Parameter calibration of discrete element simulation model for Panax notoginseng planting soil
-
摘要:目的
获取三七Panax notoginseng种植土壤与触土部件相互作用的离散元仿真模型参数。
方法基于Hertz-Mindlin with JKR接触模型建立三七种植土壤离散元模型并进行参数标定。首先,以土壤颗粒间及土壤−65Mn钢板间的JKR表面能、恢复系数、静摩擦系数、动摩擦系数为试验因素,以土壤堆积角、土壤在65Mn板上的滚动距离为评价指标。其次,采用基于Box-Behnken的响应面优化方法建立土壤堆积角、滚动距离回归模型。
结果对回归模型进行寻优,得到仿真标定的土壤颗粒间JKR表面能、恢复系数、静摩擦系数和动摩擦系数的最优值分别为14.88 J/m2、0.53、0.46和0.150,标定的土壤−65Mn板间JKR表面能、恢复系数、静摩擦系数和动摩擦系数的最优值分别为7.02 J/m2、0.59、0.57和0.058。通过三七挖掘铲仿真试验与土槽试验对比分析得到,挖掘铲受X、Y轴方向平均阻力仿真值与实测值相对误差分别为9.91%、8.78%。
结论标定的离散元土壤模型参数准确度高,研究可为三七收获机触土部件及装备优化提供理论参考。
Abstract:ObjectiveTo obtain the parameters of the discrete element simulation model for the interaction between Panax notoginseng planting soil and soil-engaging components.
MethodThis paper established a discrete element model of P. notoginseng planting soil based on the Hertz-Mindlin with JKR contact model, and calibrated parameters. Firstly, the JKR surface energy, restitution coefficient, static friction coefficient and rolling friction coefficient between soil particles and soil-65Mn steel plate were used as experiments factors, and the soil repose angle and the rolling distance of soil on the 65Mn plate were used as evaluation indexes. Secondly, the regression model for soil repose angle and rolling distance was established through the response surface optimization method based on Box-Behnken.
ResultThe regression model was optimized, and the optimal values of JKR surface energy, restitution coefficient, static friction coefficient and rolling friction coefficient between soil particles calibrated by simulation were 14.88 J/m2, 0.53, 0.46 and 0.150, respectively. The calibrated optimal values of JKR surface energy, restitution coefficient, static friction coefficient and rolling friction coefficient between soil-65Mn steel plate were 7.02 J/m2, 0.59, 0.57 and 0.058, respectively. Through the comparative analysis of the simulation test and the soil-bin test, the relative errors of the simulated and measured average resistance of the excavating shovel in the X and Y axis directions were 9.91% and 8.78%, respectively.
ConclusionThe calibrated discrete element soil model parameters have high accuracy, and the research can provide a theoretical reference for the optimization of the soil-engaging components and equipment of the P. notoginseng harvester.
-
-
表 1 土壤堆积角仿真试验因素及水平1)
Table 1 Factors and levels of simulation test for soil repose angle
水平
Level${x_1}$/(J∙m−2) ${x_2}$ ${x_3}$ ${x_4}$ 低水平 Low level 4 0.15 0.20 0.050 中心水平 Central level 10 0.45 0.62 0.125 高水平 High level 16 0.75 1.04 0.200 1)${x_1}$:土壤颗粒间JKR表面能,${x_2}$:土壤颗粒间恢复系数,${x_3}$:土壤颗粒间静摩擦系数,${x_4}$:土壤颗粒间滚动摩擦系数
