Abstract:The classical measurement method of particle size for sands and gravels is sieving, but in recent years, imaging methods have been shown to be more reliable. However, imaging procedures require specialized devices (such as Camsizer), proprietary software (such as Optgran-CS), dedicated illumination, or other issues. Furthermore, image resolution in digital cameras improves constantly over time, including in cameras in cellular phones, which leads to the idea that using a standard commercial device and a simple… Show more
“…2 b). F max has been used to analyze particle shapes and particle size distributions from digital imagery in past studies, especially for irregular shapes 17 , 18 . Figure 2 Analysis of ( a ) surface area and ( b ) F max of organic particles using ImageJ software and used to estimate settling velocities in Eqs.…”
The settling velocity of a particle is an integral parameter in stormwater modeling and design. The settling velocity can be used to predict the fate and transport of stormwater particles and if the particles contribute to nutrient loading in a watershed. Prediction of settling velocity for inorganic particles is generally well-researched and well-understood. Organic particles tend to vary widely in their physical properties and there are currently no set standards or empirical equations for estimating the settling velocity of organic particles. This paper presents data from tree leaves and seeds settling velocity experiments to better understand how organic particles settle in the context of settling velocity equations such as the one developed by Ferguson and Church. Analysis of the collected data showed that the second of the two drag coefficients (C2) used in the Ferguson and Church Equation was sensitive to particle type and shape. By averaging C2 by particle type and species, there was a correlation between the observed settling velocity and the settling velocity predicted by the Ferguson and Church Equation (R2 = 0.83). With these results, stormwater modelers and designers are equipped with a better understanding of how to represent common organic particles in terms of settling velocity. Additional research on a wider variety of organic particle types and species would expand on the dataset presented here.
“…2 b). F max has been used to analyze particle shapes and particle size distributions from digital imagery in past studies, especially for irregular shapes 17 , 18 . Figure 2 Analysis of ( a ) surface area and ( b ) F max of organic particles using ImageJ software and used to estimate settling velocities in Eqs.…”
The settling velocity of a particle is an integral parameter in stormwater modeling and design. The settling velocity can be used to predict the fate and transport of stormwater particles and if the particles contribute to nutrient loading in a watershed. Prediction of settling velocity for inorganic particles is generally well-researched and well-understood. Organic particles tend to vary widely in their physical properties and there are currently no set standards or empirical equations for estimating the settling velocity of organic particles. This paper presents data from tree leaves and seeds settling velocity experiments to better understand how organic particles settle in the context of settling velocity equations such as the one developed by Ferguson and Church. Analysis of the collected data showed that the second of the two drag coefficients (C2) used in the Ferguson and Church Equation was sensitive to particle type and shape. By averaging C2 by particle type and species, there was a correlation between the observed settling velocity and the settling velocity predicted by the Ferguson and Church Equation (R2 = 0.83). With these results, stormwater modelers and designers are equipped with a better understanding of how to represent common organic particles in terms of settling velocity. Additional research on a wider variety of organic particle types and species would expand on the dataset presented here.
“…The fragments of all four groups of samples were collected for particle size distribution analysis. The basic method was referred from the literature, 27 and the free software ImageJ was used for image processing work. First, the obtained particle image was binarized, and then the size of each particle size was calculated.…”
Section: Fractal Analysis Of Particle Size Distribution Based On the ...mentioning
The mechanical properties of low-rank coal and its char
particles
are of great significance in many energy and chemical process applications.
The 2.8–4.0 mm narrow size range irregularly shaped particles
of Shenhua sub-bituminous coal and Huolinhe lignite and their 800
°C chars were studied by using a uniaxial compression test. The
results showed that their mechanical properties such as effective
elastic modulus, crushing force, crushing energy, and tensile stress
fitted well with Weibull and logistic distributions. Statistically,
the strength of both kinds of coal chars was higher than that of raw
coal. The distribution of mechanical parameters of lignite and its
char particles was more dispersed and had a wider range of variation.
The brittleness index composed of compressive stiffness and breakage
energy could well describe the particle failure mode, and the brittleness
of sub-bituminous coal was greater than that of lignite. Image-based
particle size distribution analysis revealed that samples with higher
brittleness and strength would produce less volume of fragments conforming
to fractal distribution during the crushing process. This indicates
that the crushing process of coal particles with brittleness and high
strength is relatively fast and their cracks are not fully developed.
Natural sand samples collected from bedload or suspension transport can be too small to be sieved. However, related transported mass to sediment size is crucial to calibrate sediment transport models. Image analysis technique can be an easy and cheap alternative. The present study proposes a general law valid for natural sand grains and small gravels that statistically relates elongation to flatness of particles and gives after some assumptions on grain shape and orientation of grains at the sieve mesh passage, the closest distribution of mass to sieving technique from images of grains given by a flatbed scanner. The proposed model is based on the hypothesis of an ellipsoidal grain shape and a preferential grain crossing aligned with the sieve diagonal. Any sand either homogeneous or heterogeneous from various origins (fluvial, marine and quarry) can be analysed directly without any further need for calibration.
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