Estimating relative density of sand using particle configuration parameters from soil assembly image

Area of Science:

• Geotechnical Engineering
• Soil Mechanics
• Image Analysis

Background:

• Estimating sand relative density (D_R) is crucial for geotechnical applications.
• Traditional methods can be time-consuming and require specialized equipment.
• Image analysis offers a potential non-destructive and efficient alternative.

Purpose of the Study:

• To develop a novel image-based approach for estimating sand relative density (D_R).
• To investigate the relationship between particle configuration parameters and D_R.
• To establish a unified correlation model for D_R estimation using image analysis.

Main Methods:

• Acquired soil images depicting particles in group configuration at various D_R.
• Analyzed particle diameter (d), perimeter (p), and total perimeter (p_tot) from images.
• Introduced and evaluated the number of particles (NoP) as a new indicator for volume characteristics.

Main Results:

• Found that as D_R increased, d and p decreased, while p_tot remained similar.
• Established a linear correlation between p_tot and NoP, indicating their relationship with D_R.
• Developed and validated a unified correlation model using combined p_tot and NoP for D_R estimation.

Conclusions:

• The proposed image-based method effectively estimates sand relative density (D_R).
• The combined parameters of p_tot and NoP provide a robust basis for D_R prediction.
• The method demonstrates validity and efficacy across different sand types.