https://doi.org/10.4081/jae.2023.1534
A review of the discrete element method/modelling in agricultural engineering
Published: 4 August 2023
Abstract Views: 1123
PDF: 599
HTML: 11
HTML: 11
Publisher's note
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.
Authors
With the development of high-performance computing technology, the number of scientific publications regarding computational modelling of applications with the Discrete Element Method/Modelling (DEM) approaches in agricultural engineering has risen in the past decades. Many granular materials, e.g. grains, fruits and soils in agricultural engineering are processed, and thus a better understanding of these granular media with DEM is of great significance in design and optimization of tools and process in agricultural engineering. In this review, the theory and background of DEM have been introduced. Some improved contact models discussed in the literature for accurately predicting the contact force between two interacting particles have been compared. Accurate approximation of irregular particle shapes is of great importance in DEM simulations to model real particles in agricultural engineering. New algorithms to approximate irregular particle shapes, e.g. overlapping multi-sphere approach, ellipsoid, etc., have been summarized. Some remarkable engineering applications of the improved numerical models developed and implemented in DEM are discussed. Finally, potential applications of DEM and some suggested further works are addressed in the last section of this review.
Aikins K.A., Ucgul M., Barr J.B., Jensen T.A., Antille D.L., Desbiolles J.M.A. 2021. Determination of discrete element model parameters for a cohesive soil and validation through narrow point opener performance analysis. Soil Tillage Res. 213:105123.
Atkinson K. 1991. An introduction to numerical analysis. John Wiley & sons.
Bangura K., Gong H., Deng R., Tao M., Liu C., Cai Y., Liao K., Liu J., Qi L. 2020. Simulation analysis of fertilizer discharge process using the discrete element method (DEM). PloS one 15:e0235872.
Binelo M.O., de Lima R.F., Khatchatourian O.A., Stránský J. 2019. Modelling of the drag force of agricultural seeds applied to the discrete element method. Biosyst. Eng. 178:168-75.
Blais B., Lassaigne M., Goniva C., Fradette L., Bertrand F. 2016. Development of an unresolved CFD-DEM model for the flow of viscous suspensions and its application to solid–liquid mixing. J Comput. Phys. 318:201-21.
Boac J.M., Casada M.E., Pordesimo L.O., Petingco M.C., Maghirang R.G., Harner III J.P. 2023. Evaluation of particle models of corn kernels for discrete element method simulation of shelled corn mass flow. Smart Agric. Technol. 4:100197.
Chen Z., Li Z., Xia H., Tong X. 2021. Performance optimization of the elliptically vibrating screen with a hybrid MACO-GBDT algorithm. Particuology 56:193-206.
Coetzee C.J. 2016. Calibration of the discrete element method and the effect of particle shape. Powder Technol. 297:50-70.
Cundall P.A., Strack O.D.L. 1979. A discrete numerical model for granular assemblies. Géotechnique 29:47-65.
DCS Computing. LIGGGHTS-DEM simulation engine, 2015. Available from: https://github.com/CFDEMproject/LIGGGHTS-PUBLIC
Goniva C., Kloss C., Deen N.G., Kuipers J.A.M., Pirker S. 2012. Influence of rolling friction on single spout fluidized bed simulation. Particuology 10:582-91.
Goodier J.N., Timoshenko S. 1970. Theory of elasticity. McGraw-Hill.
Horabik J., Molenda M. 2016. Parameters and contact models for DEM simulations of agricultural granular materials: A review. Biosyst. Eng. 147:206-25.
Huang S., Lu C., Li H., He J., Wang Q., Cao X., Gao Z., Wang Z., Lin H. 2023. Research on acoustic wave attenuation from the perspective of soil particle movement using the discrete element method. Comput. Electron. Agric. 207:107747.
Kafashan J., Wiacek J., Ramon H., Mouazen A.M. 2021. Modelling and simulation of fruit drop tests by discrete element method. Biosyst. Eng. 212:228-240.
Kroupa M., Klejch M., Vonka M., Kosek J. 2012. Discrete element modeling (DEM) of agglomeration of polymer particles. Procedia Eng. 42:58-69.
