To establish a modelling method for wheat plants with leaves, aimed at analysing the wheat harvesting process and the influence of leaves on the harvesting process, this study first conducted a test analysis of the geometric shapes and size parameters of wheat leaves. On this basis, four geometric modelling schemes were proposed: three-leaf-vein and five-leaf-vein configurations with tangent and interval arrangements. The contact parameters were measured and calibrated, and combined with neural network training and genetic algorithm optimisation, a discrete element model of wheat plants with leaves was established based on the Bonding model. Based on the above work, the accuracy of the leaf contact model and parameters was verified through leaf volume density tests and comparisons with simulations. The accuracy of the leaf bonding model and parameters was verified through leaf impact tests and comparisons with simulations. By comparing the maximum impact force and the fracture of the leaf in the test and simulation, and the five-leaf-vein with intervals arrangement was finally determined as the optimal modelling scheme. Through tangential threshing tests and comparison with simulation results, the feasibility and effectiveness of the overall model of wheat plants with leaves established were verified. The plant model with leaves can further reduce the overall error in the simulation and actual test of the threshing process, laying the foundation for further research on multi-scale modelling of wheat plants and the influence of wheat leaves on the simulation analysis of the harvesting process.

To address the challenge of simulating complex interactions in high moisture (e.g., 41.46% for straw) wheat straw-root systems during rotary tillage, this study developed an integrated Discrete Element Method (DEM) framework incorporating geometry reconstruction, multi-mechanism contact modelling, and a novel parameter calibration methodology. By analysing geometric properties of straw and root (coefficient of variation <10%), this study constructed a simplified model using linearly arranged spherical particles. The Hertz-Mindlin with bonding model and Hertz-Mindlin with JKR contact model were innovatively combined to simultaneously capture flexible fracture behaviour and moisture-dependent adhesion characteristics. Moreover, this study proposes a macro-micro parametric regression-based calibration method, establishing robust relationships (R-2 > 0.96) between macroscopic mechanical parameters and microscopic discrete element parameters. The model was systematically validated through experimental trials to demonstrate accurate prediction of key mechanical behaviour, including the straw three-point bending test (relative error (RE) of flexural elastic modulus is 7.90%), the shear test of multiple roots (RE of shear ultimate force is 1.07%), and the dynamic angle of repose (AoR) (RE < 5%). Finally, simulations revealed that adhesion in high moisture straw-root mixture (SRM) accounts for 3.4513.79% of additional energy consumption during rotary tillage-a first quantitative demonstration of adhesion's role in agricultural tool dynamics. The developed model enables precise analysis of straw-root-soil-blade interactions, offering great potential for optimising blade geometry and operational parameters.

Discrete element method (DEM)-based simulation of the wheat cutting process is a critical approach for optimising harvesting machinery, with accuracy depending on plant model precision and mechanical parameter rationality. However, existing quasi-static parameters lead to significant prediction errors in cutting force at higher cutting speeds. To address this issue, a specific wheat plant tillering model was developed, and two dynamic calibration strategies for the Parallel Bonding Model (PBM) were proposed to enhance high-speed cutting simulation accuracy. The first strategy, a stiffness-stress central composite design (CCD) calibration method, optimised bond parameters for constant cutting speeds. The second strategy, a bond-radius multiplier calibration method, establishes a speed-adaptive model by correlating the cutting speed with the bond-radius multiplier, facilitating the efficient and rapid force calibration required for variable-speed cutting simulations. Reciprocating cutting tests and simulation results demonstrated that at a cutting speed of 1.0 m s-1, the CCD calibration method reduced the peak cutting force simulation error from 16.75% to 9.13%. Meanwhile, the speed-adaptive bond-radius multiplier method consistently reduced this error from 16.75% to 5.58%-10.03%. Furthermore, the simulated miss-cutting ratio error under different cutting speed ratios remained below 5%. These findings indicate that the proposed tillering plant modelling method and dynamic bond parameter calibration strategies significantly improve the accuracy of DEM-based dynamic cutting simulations, providing a vital framework for the simulative optimisation of harvesting cutters.

With the diversification of market demand, various mixed-model production methods have been widely adopted. Aiming to address the joint optimisation of mixed-model and parallel two-sided assembly line balance, a joint optimisation model of mixed-model and parallel two-sided assembly line balance is established. A discrete hybrid artificial fish swarm algorithm based on the genetic algorithm with crossover and mutation rules is proposed to solve this model. By computing 25 groups of classical examples, the results are compared with those of other heuristic algorithms and the mixed-model two-sided assembly line balancing problem; Comparison results show that the discrete hybrid artificial fish swarm algorithm is competitive in solving this problem, verifying the effectiveness of the model and algorithm; The balancing results of the parallel two-sided assembly line are superior to those of the two-sided assembly line, which verifies the effectiveness of the multi-line synergy effect in the parallel two-sided assembly line.

