5:15 PM - 7:15 PM
[SMP29-P08] Development of a method for validation a soil particle morphology distribution using an automated particle image analysis and numerical simulation.
Keywords:Particle Size, Particle Shape, Image Analysis
[Introduction]
Soil particle morphology, including shape and size, plays a crucial role in predicting various bulk characteristics and understanding the mechanical behavior of the ground at a microscopic insight. To address this, Image Analysis (IA) employing manual microscopic techniques is commonly utilized to investigate particle behaviors. However, a primary challenge faced by conventional IA is nearly impossible to sufficient for evaluating a statistically significant number of particles. Realistic particle morphology in natural fields typically exhibits a broad distribution, and standards from ISO and JIS recommend the measurement of tens of thousands of particles to ensure accuracy.
Moreover, it is needed to consider the broad distribution width of grain size in natural soils that is suggested following a lognormal distribution with non-uniform. To evaluate this, it is needed to integrated particle characterizing platform with sampling, observation and analysis. Recent advancements in computer technology have achieved development for an automated particle image analysis (APIA) approach utilizing digital imaging technology with sampling units. This technology enables the acquisition and calculation of binarized (2D) particle projection images for each individual particle from a dataset of over ten thousand particles within a few hours. These advancements allowed for the calculation of various morphological parameters through graphical comparisons, including frequency curves and cumulant curves. However, despite recent progress, there remains a limited determination method for verification enough particles to determine realistic distribution across various aspects. Our research group has consistently focused on development of verification of particle sampling size in IA's particle count. This report will discuss the shape aspect investigation by combined such as a statistical modeling, simulation and evaluate function investigation used by APIA acquired data. By the this study expected to enhance our understanding of particle distribution on various model.
[Method]
Various model sand (Silica sand, Almina, Cray and so on) were used as model samples. APIA analyses were conducted on a Morphologi 4 as automated image analysis system (Malvern Panalytical Instruments, Worcestershire, UK). Sample was subsequently dispersed with an SDU using a short duration pulse of compressed air. Measurements were collected automatically using standard operating procedures (SOPs), which clearly define the software and hardware settings used during the measurement process. The measurement sample was dispersed on a glass plate, which was used as a sample carrier to minimize environmental exposure within the enclosed sample chamber unit.
A computer simulation was carried out mainly Scilab platform with implemented own programming to calculate various numerical model, MS Excel used as supportive.
[Simulation Design]
In this study, we adopted a method of comparing the circularity obtained by directly changing the shape using a simulation with the measured value. Specifically, a polar coordinate function is used to give roughness to the end face with random numbers.
The number of vertices can be defined computationally. The particle shape distribution and each characteristic value were compared with the number of occurrences of figures as the number of particles. To minimize the influence of the particle size, the actual measurement data was verified by limiting the particle size.
Soil particle morphology, including shape and size, plays a crucial role in predicting various bulk characteristics and understanding the mechanical behavior of the ground at a microscopic insight. To address this, Image Analysis (IA) employing manual microscopic techniques is commonly utilized to investigate particle behaviors. However, a primary challenge faced by conventional IA is nearly impossible to sufficient for evaluating a statistically significant number of particles. Realistic particle morphology in natural fields typically exhibits a broad distribution, and standards from ISO and JIS recommend the measurement of tens of thousands of particles to ensure accuracy.
Moreover, it is needed to consider the broad distribution width of grain size in natural soils that is suggested following a lognormal distribution with non-uniform. To evaluate this, it is needed to integrated particle characterizing platform with sampling, observation and analysis. Recent advancements in computer technology have achieved development for an automated particle image analysis (APIA) approach utilizing digital imaging technology with sampling units. This technology enables the acquisition and calculation of binarized (2D) particle projection images for each individual particle from a dataset of over ten thousand particles within a few hours. These advancements allowed for the calculation of various morphological parameters through graphical comparisons, including frequency curves and cumulant curves. However, despite recent progress, there remains a limited determination method for verification enough particles to determine realistic distribution across various aspects. Our research group has consistently focused on development of verification of particle sampling size in IA's particle count. This report will discuss the shape aspect investigation by combined such as a statistical modeling, simulation and evaluate function investigation used by APIA acquired data. By the this study expected to enhance our understanding of particle distribution on various model.
[Method]
Various model sand (Silica sand, Almina, Cray and so on) were used as model samples. APIA analyses were conducted on a Morphologi 4 as automated image analysis system (Malvern Panalytical Instruments, Worcestershire, UK). Sample was subsequently dispersed with an SDU using a short duration pulse of compressed air. Measurements were collected automatically using standard operating procedures (SOPs), which clearly define the software and hardware settings used during the measurement process. The measurement sample was dispersed on a glass plate, which was used as a sample carrier to minimize environmental exposure within the enclosed sample chamber unit.
A computer simulation was carried out mainly Scilab platform with implemented own programming to calculate various numerical model, MS Excel used as supportive.
[Simulation Design]
In this study, we adopted a method of comparing the circularity obtained by directly changing the shape using a simulation with the measured value. Specifically, a polar coordinate function is used to give roughness to the end face with random numbers.
The number of vertices can be defined computationally. The particle shape distribution and each characteristic value were compared with the number of occurrences of figures as the number of particles. To minimize the influence of the particle size, the actual measurement data was verified by limiting the particle size.