Kroupa M., Vonka M., Soos M., Kosek J. 2016. Utilizing the discrete element method for the modeling of viscosity in concentrated suspensions. Langmuir 32:8451-60.
Kuwabara G., Kono K. 1987. Restitution coefficient in a collision between two spheres. Jpn. J. Appl. Phys. 26:1230.
Li A., Jia F., Wang Y., Han Y., Chen P., Zhang J., Fei J., Shen S., Hao X., Feng W. 2022b. Numerical analysis of the rice transport uniformity in vertical friction rice mill based on discrete element method. Comput. Electron. Agric. 202:107398.
Li X., Du Y., Liu L., Mao E., Wu J., Zhang Y., Guo D. 2022a. A rapid prototyping method for crop models using the discrete element method. Comput. Electron. Agric. 203:107451.
Li Z., Tong X., Xia H., Yu L. 2016. A study of particles looseness in screening process of a linear vibrating screen. J. Vibroeng. 18:671-81.
Lu B., Ni X., Li S., Li K., Qi Q. 2022. Simulation and experimental study of a split high-speed precision seeding system. Agriculture 12:1037.
Lu C., Gao Z., Li H., He J., Wang Q., Wei X., Wang X., Jiang S., Xu J., He D, Li Y. 2023. An ellipsoid modelling method for discrete element simulation of wheat seeds. Biosyst. Eng. 226:1-15.
Lu M.M.G.R., McDowell G.R. 2007. The importance of modelling ballast particle shape in the discrete element method. Granul. Matter 9:69-80.
Luding S. 2008. Cohesive, frictional powders: contact models for tension. Granul. Matter 10:235-46.
Ma Z., Li Y., Xu L. 2015. Discrete-element method simulation of agricultural particles’ motion in variable-amplitude screen box. Comput. Electron. Agric. 118:92-9.
Ma Z., Li Y., Xu L., Chen J., Zhao Z., Tang Z. 2017. Dispersion and migration of agricultural particles in a variable-amplitude screen box based on the discrete element method. Comput. Electron. Agric. 142:173-80.
Marquez-Florez K., Arroyave-Tobón S., Linares J.M. 2023. From biological morphogenesis to engineering joint design: a bio-inspired algorithm. Mater. Des. 225:111466.
Norouzi H.R., Zarghami R., Sotudeh-Gharebagh R., Mostoufi N. 2016. Coupled CFD-DEM modeling: formulation, implementation and application to multiphase flows. John Wiley & Sons.
Pasha M., Hare C., Ghadiri M., Gunadi A., Piccione P.M. 2016. Effect of particle shape on flow in discrete element method simulation of a rotary batch seed coater. Powder Technol. 296:29-36.
Peng Z., Doroodchi E., Evans G. 2010. DEM simulation of aggregation of suspended nanoparticles. Powder Technol. 204:91-102.
Podlozhnyuk A., Pirker S., Kloss C. 2017. Efficient implementation of superquadric particles in discrete element method within an open-source framework. Comput. Part. Mech. 4:101-18.
Qi L., Chen Y., Sadek M. 2019. Simulations of soil flow properties using the discrete element method (DEM). Comput. Electron. Agric. 157:254-60.
Radvilaitė U., Ramírez-Gómez A., Kačianauskas R. 2016. Determining the shape of agricultural materials using spherical harmonics. Comput. Electron. Agric. 128:160-71.
Scheffler O.C., Coetzee C.J., Opara U.L. 2018. A discrete element model (DEM) for predicting apple damage during handling. Biosyst. Eng. 172:29-48.
Schramm M., Tekeste M.Z. 2022. Wheat straw direct shear simulation using discrete element method of fibrous bonded model. Biosyst. Eng. 213:1-12.
Seville J.P.K., Willett C.D., Knight P.C. 2000. Interparticle forces in fluidisation: a review. Powder Technol. 113:261-8.
