Parameter calibration and experimental verification of discrete element simulation model for Protaetia brevitarsis larvae bioconversion mixture
Keywords:
Protaetia brevitarsis larvae-frass mixture, repose angle, parameter calibration, discrete element, modelAbstract
To improve the survival rate of larvae during material separation after biotransformation of existing residual film mixtures of Protaetia brevitarsis larvae, this paper adopts the method of combining physical test and EDEM simulation test, and selects Hertz Mindlin with JKR contact model to calibrate the discrete element simulation contact parameters of the Protaetia brevitarsis larvae and the frass mixture. First, the cylinder lifting method was used to determine the actual repose angle of the mixture of larvae and frass. The collision recovery coefficients between larvae-frass and steel, static friction coefficient, kinetic friction coefficient and the collision recovery coefficient between larvae were measured through physical tests such as the inclined plane method. The Plackett-Burman test was then used to screen out the factors that have a significant impact on the repose angle: Poisson’s ratio of frass, frass-frass rolling friction coefficient, frass JKR surface energy, frass-larvae JKR surface energy. The optimal value intervals of four significant factors were determined based on the steepest climb test, Based on the Box-Behnken response surface analysis test, the second-order regression model between the repose angle and four significant factors was determined, and variance and interaction effects were analyzed. And with the actual repose angle as the goal, the significant factors were optimized and the optimal parameter combination of the four significant factors was determined. The simulation test of material repose angle and screening was carried out with the optimal parameter combination, and compared with the physical test. It was found that the maximum relative errors of the two tests were 1.48% and 3.79% respectively, indicating that the calibrated parameter values are true and reliable, It can provide a reference for the discrete element simulation of the transportation and separation of the Protaetia brevitarsis larvae-frass mixture. Key words: Protaetia brevitarsis larvae-frass mixture; repose angle; parameter calibration; discrete element; model DOI: 10.25165/j.ijabe.20241704.8707 Citation: Li Y Z, Xie J H, Zhang J, Yue Y, Meng Q H, Du Y K, et al. Parameter calibration and experimental verification of discrete element simulation model for Protaetia brevitarsis larvae bioconversion mixture. Int J Agric & Biol Eng, 2024; 17(4): 35–44.References
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[2] Zhou M D, Qin X H, Hou H, Yue Y B. Policy and present situation of pollution treatment of recycled plastic film in agricultural fields in Xinjiang. Environment and Sustainability, 2014; 39(5): 171–174. (in Chinese)
[3] Yi H F, Wang Y, Ma Y X, Wang J S. Study on bio transformation of nutrients in corn stalks by larvae of Protaetia brevitarsis. Special Economic Animals and Plants, 2021; 24(12): 3–5. (in Chinese)
[4] Yang C, Liu Y S, Xu X Y, Zhang J W. Analysis and evaluation of resource components of Protaetia brevitarsis (Lewis) Larvae. Journal of Shandong Agricultural University, 2014; 45(2): 166–170. (in Chinese)
[5] Li P P. Study on the conversion ability of livestock and poultry manure using potosa brevitarsis. Shandong Agricultural University, 2022. (in Chinese)
[6] Lai D Q, Wang Q L, Wu Y, Shu C L, Zhang Y, Liu C Q. Effect of Protaetia brevitarsis (Lewis) Larvae dung on development of pepper seedling stage under low temperature. Northern Horticulture, 2019; 431(8): 63–66. (in Chinese)
[7] Peng C W, Xu D J, He X, Tang Y H, Sun S L. Parameter calibration of discrete element simulation model for pig manure organic fertilizer treated with Hermetia illucen. Transactions of the CSAE, 2020; 36(17): 212–218. (in Chinese)
[8] Peng C W, Zhou T, Sun S L, Xie Y L, Wei Y. Calibration of parameters of black solider fly in discrete method simulation based on response angle of particle heap. Acta Agriculturae Zhejiangensis, 2022; 34(4): 814–823. (in Chinese)
[9] Sun J, Wang Y, MA Y, Tong J, Zhang Z. DEM simulation of bionic subsoilers (tillage depth>40 cm) with drag reduction and lower soil disturbance characteristics. Advances in Engineering Software, 2018; 119(5): 30–37.
[10] Barr J B, Ucgul M, Desbiolles J M A, Fielke J M. Simulating the effect of rake angle on narrow opener performance with the discrete element method. Biosystems Engineering, 2018; 171(1): 1–15.