1)${x_1}$: JKR surface energy between soil particles, ${x_2}$: Restitution coefficient between soil particles, ${x_3}$: Static friction coefficient between soil particles, ${x_4}$: Rolling friction coefficient between soil particles表 2 土壤堆积角仿真试验设计及结果1)
Table 2 Design and results of soil repose angle simulation test
试验号
Test
No.${x_1}$/(J∙m−2) ${x_2}$ ${x_3}$ ${x_4}$ 堆积角/(°)
Repose
angle1 4 0.75 0.62 0.125 18.00 2 10 0.75 0.62 0.200 37.80 3 4 0.15 0.62 0.125 25.36 4 16 0.15 0.62 0.125 37.48 5 16 0.45 0.62 0.200 44.13 6 4 0.45 0.62 0.050 10.05 7 10 0.75 1.04 0.125 29.78 8 10 0.45 0.62 0.125 36.78 9 10 0.15 0.62 0.200 40.57 10 10 0.15 0.62 0.050 27.48 11 10 0.75 0.20 0.125 31.62 12 4 0.45 0.20 0.125 8.10 13 10 0.15 0.20 0.125 39.95 14 16 0.45 0.20 0.125 37.42 15 4 0.45 1.04 0.125 23.09 16 10 0.75 0.62 0.050 21.11 17 10 0.45 1.04 0.050 22.59 18 16 0.45 1.04 0.125 51.84 19 10 0.45 0.20 0.200 42.32 20 10 0.45 0.62 0.125 37.89 21 10 0.45 1.04 0.200 39.42 22 16 0.45 0.62 0.050 31.58 23 16 0.75 0.62 0.125 36.87 24 10 0.15 1.04 0.125 35.02 25 10 0.45 0.62 0.125 35.53 26 10 0.45 0.20 0.050 29.01 27 10 0.45 0.62 0.125 37.49 28 4 0.45 0.62 0.200 29.04 29 10 0.45 0.62 0.125 35.68 1)${x_1}$:土壤颗粒间JKR表面能,${x_2}$:土壤颗粒间恢复系数,${x_3}$:土壤颗粒间静摩擦系数,${x_4}$:土壤颗粒间滚动摩擦系数
1)${x_1}$: JKR surface energy between soil particles, ${x_2}$: Restitution coefficient between soil particles, ${x_3}$: Static friction coefficient between soil particles, ${x_4}$: Rolling friction coefficient between soil particles表 3 土壤堆积角回归模型方差分析1)
Table 3 Variance analysis of soil repose angle regression model
方差源
Variance
source平方和
Sum of
squares自由度
Degree of
freedom均方
Mean
squareF P 模型
Model2 696.23 24 112.34 100.93 0.000 2** ${x_1}$ 335.26 1 335.26 301.18 <0.000 1** ${x_2}$ 20.88 1 20.88 18.76 0.012 3* ${x_3}$ 21.72 1 21.72 19.51 0.011 5* ${x_4}$ 227.10 1 227.10 204.02 0.000 1** ${x_1}{x_2}$ 11.39 1 11.39 10.23 0.032 9* ${x_1}{x_3}$ 0.08 1 0.08 0.07 0.800 4 ${x_1}{x_4}$ 10.37 1 10.37 9.31 0.038 0* ${x_2}{x_3}$ 2.39 1 2.39 2.14 0.216 9 ${x_2}{x_4}$ 3.24 1 3.24 2.91 0.163 2 ${x_3}{x_4}$ 3.10 1 3.10 2.78 0.170 6 $x_1^2$ 53.95 1 53.95 48.46 0.002 2** $x_2^2$ 18.36 1 18.36 16.50 0.015 3* $x_3^2$ 1.02 1 1.02 0.92 0.391 7 $x_4^2$ 34.10 1 34.10 30.63 0.005 2** $x_1^2{x_2}$ 0.17 1 0.17 0.15 0.715 0 $x_1^2{x_3}$ 187.50 1 187.50 168.45 0.000 2** $x_1^2{x_4}$ 0.25 1 0.25 0.22 0.663 4 ${x_1}x_2^2$ 3.96 1 3.96 3.56 0.132 3 ${x_1}x_3^2$ 57.51 1 57.51 51.67 0.002 0** $x_2^2{x_3}$ 0.81 1 0.81 0.73 0.441 0 $x_2^2{x_4}$ 0.02 1 0.02 0.02 0.909 8 ${x_2}x_3^2$ 2.45 1 2.45 2.20 0.211 8 $x_1^2x_2^2$ 0.00 1 0.00 0.00 0.978 7 $x_1^2x_3^2$ 0.88 1 0.88 0.79 0.423 3 纯误差