Shaikh S.A., Li Y., Ma Z., Chandio F.A., Hussain Tunio M., Liang Z., Solangi K.A. 2021. Discrete element method (DEM) simulation of single grouser shoe-soil interaction at varied moisture contents. Comput. Electron. Agric. 191:106538.
Sharaby N., Doroshenko A., Butovchenko A. 2022. Modelling and verification of sesame seed particles using the discrete element method. J. Agric. Eng. 53.
Shi Y., Jiang Y., Wang X., Thuy N.T.D., Yu H. 2023. A mechanical model of single wheat straw with failure characteristics based on discrete element method. Biosyst. Eng. 230:1-15.
Siddique S.H., Hazell P.J., Wang H., Escobedo J.P., Ameri A.A.H. 2022. Lessons from nature: 3D printed bio-inspired porous structures for impact energy absorption–a review. Addit. Manuf. p103051.
Skeel R.D. 1993. Variable step size destabilizes the störmer/leapfrog/verlet method. BIT Numer. Math. 33:172-5.
Soltanbeigi B., Podlozhnyuk A., Papanicolopu-los S.-A., Kloss C., Pirker S., Ooi J.Y. 2018. DEM study of mechanical characteristics of multi-spherical and superquadric particles at micro and macro scales. Powder Technol. 329:288-303.
Song W., Xu F., Wu H., Xu Z. 2021. Investigating the skeleton behaviors of open-graded friction course using discrete element method. Powder Technol. 385:528-36.
Thornton C., Ning Z. 1998. A theoretical model for the stick/bounce behaviour of adhesive, elastic-plastic spheres. Powder Technol. 99:154-62.
Tian Y., Zeng Z., Gong H., Zhou Y., Qi L., Zhen W. 2023. Simulation of tensile behavior of tobacco leaf using the discrete element method (DEM). Comput. Electron. Agric. 205:107570.
Ucgul M., Saunders C. 2020. Simulation of tillage forces and furrow profile during soil-mouldboard plough interaction using discrete element modelling. Biosyst. Eng. 190:58-70.
Verlet L. 1967. Computer “experiments” on classical fluids. I. thermodynamical properties of Lennard-Jones molecules. Phys. Rev. 159:98.
Wang J., Xu C., Xu W., Fu Z., Wang Q., Tang H. 2022a. Discrete element method simulation of rice grain motion during discharge with an auger operated at various inclinations. Biosyst. Eng. 223:97-115.
Wang S., Yu Z., Aorigele, Zhang W. 2022b. Study on the modeling method of sunflower seed particles based on the discrete element method. Comput. Electron. Agric. 198:107012.
Wang X., Li Z., Tong X., Ge X. 2018. The influence of particle shape on screening: Case studies regarding DEM simulations. Eng. Comput.
Wang X., Zhang S., Pan H., Zheng Z., Huang Y., Zhu R. 2019. Effect of soil particle size on soil-subsoiler interactions using the discrete element method simulations. Biosyst. Eng. 182:138-50.
Wu X., Li Z., Xia H., Tong X. 2018. Vibration parameter optimization of a linear vibrating banana screen using DEM 3D simulation. J. Eng. Technol. Sci. 50.
Xia H., Li Z., Tong X. 2019. Modelling continuous materials using discrete element modelling: investigations on the effect of particle packing. Comput. Part. Mech. 6:823-36.
Xia H., Tong X., Li Z., Wu X. 2017. DEM-FEM coupling simulations of the interactions between particles and screen surface of vibrating screen. Int. J. Min. Miner. Eng. 8:250-63.
Xu T., Yu J., Yu Y., Wang Y. 2018. A modelling and verification approach for soybean seed particles using the discrete element method. Adv. Powder Technol. 29:3274-90.
Xu X., Zhang Y., Wang X., Fang J., Chen J., Li J. 2022. Searching superior crashworthiness performance by constructing variable thickness honeycombs with biomimetic cells. Int. J. Mech. Sci. 235:107718.
Zhang Y., Xu X., Fang J., Huang W., Wang J. 2022. Load characteristics of triangular honeycomb structures with self-similar hierarchical features. Eng. Struct. 257:114114.
