Soil Particle Size Analysis by Laser Diffractometry: Result Comparison with Pipette Method

World Multidisciplinary Civil Engineering-Architecture-Urban Planning Symposium - WMCAUS

土木建筑工程

Šinkoviová, Miroslava^1 ; Igaz, Duan^1 ; Kondrlová, Elena^1 ; Jaroová, Miriam^1

Slovak University of Agriculture in Nitra, Faculty of Horticulture and Landscape Engineering, Department of Biometeorology and Hydrology, Hospodárska 7, Nitra

949 76, Slovakia^1

关键词: Grain size distribution;    Laser diffraction method;    Polynomial regression;    Regression coefficient;    Regression relationship;    Sedimentation velocities;    Soil physical property;    Technical advancement;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/245/7/072025/pdf
DOI  :  10.1088/1757-899X/245/7/072025

学科分类：土木及结构工程学

来源: IOP

【 摘 要 】

Soil texture as the basic soil physical property provides a basic information on the soil grain size distribution as well as grain size fraction representation. Currently, there are several methods of particle dimension measurement available that are based on different physical principles. Pipette method based on the different sedimentation velocity of particles with different diameter is considered to be one of the standard methods of individual grain size fraction distribution determination. Following the technical advancement, optical methods such as laser diffraction can be also used nowadays for grain size distribution determination in the soil. According to the literature review of domestic as well as international sources related to this topic, it is obvious that the results obtained by laser diffractometry do not correspond with the results obtained by pipette method. The main aim of this paper was to analyse 132 samples of medium fine soil, taken from the Nitra River catchment in Slovakia, from depths of 15-20 cm and 40-45 cm, respectively, using laser analysers: ANALYSETTE 22 MicroTec plus (Fritsch GmbH) and Mastersizer 2000 (Malvern Instruments Ltd). The results obtained by laser diffractometry were compared with pipette method and the regression relationships using linear, exponential, power and polynomial trend were derived. Regressions with the three highest regression coefficients (R2) were further investigated. The fit with the highest tightness was observed for the polynomial regression. In view of the results obtained, we recommend using the estimate of the representation of the clay fraction (