Optimized mouldboard design for efficient soil inversion using the discrete element method

TL;DR

This paper presents a modified mouldboard design optimized via discrete element method simulations, achieving up to 33% better soil inversion, reduced wear, and maintaining stress within safe limits, aiming to improve tillage efficiency.

Contribution

It introduces a novel cylindroid-shaped mouldboard profile optimized through simulation, demonstrating significant improvements in soil inversion and wear reduction over previous designs.

Findings

Up to 32.95% improvement in soil inversion efficiency.

Wear reduction of up to 23.7%.

Stress levels remain within safe material limits.

Abstract

The design of a mouldboard (MB) plough is critical for achieving efficient soil inversion, which directly impacts soil aeration, weed control, and overall agricultural productivity. In this work, a design modification of the cylindroid-shaped MB plough is proposed, focusing on optimizing its surface profile to enhance performance. The discrete element method is used to simulate the ploughing process and evaluate the performance of the modified plough profile. The modified plough profile is compared against a previously proposed design to assess its impact on soil inversion efficiency, wear reduction, and stress distribution. A novel methodology is introduced to evaluate the plough's performance in soil inversion. The modified design demonstrates superior soil inversion efficiency, with improvements of up to $32.95\%$ in the inversion index for different velocities. The modified design achieves a notable reduction in wear up to $23.7\%$, compared to the original design. Although a slight increase in stress is observed in the modified design due to higher forces, the induced stresses remain well within the permissible limits for the plough material. Overall, the findings highlight the advantages of the modified plough design, including enhanced soil inversion efficiency and reduced wear, underscoring its potential for improved performance in tillage applications. However, the current study is limited to simulation-based analysis without experimental or field validation. Future work will focus on full-scale physical experiments to validate the simulation outcomes and incorporate additional factors such as depth-dependent moisture, soil cohesion, and multi-factor wear models for improved predictive accuracy.