Pure error4.45 4 1.11 总和
Sum2 700.69 28 1)${x_1}$:土壤颗粒间JKR表面能,${x_2}$:土壤颗粒间恢复系数,${x_3}$:土壤颗粒间静摩擦系数,${x_4}$:土壤颗粒间滚动摩擦系数;“*”“**”分别表示在P<0.05和P<0.01水平影响显著(P值检验法)
1)${x_1}$: JKR surface energy between soil particles, ${x_2}$: Restitution coefficient between soil particles, ${x_3}$: Static friction coefficient between soil particles, ${x_4}$: Rolling friction coefficient between soil particles; “*” and “**” indicate signifcant effects at P < 0.05 and P < 0.01 levels respectively (P-value test method)表 4 斜面仿真试验因素及水平1)
Table 4 Factors and levels of slope simulation test
水平
Level${x_5}$/(J∙m−2) ${x_6}$ ${x_7}$ ${x_8}$ 低水平 Low level 2 0.20 0.20 0.030 中心水平 Central level 7 0.45 0.45 0.055 高水平 High level 12 0.70 0.70 0.080 1)${x_5}$:土壤−65Mn板间JKR表面能,${x_6}$:土壤−65Mn板间恢复系数,${x_7}$:土壤−65Mn板间静摩擦系数,${x_8}$:土壤−65Mn板间滚动摩擦系数
1)${x_5}$: JKR surface energy between soil-65Mn plate, ${x_6}$: Restitution coefficient between soil-65Mn plate, ${x_7}$: Static friction coefficient between soil-65Mn plate, ${x_8}$: Rolling friction coefficient between soil-65Mn plate表 5 斜面仿真试验设计及结果1)
Table 5 Design and results of slope simulation test
试验号
Test No.${x_5}$/(J∙m−2) ${x_6}$ ${x_7}$ ${x_8}$ 滚动距离/mm
Rolling
distance1 7 0.20 0.45 0.030 882.53 2 7 0.70 0.70 0.055 402.56 3 2 0.45 0.70 0.055 463.21 4 7 0.70 0.45 0.030 854.41 5 7 0.45 0.20 0.030 817.00 6 7 0.45 0.45 0.055 415.24 7 7 0.70 0.45 0.080 266.53 8 12 0.45 0.45 0.080 230.83 9 7 0.20 0.45 0.080 241.72 10 2 0.45 0.45 0.030 877.41 11 7 0.45 0.70 0.080 257.49 12 12 0.45 0.70 0.055 391.03 13 7 0.45 0.45 0.055 421.78 14 7 0.45 0.45 0.055 429.95 15 7 0.45 0.45 0.055 427.71 16 7 0.45 0.20 0.080 256.03 17 7 0.70 0.20 0.055 415.11 18 12 0.45 0.45 0.030 793.51 19 12 0.70 0.45 0.055 354.93 20 2 0.20 0.45 0.055 456.22 21 7 0.45 0.70 0.030 843.15 22 2 0.45 0.20 0.055 488.20 23 2 0.45 0.45 0.080 295.52 24 7 0.20 0.20 0.055 396.58 25 7 0.20 0.70 0.055 396.66 26 2 0.70 0.45 0.055 455.17 27 12 0.20 0.45 0.055 342.45 28 7 0.45 0.45 0.055 421.21 29 12 0.45 0.20 0.055 350.32 1)${x_5}$:土壤−65Mn板间JKR表面能,${x_6}$:土壤−65Mn板间恢复系数,${x_7}$:土壤−65Mn板间静摩擦系数,${x_8}$:土壤−65Mn板间滚动摩擦系数
1)${x_5}$: JKR surface energy between soil-65Mn plate, ${x_6}$: Restitution coefficient between soil-65Mn plate, ${x_7}$: Static friction coefficient between soil-65Mn plate, ${x_8}$: Rolling friction coefficient between soil-65Mn plate表 6 土壤滚动距离回归模型方差分析1)
Table 6 Variance analysis of regression model of soil rolling distance
方差源
