Discrete Element Simulation Study of the Accumulation Characteristics for Rice Seeds with Different Moisture Content
Abstract
:1. Introduction
2. Materials and Methods
2.1. Parameter Determination
2.2. Discrete Element Numerical Simulation Scheme
2.3. Comparative Verification of Accumulate Test
3. Results and Discussion
3.1. Results of Comparative Verification for Accumulate Test
3.2. Velocity Distribution in the Accumulation Process of Rice Seeds
3.3. Analysis of the Mechanical Characteristics of Rice Seeds during Accumulation
3.4. Analysis of Mechanical Characteristics of Rice Seeds in Quasi-Static Accumulation Stage
4. Conclusions
- (1)
- According to the velocity characteristics of rice seeds, the accumulation process can be divided into four stages: substrate support forming stage, expansion accumulation stage, free accumulation stage and quasi-static accumulation stage. The average velocity of rice seeds with different moisture content showed a trend of increasing and then decreasing during the accumulation process. The force during the accumulation of seeds was the direct cause of its velocity change.
- (2)
- The average translational kinetic energy and the average rotational kinetic energy of rice seeds with different moisture content showed a trend of increasing and then decreasing, and the higher the moisture content, the greater the energy in the process of seed accumulation and the longer the kinetic energy decayed.
- (3)
- The force distribution of the “central depression” structure of the action of rice seeds with the moisture content of 10.23%, 14.09% and 17.85% on the horizontal surface. The higher the moisture content of rice seeds, the more likely the typical “ring force” structure appeared, and the more evenly the force on the horizontal surface was distributed in the circumferential direction.
- (4)
- When rice grains with 10.23% moisture content formed accumulation, the kinetic energy decay time was the shortest and the speed was the fastest; In the quasi-static accumulation stage, the force of rice grain with 21.77% water content on the horizontal plane is the most uniform, and it was the least prone to blockage when unloading at the accumulation center. This study provides a reference for the design and development of food processing equipment and safe storage equipment.
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
- Han, Y.; Zhao, D.; Chu, Y.; Zhen, J.; Li, G.; Zhao, H.; Jia, F. Breakage behaviour of single rice particles under compression and impact. Adv. Powder Technol. 2021, 32, 4635–4650. [Google Scholar] [CrossRef]
- Hesse, R.; Krull, F.; Antonyuk, S. Prediction of random packing density and flowability for non-spherical particles by deep convolutional neural networks and Discrete Element Method simulations. Powder Technol. 2021, 393, 559–581. [Google Scholar] [CrossRef]
- Horabik, J.; Molenda, M. Parameters and contact models for DEM simulations of agricultural granular materials: A review. Biosyst. Eng. 2016, 147, 206–225. [Google Scholar] [CrossRef]
- Zheng, Q.J.; Yu, A.B. Finite element investigation of the flow and stress patterns in conical hopper during discharge. Chem. Eng. Sci. 2015, 129, 49–57. [Google Scholar] [CrossRef]
