Prediction of precise subsoiling based on analytical method, discrete element simulation and experimental data from...

Area of Science:

• Agricultural Engineering
• Soil Mechanics
• Computational Modeling

Background:

• Deep tillage operations like subsoiling can cause significant soil structure deformation.
• Accurate prediction of cutting forces and soil profile changes is crucial for optimizing tillage practices.
• Existing analytical models (AM) and Discrete Element Method (DEM) require further validation for precision subsoiling.

Purpose of the Study:

• To compare the predictive accuracy of an analytical model (AM) and the Discrete Element Method (DEM) for subsoiling.
• To understand the cutting forces and soil profile alterations induced by a subsoiler.
• To validate computational models against experimental data for precision agriculture.

Main Methods:

• Subsoiling simulations were performed using both an analytical model (AM) and the Discrete Element Method (DEM).
• The AM incorporated modified McKyes and Willat and Willis equations for force and profile prediction.
• DEM simulations included the elastoplastic behavior of soil; both models were validated with experimental soil bin data.
• Taguchi method was employed for experimental design.

Main Results:

• The Discrete Element Method (DEM) demonstrated superior predictive performance with a regression coefficient of 0.984.
• The analytical model (AM) achieved a lower regression coefficient of 0.957.
• Both models' results were statistically significant (p < 0.05), with DEM showing better agreement with experimental data.

Conclusions:

• The Discrete Element Method (DEM) is a highly effective and user-friendly tool for developing precision subsoiling models.
• DEM provides more accurate predictions of cutting forces and soil profile changes compared to traditional AM.
• This study enhances understanding of deep tillage impacts and supports the development of precision agriculture techniques.