Aplicaciones de la Segunda Ley de Newton en la Ingeniería Agropecuaria: revisión documental sobre dinámica de maquinaria y transporte de granos: Applications of Newton’s Second Law in Agricultural Engineering: a documentary review on machinery dynamics and grain transport

William Adolfo Valverde Lucio; Pedro Roberto Valdés Tamayo; Williams Ausberto Merchán García; Edgar Mauro Caicedo Álvarez

doi:10.33936/cognosis.v11i2.8613

Authors

William Adolfo Valverde Lucio Facultad de Ciencias Naturales y de la Agricultura, Universidad Estatal del Sur de Manabí, Ecuador. https://orcid.org/0009-0004-6033-558X
Pedro Roberto Valdés Tamayo Facultad de Ciencias Naturales y de la Agricultura, Universidad Estatal del Sur de Manabí, Ecuador. https://orcid.org/0000-0002-7264-0440
Williams Ausberto Merchán García Facultad de Ciencias Naturales y de la Agricultura, Universidad Estatal del Sur de Manabí, Ecuador. https://orcid.org/0000-0002-6910-5885
Edgar Mauro Caicedo Álvarez Facultad de Ciencias Naturales y de la Agricultura, Universidad Estatal del Sur de Manabí, Ecuador. https://orcid.org/0000-0002-6354-3307

DOI:

https://doi.org/10.33936/cognosis.v11i2.8613

Abstract

Newton’s Second Law remains one of the most important foundations for understanding the dynamic behavior of numerous processes involved in agricultural engineering. Based on this premise, the present study aimed to analyze the main scientific contributions related to agricultural machinery dynamics and the behavior of granular materials during transport and storage operations. The research was conducted through a documentary review based on the consultation of internationally recognized academic databases, including Scopus, Web of Science, ScienceDirect, MDPI, and Google Scholar. The search focused primarily on publications from 2015 to 2025, complemented by classical reference works considered essential for the theoretical and methodological foundation of the topic. The selected documents were organized into categories related to agricultural machinery dynamics, granular materials, and numerical simulation techniques based on DEM, CFD, FEM, and MBD approaches. The analysis revealed a strong predominance of the Discrete Element Method in the study of granular materials, as well as a progressive increase in multiphysics approaches aimed at integrating particles, fluids, and mechanical structures. Relevant applications were also identified in agricultural equipment optimization, operational stability improvement, and the reduction of mechanical grain damage during handling processes. The findings suggest that the combination of classical dynamics principles and modern simulation tools represents a promising alternative for the development of more efficient and sustainable agro-industrial systems.

KEYWORDS: dynamics; agricultural engineering; agricultural machinery; granular materials; numerical simulation.

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References

Chen, Z., Wassgren, C., & Ambrose, R. P. K. (2022). Development and validation of a DEM model for predicting impact damage of maize kernels. Biosystems Engineering, 224, 16–33. https://doi.org/10.1016/j.biosystemseng.2022.09.012

Coetzee, C. J. (2017). Calibration of the discrete element method. Powder Technology, 310, 104–142. https://doi.org/10.1016/j.powtec.2016.10.076

Delele, M. A., Tijskens, E., & Ramon, H. (2016). On modeling and simulation of particulate processes in agricultural engineering. Biosystems Engineering, 145, 123–135. https://doi.org/10.1016/j.biosystemseng.2016.03.001

Fielke, J. M. (2019). Soil–tool interaction modeling in agricultural engineering. Soil and Tillage Research, 189, 114–125. https://doi.org/10.1016/j.still.2019.02.009

Guo, Y., & Xia, J. (2023). Discrete element modeling of granular materials in agricultural engineering: A review. Computers and Electronics in Agriculture, 207, 107746. https://doi.org/10.1016/j.compag.2023.107746

Hibbeler, R. C. (2016). Engineering mechanics: Dynamics (14th ed.). Pearson.