Aiming at the flexible production of small-lot and multi-variety assembly lines in intelligent manufacturing systems, a robot-operated mixed-model sequencing and parallel two-sided assembly line assembly system is proposed. Systematic co-optimization in three dimensions of task assignment at mated-stations and multi-line stations, multi-product mixed-model sequencing and task line balancing, as well as robot types and task time at workstations are solved. Mixed-model parallel two-sided assembly line system and its key terms are defined. A mathematical model of the mixed-model robotic parallel two-sided assemblyGreen line type-II balancing problem (MRPTALBP-II) considering energy consumption is developed. Based on the ant colony optimization algorithm (ACO) and simulated annealing algorithm (SA) for solving the model, the ant colony hybrid simulated annealing algorithm (ACHSA) is proposed to solve the model. A new initial solution encoding, multiple neighborhood structures and dual pheromone matrix updating method are designed,in order to avoid the algorithm from falling into local optimum and to expand the search range. Three sets of calculations are obtained for comparative analysis in conjunction with classical arithmetic cases. The results show that the ACHSA outperforms the SA and the ACO, with an excellence rate of 100% for large-scale arithmetic cases and 61% for small-scale arithmetic cases, which verifies the validity of the model and the algorithm. Firstly, the MRPTALBP-II is successfully solved, which provides a useful reference for the solution of multi-factor collaborative problems of complex systems.

Establishing an accurate high-moisture corn ear fragmentation model using the Discrete Element Method is crucial for studying the processing and fragmentation of high-moisture corn ears. This study focuses on high-moisture corn ears during the early harvest stage, developing a fragmentable corn ear model and calibrating its bonding parameters. First, based on the Hertz–Mindlin method in the Discrete Element Method, a three-layer corn cob bonding model consisting of pith, woody ring structure, and glume was established. Through a combined experimental and simulation calibration approach, the bonding parameters of the cob were determined using Plackett–Burman tests, the steepest ascent tests, and Box–Behnken tests. Subsequently, the same method was applied to establish a corn kernel bonding model, with the kernel bonding parameters calibrated through the steepest ascent and Box–Behnken tests. In order to arrange the kernel models on the cob model to achieve the construction of a complete ear model, this paper proposes a “matrix coordinate positioning method”. Through calculations, this method enables the uniform arrangement of corn kernels on the cob, thereby accomplishing the establishment of a composite model for the high-moisture corn ear. The bonding parameters between the cob and kernels were determined through compression tests. Finally, the reliability of the model was partially validated through shear testing; however, potential confounding variables remain unaccounted for in the experimental analysis. While this study establishes a theoretical framework for the design and optimization of machinery dedicated to high-moisture corn ear fragmentation processes, questions persist regarding the comprehensiveness of variable inclusion during parametric evaluation. This analytical approach exhibits characteristics analogous to incomplete system modeling, potentially limiting the generalizability of the proposed methodology.

A high-performance stubble-breaking operation is an important guarantee for the quality of no-till operations, and studying the interaction between blades and root-soil composites is a key foundation for improving the performance of stubble-breaking devices. Therefore, a model was developed to predict the cutting force of the blade and the dragging distance of the root for cutting maize root-soil composites. This model was validated through cutting experiments of reshaped and undisturbed maize root-soil composites, and was used to study the influence of key factors on cutting. The verification test results indicated that the model was accurate (error<20%), efficient (1.86 s), and general. Based on the model, the interaction was described as follows: (a) The root tensile force, which is generated by the dragging of the root, increased the resistance of the blade; (b) Once the root-soil interface fails, the root is difficult to break; (c) A higher soil foundation modulus prevents roots from being dragged and also leads to a higher cutting force; (d) As the number of roots per unit volume increases, the stubble-breaking resistance also increases; (e) The cutting force of cutting root-soil composites with thick roots or densely distributed fine roots is higher. In summary, to reduce stubble-breaking resistance, suitable field conditions should be selected, a large number of roots should be avoid distributing on the blade cutting path, and the root dragging distance should be shortened. This study revealed the blade-root-soil interaction mechanism, providing a theoretical basis for the design and optimisation of stubble-breaking devices.

