Calibration and Experimental Validation of Discrete Element Parameters of Fritillariae Thunbergii Bulbus
Source abstract
Abstract
The development of slicing equipment for Fritillariae Thunbergii Bulbus (FTB) has been constrained by the absence of precise and reliable simulation model parameters, which has hindered the optimization of structural design through simulation techniques. Taking FTB as the research object, this study aims to resolve this issue by conducting the calibration and experimental validation of the discrete element parameters for FTB. Both intrinsic and contact parameters were obtained through physical experiments, on the basis of which a discrete element model for FTB was established by using the Hertz–Mindlin with bonding model. To validate the calibrated bonding parameters of this model, the maximum shear force was selected as the evaluation index. Significant influencing factors were identified and analyzed through a single-factor test, a two-level factorial test, and the steepest ascent method. Response surface methodology was then applied for experimental design and parameter optimization. Finally, shear and compression tests were conducted to verify the accuracy of calibrated parameters. The results show that the mechanical properties of FTB are significantly affected by the normal stiffness per unit area, the tangential stiffness per unit area, and the bonding radius, with optimal values of 1.438 × 108 N·m−3, 0.447 × 108 N·m−3, and 1.362 mm, respectively. The relative errors in the shear and compression tests were all within 5.18%. The maximum error between the simulated and measured maximum shear force under three different types of blades was less than 5.11%. The percentages of the average shear force of the oblique blade were reduced by 52.23% and 29.55% compared with the flat and arc blades, respectively, while the force variation trends for FTB remained consistent. These findings confirm the reliability of the simulation parameters and establish a theoretical basis for optimizing the structural design of slicing equipment for FTB.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Advanced Surface Polishing Techniques · Vibration and Dynamic Analysis · Polysaccharides and Plant Cell Walls
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Institute of Agricultural Equipment, Zhejiang Academy of Agricultural Sciences, Hangzhou 310021, China
Key Laboratory of Agricultural Equipment for Hilly and Mountainous Areas in Southeastern China (Co-Construction by Ministry and Province), Ministry of Agriculture and Rural Affairs, Hangzhou 310021, China
College of Optical, Mechanical and Electrical Engineering, Zhejiang A&F University, Hangzhou 311300, China
College of Engineering and Technology, Southwest University, Chongqing 400715, China
Funding
Key R&D Program of ZheJiang Province, China · National Natural Science Foundation of China
References (45)
Show source-provided references
1. Design and Experimental Study of Chain Separation Device for Fritillaria thunbergii Harvester
2. Song, J. (2023). Low Loss Screening Mechanism of Drum Screen of Fritillaria Ussuriensis Maxim Harvester and Its Parameter Optimization Test. [Ph.D. Thesis, Heilongjiang Bayi Agricultural University].
3. Simulation and Experimental Research of Vibrating Screening Process of Fritillary Harvester
4. Wang, M. (2017). Optimization Design and Test of Key Components of 4B-1200 Flat Fritillary Harvester. [Ph.D. Thesis, Heilongjiang Bayi Agricultural University].
5. Application of Discrete Element Method in Agricultural Engineering
6. Critical Review of Applications of Discrete Element Method in Agricultural Engineering
7. Parameters and contact models for DEM simulations of agricultural granular materials: A review10.1016/j.biosystemseng.2016.02.017 ↗
8. Zhang, L.W. (2021). 3D Reconstruction Technology of Blueberry Fruit and Its Discrete Element Parameter Calibration. [Ph.D. Thesis, Northeast Forestry University].
9. Li, M., He, X., Zhu, G., Liu, J., Gou, K., and Wang, X. (2024). Modeling and Parameter Calibration of Morchella Seed Based on Discrete Element Method. Appl. Sci., 14.10.3390/app142311134 ↗
10. Jiang, J.Y. (2023). Design of Bionic Tillage Tools for Tea Plantation Based on Discrete Element Method. [Ph.D. Thesis, Zhejiang A&F University].