Horabik, J., & Molenda, M. (2016). Parameters and contact models for DEM simulations of agricultural granular materials: A review. Powder Technology, 293, 157–168. https://doi.org/10.1016/j.powtec.2016.02.043

Hu, M., Gao, T., Dong, X., Tan, Q., Yi, C., Wu, F., & Bao, A. (2023). Simulation of soil-tool interaction using smoothed particle hydrodynamics (SPH). Soil and Tillage Research, 229, 105671. https://doi.org/10.1016/j.still.2023.105671

Kloss, C., Goniva, C., Hager, A., Amberger, S., & Pirker, S. (2012). Models, algorithms and validation for DEM and CFD–DEM. Progress in Computational Fluid Dynamics, 12(2–3), 140–152. https://doi.org/10.1504/PCFD.2012.047457

Li, Y., Xu, L., & Qiu, Z. (2022). Advances in DEM applications in agricultural machinery. Computers and Electronics in Agriculture, 198, 107085. https://doi.org/10.1016/j.compag.2022.107085

Maraveas, C., Tsigkas, N., & Bartzanas, T. (2025). Agricultural processes simulation using discrete element method: A review. Computers and Electronics in Agriculture, 237, 110733. https://doi.org/10.1016/j.compag.2025.110733

Meriam, J. L., & Kraige, L. G. (2018). Engineering mechanics: Dynamics (8th ed.). Wiley.

Nedderman, R. M. (2005). Statics and kinematics of granular materials. Cambridge University Press. https://doi.org/10.1017/CBO9780511617542

Orefice, L., Ketterhagen, W. R., & Hancock, B. C. (2020). Granular flow modeling: Current challenges. Powder Technology, 360, 104–117. https://doi.org/10.1016/j.powtec.2019.09.034

O'Sullivan, C. (2011). Particulate discrete element modelling: A geomechanics perspective. CRC Press. https://doi.org/10.1201/b10826

Shabana, A. A. (2013). Dynamics of multibody systems (4th ed.). Cambridge University Press. https://doi.org/10.1017/CBO9781107337219

Shigley, J. E., Mischke, C. R., & Budynas, R. G. (2020). Mechanical engineering design (11th ed.). McGraw-Hill.

Srivastava, A. K., Goering, C. E., Rohrbach, R. P., & Buckmaster, D. R. (2006). Engineering principles of agricultural machines (2nd ed.). ASABE.

Ucgul, M., Fielke, J. M., & Saunders, C. (2017). Three-dimensional discrete element modelling (DEM) of tillage: Accounting for soil cohesion and adhesion. Computers and Electronics in Agriculture, 134, 298–306. https://doi.org/10.1016/j.compag.2017.01.001

Wang, L., Zhang, S., & Chen, X. (2024). DEM simulation of grain damage during handling. Biosystems Engineering, 235, 45–58. https://doi.org/10.1016/j.biosystemseng.2024.01.005

Wong, J. Y. (2008). Theory of ground vehicles (4th ed.). Wiley. https://doi.org/10.1002/9780470172571

Yang, W., Li, Y., & Wang, X. (2023). Coupled DEM–FEM modeling of granular flow and structural interaction in silos. Computers & Structures, 279, 106969. https://doi.org/10.1016/j.compstruc.2023.106969

Zhang, B., Wang, J., Yang, X., & Chen, B. (2024). A DEM-MBD based method for regulating transfer flux in the supply and discharge of cane seed particles. Computers and Electronics in Agriculture, 218, 108732. https://doi.org/10.1016/j.compag.2024.108732

Zhao, Y., Gong, Z., & Zhang, R. (2021). Coupled DEM–CFD simulation of grain flow in storage and handling systems. Biosystems Engineering, 205, 1–15. https://doi.org/10.1016/j.biosystemseng.2021.03.005

Applications of Newton’s Second Law in Agricultural Engineering: a documentary review on machinery dynamics and grain transport