- Tian, T.; Su, J.; Zhan, J.; Geng, S.; Xu, G.; Liu, X. Discrete and continuum modeling of granular flow in silo discharge. Particuology 2018, 36, 127–138. [Google Scholar] [CrossRef]
- Wan, J.; Wang, F.; Yang, G.; Zhang, S.; Wang, M.; Lin, P.; Yang, L. The influence of orifice shape on the flow rate: A DEM and experimental research in 3D hopper granular flows. Powder Technol. 2018, 335, 147–155. [Google Scholar] [CrossRef]
- Zaki, M.; Siraj, M.S. Study of a flat-bottomed cylindrical silo with different orifice shapes. Powder Technol. 2019, 354, 641–652. [Google Scholar] [CrossRef]
- Liu, H.; Han, Y.; Jia, F.; Xiao, Y.; Chen, H.; Bai, S.; Zhao, H. An experimental investigation on jamming and critical orifice size in the discharge of a two-dimensional silo with curved hopper. Adv. Powder Technol. 2021, 32, 88–98. [Google Scholar] [CrossRef]
- Xiao, Y.; Han, Y.; Jia, F.; Liu, H.; Li, G.; Chen, P.; Meng, X.; Bai, S. Research on clogging mechanisms of bulk materials flowing trough a bottleneck. Powder Technol. 2021, 381, 381–391. [Google Scholar] [CrossRef]
- Ahmadi, A.; Seyedi Hosseininia, E. An experimental investigation on stable arch formation in cohesionless granular materials using developed trapdoor test. Powder Technol. 2018, 330, 137–146. [Google Scholar] [CrossRef]
- Cheng, X.; Zhang, Q.; Shi, C.; Yan, X. Model for the prediction of grain density and pressure distribution in hopper-bottom silos. Biosyst. Eng. 2017, 163, 159–166. [Google Scholar] [CrossRef]
- Liu, K.; Xiao, Z.; Wang, S. Development of arching and silo wall pressure distribution in storage and discharging state based on discrete element analysis. Nongye Gongcheng Xuebao/Trans. Chin. Soc. Agric. Eng. 2018, 34, 277–285. [Google Scholar] [CrossRef]
- Horabik, J.; Molenda, M. Distribution of static pressure of seeds in a shallow model silo. Int. Agrophys. 2017, 31, 167–174. [Google Scholar] [CrossRef] [Green Version]
- Gallego, E.; Fuentes, J.M.; Wiącek, J.; Villar, J.R.; Ayuga, F. DEM analysis of the flow and friction of spherical particles in steel silos with corrugated walls. Powder Technol. 2019, 355, 425–437. [Google Scholar] [CrossRef]
- Shi, L.; Yang, X.; Zhao, W.; Sun, W.; Wang, G.; Sun, B. Investigation of interaction effect between static and rolling friction of corn kernels on repose formation by dem. Int. J. Agric. Biol. Eng. 2021, 14, 238–246. [Google Scholar] [CrossRef]
- Cao, R.H.; Cao, P.; Lin, H.; Zhang, K.; Tan, X.W. Particle flow analysis of direct shear tests on joints with different roughnesses. Yantu Lixue/Rock Soil Mech. 2013, 34, 456–463. [Google Scholar]
- Horabik, J.; Parafiniuk, P.; Molenda, M. Discrete element modelling study of force distribution in a 3D pile of spherical particles. Powder Technol. 2017, 312, 194–203. [Google Scholar] [CrossRef]
- Carlevaro, C.M.; Pugnaloni, L.A. Arches and contact forces in a granular pile. Eur. Phys. J. E 2012, 35, 44. [Google Scholar] [CrossRef] [Green Version]
- Berger, R.; Kloss, C.; Kohlmeyer, A.; Pirker, S. Hybrid parallelization of the LIGGGHTS open-source DEM code. Powder Technol. 2015, 278, 234–247. [Google Scholar] [CrossRef]
- Ma, Z.; Li, Y.; Xu, L. Discrete-element method simulation of agricultural particles’ motion in variable-amplitude screen box. Comput. Electron. Agric. 2015, 118, 92–99. [Google Scholar] [CrossRef]