Paddy field leveling is an essential step before rice transplanting. During the operation of a paddy field grader, a common issue is the wrapping of rice straw around the blades, resulting in a low rice straw burial rate. This study focused on analyzing the operating parameters of a disc spring–tooth-combined paddy field grader. A soil–straw mechanism simulation model was created using EDEM 2021 software to simulate the field operation status. Firstly, the single-factor test was carried out, with the working speed, the working depth of the disc cutter roller, and the rotation speed of the cutter roller as the factors and the straw-buried rate (SBR) and the machine forward resistance (MFR) as the test indexes, and the parameter range was optimized. The parameters were optimized by the response surface method (RSM) and machine learning algorithms. The results indicated that the genetic algorithm–back propagation (GA-BP) neural network outperformed other optimization models in terms of prediction accuracy and stability. By utilizing the GA-BP regression model and RSM model for regression fitting, two sets of optimal parameter combinations were obtained. Verification experiments were carried out using two sets of parameter combinations. Taking the average of the experimental results, the simulation results showed that the straw burial rate was 93.47% and the forward resistance was 6487 N for the parameter combinations of RSM, and the straw burial rate was 94.86% and the forward resistance was 6352 N for the parameter combinations of GA-BP; the field experiments showed that the straw burial rate was 92.86% and the forward resistance was 6518 N for the parameter combinations of RSM, and the straw burial rate was 95.17% and the forward resistance was 6249 N for the parameter combinations of GA-BP. The results demonstrated that the GA-BP prediction model exhibited better predictive capabilities compared to the traditional RSM, providing more accurate predictions of the paddy field grader’s field operation performance.

In the production process of maize, the uniformity of maize sowing is one of the main factors affecting maize yield. The effect of soil coverage and the compaction process on sowing uniformity, as the final link in determining the seed bed position, needs to be further investigated. In this paper, the parameters between soil particles and boundaries are calibrated using the Plackett–Burman test and the central composite design. Furthermore, based on the DEM–MBD coupling, the influence of soil coverage and the compaction process on the seed position of the seeding monomer at different forward speeds are analysed. It was found that the adhesion between the soil and the soil-touching component can have a significant effect on the contact process between the component and the soil. Therefore, the EEPA model was used to analyse the soil–component interaction process and the contact parameters between the soil and components were obtained for the calibration. Further, based on the above work, it was found that before and after mulching, the displacement of seed particles of all shapes in the longitudinal direction increased significantly with the increase in the advancement speed of the sowing unit, while the displacement of seed particles in the transverse and sowing depth directions decreased with the increase in the advancement speed of the unit. In addition, before and after suppression, as the forward speed of the sowing unit increased, the displacement of seed particles of all shapes in the longitudinal and transverse directions gradually increased, and the displacement of seed particles of all shapes in the direction of the sowing depth decreased; the disturbance of seed displacement by the mulch suppression process was not related to seed shape. As the operating speed of the seeding unit increased, the mulching compaction process significantly reduced the sowing uniformity of maize seeds. This paper provides a theoretical basis for the next step in optimising the structure and working process of the soil coverage and the compaction.

In response to the increasing demand for individualized products in the 'small-lot, multi-variety' market, there is an urgent need to enhance the efficiency and intelligence level of assembly lines. To address this, a novel solution method for the mixed-model parallel two-sided assembly lines balancing problem (MMPTSALBP) is proposed. The first step is to define the type and layout of the parallel two-sided assembly lines. Next, a mathematical model is constructed with the objective of minimizing the number of workstations required for the MMPTSALBP, proposing an improved ant colony algorithm that utilizes double string representation for the initial solution encoding method and a double pheromone matrix update to solve the model. Its efficiency is tested on benchmark datasets according to some performance measures and classifications. A study validates its effectiveness on 25 classical arithmetic cases by comparison with the solutions of an heuristic algorithm and an artificial fish swarm algorithm that had been reported to perform well.

The excretory-secretory product (ESP) of Trichinella spiralis (T. spiralis) has antitumor activity. To explore the effect of ESP on liver cancer cells, tumor models were established with H22 cells and then infected with T. spiralis. The results showed that the growth of tumors in mice infected with T. spiralis was significantly inhibited. ESP from adult worms or muscle larvae were then incubated with H22 cells in vitro, and it was found that the ESP could inhibit cell proliferation and promote apoptosis. Subsequently, apoptosis-related proteins in stimulated H22 cells were evaluated, and ESP was found to induce cell apoptosis through the mitochondrial pathway. Additionally, Th-related cytokines were investigated in vivo, and the results showed that the levels of Th1 cytokines were significantly increased in the early stage of T. spiralis infection, while Th2 cytokines increased later than Th1 cytokines, implying that Th1 cytokines with antitumor effects may play a role in inhibiting tumor growth at early stage. In short, ESP can directly induce tumor cell apoptosis and indirectly inhibit tumor cell growth through the host immune system, which may be the antitumor mechanism of T. spiralis infection.

