scholarly journals FIT Method for Calculating Soil Particle Size Distribution from Particle Density and Settling Time Data

2006 ◽  
Vol 55 (1) ◽  
pp. 295-304 ◽  
Author(s):  
Balázs Kovács ◽  
I. Czinkota ◽  
L. Tolner ◽  
Gy. Czinkota

Particle size distribution (PSD) is one of the most important fundamental physical properties of soils, as it determines their physical, chemical, mechanical, geotechnical, moreover environmental behaviour. Although the measurement of PSD with different techniques is commonly performed in soil laboratories, their automation and continuous PSD curve generation have not been solved yet.  However, there are some physical principles, various sensors and different data storing methods for measuring the density-time function. In the present paper a possible solution is introduced for the measurement of the soil particle density database as a function of settling time. The equipment used for this purpose is an areometer that is widely used e.g. for determining the sugar content of must, or the alcohol content of distilled spirits, etc. The device is equipped with patent pending capacitive sensors on the neck of the areometer. It measures the changes in the water levels nearby the neck of the areometer in 1 μm units with <10 μm accuracy. The typical water level changes are 3-5 cm, which makes possible a very accurate determination of particle density changes due to settling in particle size analysis. The measured signals are stored in the equipment's memory and can be downloaded to the controller computer via a modified USB port. Data evaluation can be carried out online or later. The large number of measured data points led to the introduction of a new evaluation method, the Method of FInite Tangents or shortly the “FIT Method”. The dispersed soil particle system is considered as the aggregation of many mono-disperse systems. From this it follows that the measured density-time function can be divided into grain size fractions with tangent lines drawn to finite, but optional points. These tangent lines are suitable for calculating the settling speed of a given fraction, as the changing speed of density is equal to the multiplication of settling speed and mass of the given grain size fraction. The settling speed of all fractions is calculable by using the Stokes law, so the mass of all of the floating fraction can be calculated. Because the soil suspension is a poly-disperse system, the measured density decrease can be considered as an integration of finite mono-disperse systems. From this, it follows that it can be interpreted as the sum of linear density vs. time functions. If the mass of each grain size fraction is known, the particle size distribution is calculable. The method is relatively easily programmed and the intervals of grain size fractions are freely adjustable, so with this program almost all types of particle size distribution are calculable, not only those being uniform. Using the appropriate controller and evaluation program, soil particle size distribution can be calculated immediately after downloading the measured data. This technique does not need more sample preparation than past methods. The automated reading lessens the manpower required for performing the measurement - which also reduces human error sources - and provides very detailed PSD data that has advantages, among others, like revealing multi-modality in the particle-size distribution.

2020 ◽  
Author(s):  
Zhongyuan Wang ◽  
Yongqiu Wu

&lt;p&gt;Desert (sandland) margin is the transition region from inner aeolian landforms &amp;#160;to other landforms outside, while it remains as an ambiguous conception in previous researches. Accurately delineating its boundary line and realizing the characteristics of the particle size distribution of surface aeolian sands in margin area can help us understand the formation of modern boundary of desert (sandland). In this research, the criteria of identification of the boundary were proposed and the boundary line was extracted quantitative. Then systematic analyses of grain size of aeolian sand in margin were conducted. Together with the morphologic type, activity and the geomorphological location of collected dunes, the factors controlled the particle-size distributions had also been analyzed. The results reveal the following: (1) There is notable difference in grain size characteristics of aeolian sand between inside and outside of Mu Us sandland. The outside samples are finer than inside. Additionally, the aeolian sand covering on loess is always more poorly sorted and with different grain size fraction composition. (2) The controlling factors on particle size distribution are different in different downwind margins. In southwest margin, the grain size characteristics of aeolian sand are influenced by time and degree of stabilization of sampled dune and locally topographic relief; From the estuary of Lu River to Yuxi River, sediment transport by wind is affected by topographic obstacles including both valley and loess gully. Meanwhile, the small dunefields in Loess Plateau outside of Mu Us sandland may originate from a local alluvial source; In northeast downwind margin, the grain size characteristics of aeolian sand covering on loess are determined by regional gully erosion after its deposition.&lt;/p&gt;


Water ◽  
2020 ◽  
Vol 12 (5) ◽  
pp. 1232
Author(s):  
Dušan Igaz ◽  
Elena Aydin ◽  
Miroslava Šinkovičová ◽  
Vladimír Šimanský ◽  
Andrej Tall ◽  
...  

The paper presents the comparison of soil particle size distribution determined by standard pipette method and laser diffraction. Based on the obtained results (542 soil samples from 271 sites located in the Nitra, Váh and Hron River basins), regression models were calculated to convert the results of the particle size distribution by laser diffraction to pipette method. Considering one of the most common soil texture classification systems used in Slovakia (according to Novák), the emphasis was placed on the determination accuracy of particle size fraction <0.01 mm. Analysette22 MicroTec plus and Mastersizer2000 devices were used for laser diffraction. Polynomial regression model resulted in the best approximation of measurements by laser diffraction to values obtained by pipette method. In the case of particle size fraction <0.01 mm, the differences between the measured values by pipette method and both laser analyzers ranged in average from 3% up to 9% and from 2% up to 11% in the case of Analysette22 and Mastersizer2000, respectively. After correction, the differences decreased to average 3.28% (Analysette22) and 2.24% (Mastersizer2000) in comparison with pipette method. After recalculation of the data, laser diffraction can be used alongside the sedimentation methods.


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