- Wang, Z.; Liu, M. Semi-resolved CFD–DEM for thermal particulate flows with applications to fluidized beds. Int. J. Heat Mass Transf. 2020, 159, 120150. [Google Scholar] [CrossRef]
- Li, A.; Han, Y.; Jia, F.; Zhang, J.; Meng, X.; Chen, P.; Xiao, Y.; Zhao, H. Examination milling non-uniformity in friction rice mills using by discrete element method and experiment. Biosyst. Eng. 2021, 211, 247–259. [Google Scholar] [CrossRef]
- Wang, Q.; Mao, H.; Li, Q. Modelling and simulation of the grain threshing process based on the discrete element method. Comput. Electron. Agric. 2020, 178, 105790. [Google Scholar] [CrossRef]
- Markauskas, D.; Ramírez-Gómez, Á.; Kačianauskas, R.; Zdancevičius, E. Maize grain shape approaches for DEM modelling. Comput. Electron. Agric. 2015, 118, 247–258. [Google Scholar] [CrossRef]
- Bhushan, B.; Raigar, R.K. Influence of moisture content on engineering properties of two varieties of rice bean. J. Food Process Eng. 2020, 43, e13507. [Google Scholar] [CrossRef]
- Ebrahimifakhar, A.; Yuill, D. Inverse estimation of thermophysical properties and initial moisture content of cereal grains during deep-bed grain drying. Biosyst. Eng. 2020, 196, 97–111. [Google Scholar] [CrossRef]
- Liu, J.; Liu, Y.; Wang, A.; Dai, Z.; Wang, R.; Sun, H.; Strappe, P.; Zhou, Z. Characteristics of moisture migration and volatile compounds of rice stored under various storage conditions. J. Cereal Sci. 2021, 102, 103323. [Google Scholar] [CrossRef]
- Zhang, B.; Qian, C.; Jiao, J.; Ding, Z.; Zhang, Y.; Cui, H.; Liu, C.; Feng, L. Rice moisture content detection method based on dielectric properties and SPA-SVR algorithm. Nongye Gongcheng Xuebao/Trans. Chin. Soc. Agric. Eng. 2019, 35, 237–244. [Google Scholar] [CrossRef]
- Constant, M.; Coppin, N.; Dubois, F.; Artoni, R.; Lambrechts, J.; Legat, V. Numerical investigation of the density sorting of grains using water jigging. Powder Technol. 2021, 393, 705–721. [Google Scholar] [CrossRef]
- Yang, Z.; Sun, J.; Guo, Y. Effect of moisture content on compression mechanical properties and frictional characteristics of millet grain. Nongye Gongcheng Xuebao/Trans. Chin. Soc. Agric. Eng. 2015, 31, 253–260. [Google Scholar] [CrossRef]
- Jiang, M.; Chen, G.; Liu, C.; Liu, W.; Zhang, Z. Effects of moisture content on elastic-plastic properties of bulk wheat. Nongye Gongcheng Xuebao/Trans. Chin. Soc. Agric. Eng. 2020, 36, 245–251. [Google Scholar] [CrossRef]
- Wang, J.; Xu, C.; Xu, Y.; Wang, Z.; Qi, X.; Wang, J.; Zhou, W.; Tang, H.; Wang, Q. Influencing Factors Analysis and Simulation Calibration of Restitution Coefficient of Rice Grain. Appl. Sci. 2021, 11, 5884. [Google Scholar] [CrossRef]
- Qiu, S.; Yuan, X.; Guo, Y.; Cui, Q.; Wu, X.; Zhang, Z. Effects of variety and moisture content on mechanical properties of millet. Nongye Gongcheng Xuebao/Trans. Chin. Soc. Agric. Eng. 2019, 35, 322–326. [Google Scholar] [CrossRef]
- Wu, M.; Cong, J.; Yan, Q.; Zhu, T.; Peng, X.; Wang, Y. Calibration and experiments for discrete element simulation parameters of peanut seed particles. Nongye Gongcheng Xuebao/Trans. Chin. Soc. Agric. Eng. 2020, 36, 30–38. [Google Scholar] [CrossRef]
- Romuli, S.; Karaj, S.; Müller, J. Discrete element method simulation of the hulling process of Jatropha curcas L. fruits. Biosyst. Eng. 2017, 155, 55–67. [Google Scholar] [CrossRef]
