributes to a better understanding of the catastrophic behavior of loess and the physical mechanism of geologic hazards in this area

Introduction
Fault River
Phi Theta x y plane y
Probability density of fitting curves
Pore Throat
Probability density fitting curve
Findings
Probability density of fitting curve
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