Zhao W., Chen M., Xie J., Cao S., Wu A., Wang Z. 2023. Discrete element modeling and physical experiment re-search on the biomechanical properties of cotton stalk. Comput. Electron. Agric. 204:107502.
Zhou L., Yu J., Wang Y., Yan D., Yu Y. 2020. A study on the modelling method of maize-seed particles based on the discrete element method. Powder Technol. 374:353-76.
Zhu H.P., Zhou Z.Y., Yang R.Y., Yu A.B. 2008. Discrete particle simulation of particulate systems: a review of major applications and findings. Chem. Eng. Sci. 63:5728-70.
How to Cite
Guo, Q. and Xia, H. (2023) “A review of the discrete element method/modelling in agricultural engineering”, Journal of Agricultural Engineering, 54(4). doi: 10.4081/jae.2023.1534.
Copyright (c) 2023 the Author(s)
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
PAGEPress has chosen to apply the Creative Commons Attribution NonCommercial 4.0 International License (CC BY-NC 4.0) to all manuscripts to be published.
Similar Articles
- Xiong Bi, Hongchun Wang, Double-branch deep convolutional neural network-based rice leaf diseases recognition and classification , Journal of Agricultural Engineering: Vol. 55 No. 1 (2024)
- Volodymyr Bulgakov, Simone Pascuzzi, Semjons Ivanovs, Volodymyr Kuvachov, Yulia Postol, Francesco Santoro, Viktor Melnyk, Study of the steering of a wide span vehicle controlled by a local positioning system , Journal of Agricultural Engineering: Vol. 52 No. 3 (2021)
- Salahudin Zahedi, Kaka Shahedi, Mahmod Habibnejad Rawshan, Karim Solimani, Kourosh Dadkhah, Soil depth modelling using terrain analysis and satellite imagery: the case study of Qeshlaq mountainous watershed (Kurdistan, Iran) , Journal of Agricultural Engineering: Vol. 48 No. 3 (2017)
- Melis Inalpulat, Monitoring and multi-scenario simulation of agricultural land changes using Landsat imageries and future land use simulation model on coastal of Alanya , Journal of Agricultural Engineering: Vol. 55 No. 1 (2024)
- Giovanni Russo, Giuseppe Verdiani, The health risk of the agricultural production in potentially contaminated sites: an environmental-health risk analysis , Journal of Agricultural Engineering: Vol. 43 No. 3 (2012)
- Volodymyr Bulgakov, Valerii Adamchuk, Ladislav Nozdrovicky, Ivan Holovach, Theory of the interaction of flat sensing organ with the head of the sugar beet root , Journal of Agricultural Engineering: Vol. 48 No. 4 (2017)
- Daniela Lovarelli, Jacopo Bacenetti, Marco Fiala, A new tool for life cycle inventories of agricultural machinery operations , Journal of Agricultural Engineering: Vol. 47 No. 1 (2016)
- H. Kursat Celik, Ibrahim Akinci, Nuri Caglayan, Allan E.W. Rennie, Structural strength analysis of a rotary drum mower during harvesting , Journal of Agricultural Engineering: Vol. 55 No. 1 (2024)
- Thanaporn Singhpoo, Khwantri Saengprachatanarug, Seree Wongpichet, Jetsada Posom, Kanda Runapongsa Saikaew, Cassava stalk detection for a cassava harvesting robot based on YOLO v4 and Mask R-CNN , Journal of Agricultural Engineering: Vol. 54 No. 2 (2023)
- Timothy Denen Akpenpuun, Qazeem Opeyemi Ogunlowo, Wook-Ho Na, Prabhat Dutta, Anis Rabiu, Misbaudeen Aderemi Adesanya, Mohammadreza Nariman, Ezatullah Zakir, Hyeon Tae Kim, Hyun-Woo Lee, Dynamic neural network modeling of thermal environments of two adjacent single-span greenhouses with different thermal curtain positions , Journal of Agricultural Engineering: Vol. 55 No. 2 (2024)
<< < 1 2 3 4 5 6 7 8 9 10 > >>
You may also start an advanced similarity search for this article.