- Horabik, J.; Wiącek, J.; Parafiniuk, P.; Bańda, M.; Kobyłka, R.; Stasiak, M.; Molenda, M. Calibration of discrete-element-method model parameters of bulk wheat for storage. Biosyst. Eng. 2020, 200, 298–314. [Google Scholar] [CrossRef]
- Wei, H.; Tang, X.; Ge, Y.; Li, M.; Saxén, H.; Yu, Y. Numerical and experimental studies of the effect of iron ore particle shape on repose angle and porosity of a heap. Powder Technol. 2019, 353, 526–534. [Google Scholar] [CrossRef]
- Zhao, L.L.; Zhao, Y.M.; Liu, C.S.; Li, J. Discrete element simulation of mechanical properties of wet granular pile. Wuli Xuebao/Acta Phys. Sin. 2014, 63, 034501. [Google Scholar] [CrossRef]
- Chan, Y.J.; Lu, W.C.; Lin, H.Y.; Wu, Z.R.; Liou, C.W.; Li, P.H. Effect of rice protein hydrolysates as an egg replacement on the physicochemical properties of flaky egg rolls. Foods 2020, 9, 245. [Google Scholar] [CrossRef] [Green Version]
Parameters | 10.23% Moisture Content | 14.09% Moisture Content | 17.85% Moisture Content | 21.77% Moisture Content | 26.41% Moisture Content | 29.22% Moisture Content |
---|---|---|---|---|---|---|
Density/kg·m−3 | 910 ± 6.93 e | 966 ± 7.00 d | 990 ± 9.54 cd | 1005 ± 7.94 c | 1197 ± 4.00 b | 1253 ± 32.19 a |
Modulus of elasticity/MPa | 252 ± 11.53 a | 220 ± 13.11 b | 211 ± 4.00 b | 208 ± 3.61 b | 170 ± 5.29 c | 102 ± 4.58 d |
Poisson’s ratio | 0.38 ± 0.01 a | 0.37 ± 0.00 ab | 0.35 ± 0.01 bc | 0.33 ± 0.01 c | 0.30 ± 0.01 d | 0.25 ± 0.03 e |
Static friction coefficient * | 0.28 ± 0.03 d | 0.30 ± 0.00 cd | 0.32 ± 0.02 bc | 0.32 ± 0.01 bc | 0.35 ± 0.01 b | 0.44 ± 0.03 a |
Dynamic friction coefficient * | 0.015 ± 0.001 c | 0.017 ± 0.001 c | 0.026 ± 0.003 b | 0.026 ± 0.002 b | 0.028 ± 0.001 ab | 0.031 ± 0.001 a |
Collision recovery coefficient * | 0.61 ± 0.02 a | 0.58 ± 0.01 ab | 0.56 ± 0.01 b | 0.43 ± 0.03 c | 0.38 ± 0.00 d | 0.30 ± 0.01 e |
Static friction coefficient ** | 0.44 ± 0.04 c | 0.48 ± 0.04 c | 0.51 ± 0.01 c | 0.56 ± 0.02 b | 0.60 ± 0.01 ab | 0.63 ±0.00 a |
Dynamic friction coefficient ** | 0.028 ± 0.002 d | 0.030 ± 0.001 d | 0.031 ± 0.000 d | 0.037 ± 0.002 c | 0.042 ± 0.001 b | 0.050 ± 0.003 a |
Collision recovery coefficient ** | 0.55 ± 0.03 a | 0.52 ± 0.02 a | 0.48 ± 0.01 b | 0.45 ± 0.00 b | 0.33 ± 0.02 c | 0.27 ± 0.03 d |
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. |
© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Wang, J.; Xu, C.; Qi, X.; Zhou, W.; Tang, H. Discrete Element Simulation Study of the Accumulation Characteristics for Rice Seeds with Different Moisture Content. Foods 2022, 11, 295. https://doi.org/10.3390/foods11030295
Wang J, Xu C, Qi X, Zhou W, Tang H. Discrete Element Simulation Study of the Accumulation Characteristics for Rice Seeds with Different Moisture Content. Foods. 2022; 11(3):295. https://doi.org/10.3390/foods11030295
Chicago/Turabian StyleWang, Jinwu, Changsu Xu, Xin Qi, Wenqi Zhou, and Han Tang. 2022. "Discrete Element Simulation Study of the Accumulation Characteristics for Rice Seeds with Different Moisture Content" Foods 11, no. 3: 295. https://doi.org/10.3390/foods11030295
APA StyleWang, J., Xu, C., Qi, X., Zhou, W., & Tang, H. (2022). Discrete Element Simulation Study of the Accumulation Characteristics for Rice Seeds with Different Moisture Content. Foods, 11(3), 295. https://doi.org/10.3390/foods11030295