Grain size partitioning in loess–paleosol sequence on the west coast of South Korea using the Weibull function

Park, Chung-Sun; Hwang, Sang-Ill; Soon-Ock, Yoon; Choi, Jongnam

doi:10.1016/j.catena.2014.05.018

Cited by 12 publications

(3 citation statements)

References 47 publications

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“…The sieve‐hydrometer method determines that the measured clay particle content is higher, and the curve in the range of that particle size growth rate is faster. The differences in measurement results are mainly attributed to the distinct particle dispersion degrees and different particle size transformation theories between the two methods (Park et al, 2014).…”

Section: Discussionmentioning

confidence: 99%

“…However, the dispersion process does not completely destroy the agglomerated structure in the soil particles but rather only disperses the weakly cemented agglomerates. The presence or absence of very fine components in loess depends largely on the laser diffraction, refractive index (RI) and absorptive index (AI) (Park et al, 2014). We employed Mie theory in the conversion of data from the diffraction properties of particles analysed to the particle size (RI = 1.333, AI = 0.15).…”

Section: Physical Methods Characteristicsmentioning

confidence: 99%

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A new method for determining loess particle size distribution based on ‘core + clothes’ structure

Zhou

et al. 2023

Earth Surf Processes Landf

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The particle size distribution (PSD) of loess particles and agglomerates is the key factor determining the microstructure of loess. The PSD largely determines many physical and mechanical properties such as mechanical strength, deformation characteristics and permeability of loess. In this paper, we combined image processing, geometric measurements and statistical methods to quantitatively characterize the scanning electron microscopy (SEM) images of loess. A new method based on the ‘core + clothes’ structure is proposed to determine the PSD. The developed Gaussian mixture model is applicable to describe the overall distribution of the image pixel density. Determining pixel density distribution and particle boundary allows for the measurement of various geometric parameters. The comparison analyses suggest that the sieve‐hydrometer method has a well‐developed test procedure; however, the measured particle size is limited to 0.075 mm. The laser diffraction method is simple and fast, yet only weak agglomerates can be dispersed, and very fine particles are influenced by size data conversion theory and light source parameters. X‐ray microtomography has the advantage of a non‐destructive sample preparation and intuitive process. However, the results are greatly affected by the parameter settings and segmentation algorithm, and the segmentation effect is poor for particles with a size smaller than 12 μm. The new image processing technique developed in this study improves the limitation of the measurement results via changes in the loess state (water content, stress level). Moreover, different PSDs can be determined according to the variation of functional units. This work is of great significance for the study of numerous properties related to the loess state.

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Section: Discussionmentioning

confidence: 99%

Section: Physical Methods Characteristicsmentioning

confidence: 99%

A new method for determining loess particle size distribution based on ‘core + clothes’ structure

Zhou

et al. 2023

Earth Surf Processes Landf

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“…This latter measure has received much attention in the literature but is a less meaningful metric in polymodal sediments than in unimodal sediments. Recently, numerical grain-size partitioning has been employed to better describe changes in the distribution of polymodal (particularly eolian) sediments (Sun et al, 2002, 2004, 2008; Lim and Matsumoto, 2006; Xiao et al, 2009; Park et al, 2014). The theoretical basis for this technique rests on the idea that different transport mechanisms produce unique modal grain sizes in the sediment they deposit (Harding, 1949; Middleton, 1976; Ashley, 1978; Bagnold and Barndorff-Nielson, 1980).…”

Section: Introductionmentioning

confidence: 99%

Variations in late Quaternary wind intensity from grain-size partitioning of loess deposits in the Nenana River Valley, Alaska

et al. 2017

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A high-resolution column of 57 loess samples was collected from the Dry Creek archaeological site in the Nenana River Valley in central Alaska. Numerical grain-size partitioning using a mixed Weibull function was performed on grain-size distributions to obtain a reconstructed record of wind intensity over the last ~15,000 yr. Two grain-size components were identified, one with a mode in the coarse silt range (C1) and the other ranging from medium to very coarse sand (C2). C1 dominates most samples and records regional northerly winds carrying sediment from the Nenana River. These winds were strong during cold intervals, namely, the Carlo Creek glacial readvance (14.2–14 ka), a late Holocene Neoglacial period (4.2–2.7 ka), and recent glacier expansion; weak during the Allerød (14–13.3 ka) and Younger Dryas (12.9–11.7 ka); and variable during the Holocene thermal maximum (11.4–9.4 ka). Deposition of C2 was episodic and represents locally derived sand deposited by southerly katabatic winds from the Alaska Range. These katabatic winds occurred mainly prior to 12 ka and after 4 ka. This study shows that numerical grain-size partitioning is a powerful tool for reconstructing paleoclimate and that it can be successfully applied to Alaskan loess.

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Sediment transport processes in the Pearl River Estuary as revealed by grain-size end-member modeling and sediment trend analysis

2017

Geo-Mar Lett

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Grain size partitioning in loess–paleosol sequence on the west coast of South Korea using the Weibull function

Cited by 12 publications

References 47 publications

A new method for determining loess particle size distribution based on ‘core + clothes’ structure

A new method for determining loess particle size distribution based on ‘core + clothes’ structure

Variations in late Quaternary wind intensity from grain-size partitioning of loess deposits in the Nenana River Valley, Alaska

Sediment transport processes in the Pearl River Estuary as revealed by grain-size end-member modeling and sediment trend analysis

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