Review of Discrete Element Method Simulations of Soil Tillage and Furrow Opening

Author:

Aikins Kojo Atta12ORCID,Ucgul Mustafa34ORCID,Barr James B.5,Awuah Emmanuel6ORCID,Antille Diogenes L.27ORCID,Jensen Troy A.2,Desbiolles Jacky M. A.4

Affiliation:

1. Department of Agricultural and Biosystems Engineering, Kwame Nkrumah University of Science and Technology, PMB, Kumasi, Ghana

2. Centre for Agricultural Engineering, University of Southern Queensland, Toowoomba, QLD 4350, Australia

3. Faculty of Science and Engineering, Southern Cross University, Lismore, NSW 2480, Australia

4. Agricultural Machinery R&D Centre, STEM, University of South Australia, Adelaide, SA 5000, Australia

5. Seed Terminator, 23 Aldershot Rd., Lonsdale, SA 5160, Australia

6. College of Engineering, Nanjing Agricultural University, No. 40 Dianjiangtai, Pukou District, Nanjing 210095, China

7. CSIRO Agriculture and Food, Black Mountain Science and Innovation Precinct, Canberra, ACT 2601, Australia

Abstract

In agricultural machinery design and optimization, the discrete element method (DEM) has played a major role due to its ability to speed up the design and manufacturing process by reducing multiple prototyping, testing, and evaluation under experimental conditions. In the field of soil dynamics, DEM has been mainly applied in the design and optimization of soil-engaging tools, especially tillage tools and furrow openers. This numerical method is able to capture the dynamic and bulk behaviour of soils and soil–tool interactions. This review focused on the various aspects of the application of DEM in the simulation of tillage and furrow opening for tool design optimization. Different contact models, particle sizes and shapes, and calibration techniques for determining input parameters for tillage and furrow opening research have been reviewed. Discrete element method predictions of furrow profiles, disturbed soil surface profiles, soil failure, loosening, disturbance parameters, reaction forces, and the various types of soils modelled with DEM have also been highlighted. This pool of information consolidates existing working approaches used in prior studies and helps to identify knowledge gaps which, if addressed, will advance the current soil dynamics modelling capability.

Funder

CLAAS Stiftung, Harsewinkel, Germany

Publisher

MDPI AG

Subject

Plant Science,Agronomy and Crop Science,Food Science

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