[11] Zhu X H, Fu S K, Li X D, Wei Y Q, Zhao W. General method for discrete element parameters calibration of goat manure with different moisture contents. Transactions of the CSAM, 2022; 53(8): 34–41. (in Chinese)
[12] Tian X L, Cong X, Qi J T, Guo H, Li M, Fan X H. Parameter calibration of discrete element model for corn straw-soil mixture in black soil areas. Transactions of the CSAM, 2021; 52(10): 100–108, 242. (in Chinese)
[13] Yuan Q C, Xu L M, Xing J J, Duan Z Z, Ma S, Yu C C, Chen C. Parameter calibration of discrete element model of organic fertilizer particles for mechanical fertilization. Transactions of the CSAE, 2018; 34(18): 21–27. (in Chinese)
[14] Song Z H, Li H, Yan Y F, Tian F Y, Li Y D, Li F D. Calibration method of contact characteristic parameters of soil in mulberry field based on unequal-diameter particles DEM theory. Transactions of the CSAM, 2022; 53(6): 21–33. (in Chinese)
[15] Zhang W X, Wang F Y. Parameter calibration of American ginseng seeds for discrete element simulation. Int J Agric & Biol Eng, 2022; 15(6): 16–22.
[16] Jia H L, Deng J Y, Deng Y L, Chen T Y, Wang G, Sun Z J, Guo H. Contact parameter analysis and calibration in discrete element simulation of rice straw. Int J Agric & Biol Eng, 2021; 14(4): 72–81.
[17] Liang R Q, Chen X G, Zhang B C, Wang X Z, Kan Z, Meng H W. Calibration and test of the contact parameters for chopped cotton stems based on discrete element method. Int J Agric & Biol Eng, 2022; 15(5): 1–8.
[18] Wang L M, Fan S Y, Cheng H S, Meng H B, ShenY J, Wang J, et al. Calibration of contact parameters for pig manure based on EDEM. Transactions of the CSAE, 2020; 36(15): 95–102. (in Chinese)
[19] Yao S Q, Shi G K, Wang B S, Peng H J, Meng H W, Kan Z. Calibration of the simulation parameters of jujubes in dwarfing and closer cultivation in Xinjiang during harvest period. Int J Agric & Biol Eng, 2022; 15(2): 256–264.
[20] Chen T, Yi S J, Li Y F, Tao G X, Qu S M, Li R. Establishment of discrete element model and parameter calibration of alfalfa stem in budding stage. Transactions of the CSAM, 2023; 54(5): 91–100. (in Chinese)
[21] Lenaerts B, Aertsen T, Tijskens E, Ketelaeve B D, Ramon H, Baerdemaeker J D, et al. Simulation of grain-straw separation by discrete element modeling with bendable straw particles. Computers and Electronics in Agriculture, 2014; 101: 24–33.
[22] Peng C W, Zhou T, Song S S, Fang Q, Zhu H Y, Sun S L. Measurement and analysis of restitution coefficient of black soldier fly larvae in collision models based on hertz contact theory. Transactions of the CSAM, 2021; 52(11): 125–134. (in Chinese)
[23] Liao Y Y, You Y, Wang D C, Zhang X N, Zhang H F, Ma W P. Parameter calibration and experiment of discrete element model for mixed seeds of oat and arrow pea. Transactions of the CSAM, 2022; 53(8): 14–22. (in Chinese)
[24] Zhang G Z, Chen L M, Liu H P, Dong Z, Zhang Q H, Zhou Y. Calibration and experiments of the discrete element simulation parameters for water chestnut. Transactions of the CSAE, 2022; 38(11): 41–50. (in Chinese)
[25] Zhang S W, Zhang R Y, Cao Q Q, Zhang Y, Fu J, Wen X Y, et al. A calibration method for contact parameters of agricultural particle mixtures inspired by the Brazil nut effect (BNE): The case of tiger nut tuber-stem-soil mixture. Computers and Electronics in Agriculture, 2023; 212: 108112.
[26] Shu C X, Yang J, Wan X Y, Yuan J C, Liao Y T, Liao Q X. Calibration and experiment of the discrete element simulation parameters of rape threshing mixture in combine harvester. Transactions of the CSAE, 2022; 38(9): 34–43. (in Chinese)
[27] Zhong J Q, Tao L M, Li S P, Zhang B, Wang J Y, He Y L. Determination and interpretation of parameters of double-bud sugarcane model based on discrete element. Computers and Electronics in Agriculture, 2022; 203: 107428.
[28] Wang S, Yu Z H, Aorigele, Zhang W J. Study on the modeling method of sunflower seed particles based on the discrete element method. Computers and Electronics in Agriculture, 2022; 198: 107012.
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Published
2024-09-06
How to Cite
Li, Y., Xie, J., Zhang, J., Yue, Y., Meng, Q., Du, Y., & Ma, D. (2024). Parameter calibration and experimental verification of discrete element simulation model for Protaetia brevitarsis larvae bioconversion mixture. International Journal of Agricultural and Biological Engineering, 17(4), 35–44. Retrieved from https://ijabe.migration.pkpps03.publicknowledgeproject.org/index.php/ijabe/article/view/8707
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