Scaling law modeling artificial soil-to-bulldozer blade interaction

Bulldozers are one of the major off-road machine systems for cutting and transporting granular materials during earthmoving operations. With the growing demand for energy-efficient and accelerated optimization design cycles and automated earthmoving processes, researchers and engineers are exploring methods to model the soil-to-bulldozer interaction. This study proposes a similitude scaling law for the soil and scaled blade systems, providing an alternative approach to costly and time-consuming field-based design verification and validation for product engineering of Ground-Engaging Tools (GETs). In this soil bin study, we examined the interaction between scaled bulldozer blades and cohesive-frictional artificial soil, aiming to establish scaling laws of geometrically scaled blade ratio to two blade performance responses, soil reaction forces and soil mass. A randomized complete block design with five replications was conducted in a soil bin using five 3D printed geometric scales of the blade, λ = 1/8, λ = 1/9, λ = 1/11, λ = 1/13, and λ = 1/15, with λ = 1 representing the full-scale geometry of a Caterpillar D3K2 XL bulldozer blade. Blade soil cutting forces were measured using a load cell instrumented blade dynamometer carriage on a cohesive-frictional artificial soil in the bin. Each scaled blade traveled at a constant speed of 213 mm/s and the tool depth was set to 30 % of the blade height. After reaching full load, the cut soil mass and pile dimensions (height, width, and rupture length) above the undisturbed soil were also measured. A scaling law model was established between soil horizontal reaction forces and the five geometric blade scale ratios with a high coefficient of determination, R², of 0.9898. Similarly, the scaling law (R² = 0.9951) was established between the five geometric scales and soil mass. The findings demonstrate that a scaling law model can be used for predicting the soil horizontal reaction force and soil load. The scaling law can be utilized for optimizing energy and productivity, enhancing GET product design optimization, and developing algorithms for energy-efficient automation of earthmoving processes.