Variance
source平方和
Sum of
squares自由度
Degree of
freedom均方
Mean
squareF P 模型
Model1.20 × 106 24 50 020.25 1 479.47 <0.000 1** ${x_5}$ 5 519.75 1 5 519.75 163.26 0.000 2** ${x_6}$ 2.74 1 2.74 0.08 0.790 1 ${x_7}$ 190.58 1 190.58 5.64 0.076 5 ${x_8}$ 3.29×105 1 3.29×105 9 721.81 <0.000 1** ${x_5}{x_6}$ 45.77 1 45.77 1.35 0.309 3 ${x_5}{x_7}$ 1 079.12 1 1 079.12 31.92 0.004 8** ${x_5}{x_8}$ 92.26 1 92.26 2.73 0.173 9 ${x_6}{x_7}$ 39.88 1 39.88 1.18 0.338 5 ${x_6}{x_8}$ 700.40 1 700.40 20.72 0.010 4* ${x_7}{x_8}$ 152.40 1 152.40 4.51 0.101 0 $x_5^2$ 360.96 1 360.96 10.68 0.030 9* $x_6^2$ 6.96 1 6.96 0.21 0.673 7 $x_7^2$ 1 546.55 1 1 546.55 45.74 0.002 5** $x_8^2$ 81 826.04 1 81 826.04 2 420.20 <0.000 1** $x_5^2{x_6}$ 27.16 1 27.16 0.80 0.420 8 $x_5^2{x_7}$ 17.67 1 17.67 0.52 0.509 7 $x_5^2{x_8}$ 0.530 4 1 0.53 0.02 0.906 4 ${x_5}x_6^2$ 534.97 1 534.97 15.82 0.016 4* ${x_5}x_7^2$ 472.32 1 472.32 13.97 0.020 2* $x_6^2{x_7}$ 200.80 1 200.80 5.94 0.071 4 $x_6^2{x_8}$ 841.73 1 841.73 24.90 0.007 5** ${x_6}x_7^2$ 96.19 1 96.19 2.85 0.166 9 $x_5^2x_6^2$ 41.41 1 41.41 1.22 0.330 5 $x_5^2x_7^2$ 1 052.52 1 1 052.52 31.13 0.005 1** 纯误差
Pure error135.24 4 33.81 总和
Sum1.20×106 28 1)${x_5}$:土壤−65Mn板间JKR表面能,${x_6}$:土壤−65Mn板间恢复系数,${x_7}$:土壤−65Mn板间静摩擦系数,${x_8}$:土壤−65Mn板间滚动摩擦系数;“*”“**”分别表示在P<0.05和P<0.01水平影响显著(P值检验法)
1)${x_5}$: JKR surface energy between soil-65Mn plate, ${x_6}$: Restitution coefficient between soil-65Mn plate, ${x_7}$: Static friction coefficient between soil-65Mn plate, ${x_8}$: Rolling friction coefficient between soil-65Mn plate; “*” and “**” indicate signifcant effect at P < 0.05 and P < 0.01 levels respectively (P-value test method) -
[1] JIANG D L, LIU Y, LIN Z F, et al. Effects of combined infrared and hot-air drying on ginsenosides and drying characteristics of Panax notoginseng (Araliaceae) roots[J]. International Journal of Agricultural and Biological Engineering, 2022, 15(1): 267-276. doi: 10.25165/j.ijabe.20221501.6210
[2] YANG K, YANG L, FAN W, et al. Illumina-based transcriptomic analysis on recalcitrant seeds of Panax notoginseng for the dormancy release during the after-ripening process[J]. Physiologia Plantarum, 2019, 167(4): 597-612. doi: 10.1111/ppl.12904
[3] 邵明安, 王全九, 黄明斌. 土壤物理学[M]. 北京: 高等教育出版社, 2006. [4] 邢洁洁, 张锐, 吴鹏, 等. 海南热区砖红壤颗粒离散元仿真模型参数标定[J]. 农业工程学报, 2020, 36(5): 158-166. [5] 郝建军, 魏文波, 黄鹏程, 等. 油葵籽粒离散元参数标定与试验验证[J]. 农业工程学报, 2021, 37(12): 36-44. [6] WANG X W, MA H Z, LI B, et al, Review on the research of contact parameters calibration of particle system[J]. Journal of Mechanical Science and Technology, 2022, 36(3): 1363-1378.