11. Parameter calibration of discrete element simulation model for Panax notoginseng planting soil
12. Ma, X.T., You, Y., Yang, D.Q., Wang, D.C., Hui, Y.T., Li, D.Y., and Wu, H.H. (2024). Calibration and Verification of Discrete Element Parameters of Surface Soil in Camellia Oleifera Forest. J. Agron., 14.10.3390/agronomy14051011 ↗
13. Li, Y.Y., Fan, J.L., Hu, Z.C., Luo, W.W., Yang, H.G., Shi, L.L., and Wu, F. (2022). Calibration of Discrete Element Model Parameters of Soil around Tubers during Potato Harvesting Period. Agriculture, 12.10.3390/agriculture12091475 ↗
14. Discrete Element Simulation Parameter Calibration and Experiment of Corn Straw-Cow Manure Mixture
15. Discrete Element Simulation Parameters Calibration for Xinjiang Cotton Straw
16. Parameters calibration of discrete element model for alfalfa straw compression simulation
17. Maize straw cutting process modelling and parameter calibration based on discrete element method10.35633/inmateh-63-47 ↗
18. Calibration and experimental verification of discrete element parameters of oil sunflower seeds
19. Measurement of physical contact parameters and discrete element simulation calibration of lettuce seeds
20. Zhao, H., Li, K.T., Qin, Z.Y., Wang, S.S., Wang, X.Z., and Sun, F.Y. (2024). Discrete Element Model of Oil Peony Seeds and the Calibration of Its Parameters. Agriculture, 14.10.3390/agriculture14071092 ↗
21. Virtual parameter calibration of pod pepper seeds based on discrete element simulation10.1016/j.heliyon.2024.e31686 ↗
22. Calibrating and simulating contact parameters of the discrete element for apple particles
23. Calibration and experiments of the discrete element simulation parameters for water chestnut10.15302/J-SSCAE-2022.05.006 ↗
24. Calibration and Experiment of Discrete Element Parameters of Panax notoginseng Stem
25. Calibration and experiments for discrete element simulation parameters of peanut seed particles
26. Calibration and Verification of Bonding Parameters of Banana Straw Simulation Model Based on Discrete Element Method
27. Effect of grain moisture content on physical, mechanical, and bulk dynamic behaviour of maize10.1016/j.biosystemseng.2020.04.012 ↗
28. Full-process mechanized production mode of Fritillaria in Zhejiang hilly and mountainous areas
29. Chen, S., Li, Y., Wei, B., Shi, M., Zou, X., and Huang, X. (2025). Establishment of a Discrete-Element Model and Verification of a Seeder Bench Experiment for Sesbania Seeds. Appl. Sci., 15.10.3390/app15094710 ↗
30. Yu, Y., Ren, S., Li, J., Chang, J., Yu, S., Sun, C., and Chen, T. (2022). Calibration and Testing of Discrete Element Modeling Parameters for Fresh Goji Berries. Appl. Sci., 12.10.3390/app122211629 ↗
31. Experimental study on the coefficient of restitution of grain against block interfaces for natural and engineered materials
32. Determination of three-dimensional collision restitution coefficient of oil sunflower grain by high-speed photography
33. Research progress of the restitution coefficients of collision of particles in agricultural and food fields
34. Solution to indeterminate multipoint impact with frictional contact using constraints10.1007/s11044-012-9307-x ↗
35. Simultaneous oblique impacts and contacts in multibody systems with friction10.1007/s11044-009-9182-2 ↗
36. Influence of non-spherical shape approximation on DEM simulation accuracy by multi-sphere method10.1016/j.powtec.2018.03.030 ↗
37. Hu, G.M. (2010). Discrete Element Method Analysis and Simulation of Particle Systems: Introduction to Industrial Applications of Discrete Element Method and EDEM Software, Wuhan University of Technology Press.
38. Calibration and Verification of Flexible Rice Straw Model by Discrete Element Method
39. Parameters Calibration of Discrete Element Model of Fodder Rape Crop Harvest in Bolting Stage
40. Korelsky, T., Overmyer, S., and Webber, F. (2025, June 24). Design Expert: A Knowledge-Based Tool for Developing System-Wide Properties. Available online: https://www.academia.edu/69802089/DesignExpert_A_Knowledge_Based_Tool_for_Developing_System_Wide_Properties.
41. Ren, J.H., Wu, T., Mo, W.Y.J., Li, K., Hu, P., Xu, F.Y., and Liu, Q.T. (2022). Discrete Element Simulation Modeling Method and Parameters Calibration of Sugarcane Leaves. Agronomy, 12.10.3390/agronomy12081796 ↗
42. Fan, G.J., Wang, S.Y., Shi, W.J., Gong, Z.F., and Gao, M. (2022). Simulation Parameter Calibration and Test of Typical Pear Varieties Based on Discrete Element Method. Agronomy, 12.10.3390/agronomy12071720 ↗
43. Calibration and analysis of discrete element simulation parameters of Chinese cabbage seeds10.1371/journal.pone.0270415 ↗
44. Li, D.D., Wang, R.Y., Zhu, Y.P., Chen, J.N., Zhang, G.F., and Wu, C.Y. (2024). Calibration of Simulation Parameters for Fresh Tea Leaves Based on the Discrete Element Method. Agriculture, 14.10.3390/agriculture14010148 ↗
45. Determination of melon seed physical parameters and calibration of discrete element simulation parameters10.1371/journal.pone.0300516 ↗