Discrete element flexible modeling and experimental verification of rice blanket seedling root blanket

IF 8.9 1区 农林科学 Q1 AGRICULTURE, MULTIDISCIPLINARY Computers and Electronics in Agriculture Pub Date : 2025-03-01 DOI:10.1016/j.compag.2025.110155
Xuan Jia , Xiaopei Zheng , Licai Chen , Cailing Liu , Jiannong Song , Chengtian Zhu , Jitong Xu , Shuaihua Hao
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Abstract

Using the discrete element method (DEM) to simulate the rice machine transplanting operation is important for assessing the plant injury and optimizing the rice transplanter performance, while the DEM flexible model establishment that can accurately reflect the mechanical properties of the rice blanket seedling root blanket is an important foundation. Based on the root blanket’s stratification and the root system structure’s measurement and statistics, a new method for root blanket flexible modeling was proposed in this study. Firstly, the Hertz-Mindlin with bonding V2 contact model was used to establish substrate Ⅰ (SⅠ), substrate Ⅱ (SⅡ), substrate Ⅲ (SⅢ), stem-root combination (SRC), and netted layer (NL) flexible models, respectively, and the model parameters were calibrated and determined by angle of repose (AOR), direct shear, and mechanical tests. The calibration results showed that the deviations of AOR simulated values for SⅠ and SⅡ were both less than 1.5 %, and the deviations of shear strength simulated values were both less than 4 %. Secondly, the shear characteristics of SⅠ and SⅡ were determined by direct shear test. The results showed that the physical and simulated shear stress-displacement relationship curves of SⅠ and SⅡ were basically the same; the hair roots mainly relied on the cohesive between them and the substrate to improve the substrate strength; the fitted lines of simulated shear strength and normal stress of SⅠ and SⅡ were in high agreement with these of the measured values; the deviations of the simulated cohesion and internal friction angle were both less than 5 %. After that, the Hertz Mindlin with JKR V2 contact model was used between SRC and substrate. The interfacial surface energy of the root blanket and the bonding parameters of SⅢ were calibrated by stem, half-SRC, and SRC pulling-out tests layer by layer. The calibration results showed that the deviation of the maximum pulling-out force of SRC was 5.83 %, verifying that the model could accurately simulate the intertwining effect of the crown roots. Finally, the flexible model of the root blanket was verified by cutting, curling, and tensile tests. The simulated test results were consistent with the trends of the physical test results; the deviations of the maximum cutting resistance of front cutting and side cutting were both within 8 %, the error percentage range of the marked points height was 0.35 % to 17.16 %, and the deviation of the maximum tensile force was 9.22 %, indicating the good feasibility of the modeling method and accuracy of the flexible model. The results of this study lay a foundation for the DEM simulation of the rice machine transplanting operation. They can also provide a reference for the numerical simulation of other multi-plant root-soil complexes.
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稻毯苗根毯离散元柔性建模及试验验证
采用离散元法(DEM)模拟水稻机插秧作业对评估植株损伤和优化插秧机性能具有重要意义,而建立能准确反映稻毯苗根毯力学特性的DEM柔性模型是重要基础。基于根毯的分层和根系结构的测量统计,提出了一种根毯柔性建模的新方法。首先,采用Hertz-Mindlin粘接V2接触模型,分别建立基体Ⅰ(SⅠ)、基体Ⅱ(SⅡ)、基体Ⅲ(SⅢ)、茎-根组合(SRC)和网状层(NL)柔性模型,并通过静卧角(AOR)、直剪和力学试验对模型参数进行标定和确定。标定结果表明,SⅠ和SⅡ的AOR模拟值偏差均小于1.5%,抗剪强度模拟值偏差均小于4%。其次,通过直剪试验确定SⅠ和SⅡ的剪切特性。结果表明:SⅠ和SⅡ的物理剪应力-位移关系曲线与模拟剪应力-位移关系曲线基本一致;发根主要依靠其与基材之间的黏结性来提高基材强度;SⅠ和SⅡ的模拟抗剪强度和正应力拟合线与实测值吻合较好;模拟黏聚力和内摩擦角的偏差均小于5%。然后,在SRC与衬底之间使用带有JKR V2接触模型的Hertz Mindlin。根毯的界面表面能和SⅢ的键合参数通过茎、半SRC和SRC逐层拔出试验进行标定。校正结果表明,SRC的最大拔出力偏差为5.83%,验证了该模型能较准确地模拟冠根的缠绕效应。最后,通过剪切、卷曲和拉伸试验验证了根毡的柔性模型。模拟试验结果与物理试验结果趋势一致;正面切割和侧面切割的最大切割阻力偏差均在8%以内,标记点高度误差百分比范围为0.35% ~ 17.16%,最大拉伸力偏差为9.22%,表明建模方法具有良好的可行性和柔性模型的准确性。研究结果为水稻机插操作的DEM模拟奠定了基础。也可为其他多植物根系-土壤复合体的数值模拟提供参考。
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来源期刊
Computers and Electronics in Agriculture
Computers and Electronics in Agriculture 工程技术-计算机:跨学科应用
CiteScore
15.30
自引率
14.50%
发文量
800
审稿时长
62 days
期刊介绍: Computers and Electronics in Agriculture provides international coverage of advancements in computer hardware, software, electronic instrumentation, and control systems applied to agricultural challenges. Encompassing agronomy, horticulture, forestry, aquaculture, and animal farming, the journal publishes original papers, reviews, and applications notes. It explores the use of computers and electronics in plant or animal agricultural production, covering topics like agricultural soils, water, pests, controlled environments, and waste. The scope extends to on-farm post-harvest operations and relevant technologies, including artificial intelligence, sensors, machine vision, robotics, networking, and simulation modeling. Its companion journal, Smart Agricultural Technology, continues the focus on smart applications in production agriculture.
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