[7] 向伟, 吴明亮, 吕江南, 等. 基于堆积试验的黏壤土仿真物理参数标定[J]. 农业工程学报, 2019, 35(12): 116-123. [8] 李俊伟, 佟金, 胡斌, 等. 不同含水率黏重黑土与触土部件互作的离散元仿真参数标定[J]. 农业工程学报, 2019, 35(6): 130-140. [9] 王宪良, 钟晓康, 耿元乐, 等. 基于离散元非线性弹塑性接触模型的免耕土壤参数标定[J]. 农业工程学报, 2021, 37(23): 100-107. [10] 杨启志, 赫明胜, 施雷, 等. 分层防寒土与接触式清土机具相互作用的离散元仿真参数标定[J]. 江苏大学学报(自然科学版), 2023, 44(1): 52-61. [11] 宋占华, 李浩, 闫银发, 等. 桑园土壤非等径颗粒离散元仿真模型参数标定与试验[J]. 农业机械学报, 2022, 53(6): 21-33. [12] 石林榕. 西北旱区玉米直插穴播互作机理研究[D]. 兰州: 甘肃农业大学, 2022. [13] 游琪, 杨启良. 不同排水体对三七生长、土壤养分及根区土壤微生物的影响[J]. 排灌机械工程学报, 2022, 40(9): 959-965. [14] 锦州市环境监测中心站. 土壤 干物质和水分的测定 重量法: HJ 613—2011[S]. 北京: 中国环境科学出版社, 2011: 1-3. [15] 解开婷, 张兆国, 王法安, 等. 土壤与三七根茎黏附数学模型构建与验证[J]. 农业工程学报, 2022, 38(S1): 131-141. [16] 廖宜涛, 王在腾, 廖庆喜, 等. 果荚初期饲料油菜茎秆离散元接触模型参数标定[J]. 农业机械学报, 2020, 51(S1): 236-243. [17] 陈涛, 衣淑娟, 李衣菲, 等. 苜蓿现蕾期茎秆离散元模型建立与参数标定[J]. 农业机械学报, 2023, 54(5): 91-100. [18] 张锐, 韩佃雷, 吉巧丽, 等. 离散元模拟中沙土参数标定方法研究[J]. 农业机械学报, 2017, 48(3): 49-56. [19] 马帅, 徐丽明, 袁全春, 等. 葡萄藤防寒土与清土部件相互作用的离散元仿真参数标定[J]. 农业工程学报, 2020, 36(1): 40-49. [20] 张胜伟, 张瑞雨, 陈天佑, 等. 绿豆种子离散元仿真参数标定与排种试验[J]. 农业机械学报, 2022, 53(3): 71-79. [21] SUN J F, CHEN H M, WANG Z M, et al. Study on plowing performance of EDEM low-resistance animal bionic device based on red soil[J]. Soil and Tillage Research, 2020, 196: 104336. doi: 10.1016/j.still.2019.104336
[22] 王一驰. 基于离散元法的三七挖掘机理研究[D]. 昆明: 昆明理工大学, 2021. [23] CUNHA R N, SANTOS K G, LIMA R N, et al. Repose angle of monoparticles and binary mixture: An experimental and simulation study[J]. Powder Technology, 2016, 303: 203-211. doi: 10.1016/j.powtec.2016.09.023
[24] MA W B, LIU J, CHENG Y R, et al. Study on mesoscopic adhesion characteristics of deep-sea sediment for self-cleaning mechanism of bionic grouser[J]. Applied Ocean Research, 2023, 131: 103451. doi: 10.1016/j.apor.2022.103451
[25] 黄玉祥, 杭程光, 苑梦婵, 等. 深松土壤扰动行为的离散元仿真与试验[J]. 农业机械学报, 2016, 47(7): 80-88. [26] 杜小强, 宁晨, 杨振华, 等. 跨式油茶果收获机履带底盘行走液压系统设计与试验[J]. 农业机械学报, 2023, 54(3): 139-147. [27] 张兆国, 余小兰, 李汉青, 等. 温室三七收获机挖掘铲铲型对比研究[J]. 东北农业大学学报, 2020, 51(9): 79-88. [28] 于艳, 龚丽农, 尚书旗. 农机土槽试验动力学参数测试系统的研制[J]. 农业工程学报, 2011, 27(S1): 323-328. -
期刊类型引用(1)
1. 张运春,欧春予,张桥英. 氮添加对不同密度入侵植物喜旱莲子草生长的影响. 生态环境学报. 2020(09): 1745-1751 . 百度学术
其他类型引用(5)