Aiming at the improvement of the efficiency of the assembly line in the intelligent manufacturing field, a parallel U-shaped assembly line balancing problem (PUALBP) appears. In this paper, a mathematical model of the PUALBP-I is established, and an improved genetic algorithm (IGA) is innovatively designed based on the allocation strategy. Combined with 56 classic examples, the IGA is used to solve the mathematical models of SUAL and PUAL respectively, and the balance results and the balance effect evaluation indicators are obtained. The comparison with Parallel U-line Heuristic (PUH) shows that the results of PUAL are better than SUAL, and verifies that the IGA is effective. The results demonstrate that the IGA in calculating large-scale problems is superior to the small-scale problems, which provides a useful reference for solving PUALBP.

To improve the crushing efficiency and crushing pass rate of high-moisture corn ears (HMCEs), a multi-stage crushing scheme is proposed in this paper. A two-stage crushing device for HMCEs is designed, and the ear crushing process is analyzed. Firstly, a simulation model for HMCEs was established in EDEM software (2018), and the accuracy of the model was verified by the shear test. Subsequently, single-factor simulation experiments were conducted, with the crushing rate serving as the evaluation index. The optimal working parameter ranges for the HMCE device were identified as a primary crushing roller speed of 1200–1600 revolutions per minute (r/min), a secondary crushing roller clearance of 1.5–2.5 mm, and a secondary crushing roller speed of 2750–3750 r/min. A Box–Behnken experiment was conducted to establish a multiple regression equation. With the objective of maximizing the qualified crushing pass rate, the optimal combination of parameters was revealed: a primary crushing roller speed of 1500 r/min, a secondary crushing roller clearance of 2.5 mm, and a secondary crushing roller speed of 3280 r/min. The pass rate of corn cob crushing in the simulation test was 98.2%. The physical tests, using the optimized parameter combination, yielded a qualified crushing rate of 97.5%, which deviates by 0.7% from the simulation results, satisfying the requirement of a qualified crushing rate exceeding 95%. The experimental outcomes validate the rationality of the proposed crushing scheme and the accuracy of the model, providing a theoretical foundation for subsequent research endeavors.

In this paper, the Multisphere (MS) models of three varieties of Cyperus esculentus seeds are modeled based on DEM. In addition, for comparison, other particle models based on automatic filing in EDEM software are also introduced. Then, the direct shear test, piling test, bulk density test, and rotating hub test are used to verify the feasibility of particle models of Cyperus esculentus seeds that we proposed. By comparing the simulated results and experimental results, combined with the CPU computation time, the proposed particle models achieved better simulation accuracy with fewer filing spheres. According to simulation results, some limitation was present when using one single verification test; varieties of verification tests used could improve the verification reliability, and a more appropriate particle model could be selected. Additionally, the issue of multicontact points in the MS model was studied. The Hertz Mindlin (no slip) (HM) model and Hertz Mindlin new restitution (HMNR) model were both considered in simulations for comparison. The rotating hub test and particle–wall impact test were used, and the influences of multiple contact points on the motion behavior of individual particles and particle assemblies were analyzed. Simulation results showed that the multiple contact points affected the motion behavior of individual particles; in contrast, the influence of multiple contact points on the motion behavior of the particle assembly was insignificant. Moreover, the relationships between moisture content of seeds and Young’s modulus, Young’s modulus, and the number of contact points were also considered. Young’s modulus decreased with increasing moisture content. The number of contact points increased with a decreasing Young’s modulus.

Simulation of the wheat harvesting process using the discrete element method is of significant importance in optimizing the components of wheat harvesting machinery. Establishing a discrete element model that can accurately reflect the biomechanical properties of wheat plants is a crucial foundation for simulating harvesting operations. To address the current issues in the discrete element model (DEM) of wheat plants, a general modeling method for wheat plants was developed in this study. Firstly, the shape and size of 10 representative varieties of wheat plants in the mature period from different regions in mainland China to establish the common correlations between the shape and size of wheat plants. On this basis, a geometrical model of wheat plants was built using the particle arrangement method, and the coordinates of the component particles were solved for. Then, the contact mechanical parameters were measured and calibrated through various tests, including the slope test, single-pendulum test, drop test and stacking angle test. Moreover, the parallel bonding mechanical parameters of wheat plants were measured and analyzed by tensile, compression and shear tests. On this basis, the mechanical model of wheat plants was established based on the Hertz-Mindlin contact model and the parallel bonding model (PBM). The geometrical model together with the mechanical model enabled the construction of a DEM-based model of wheat plants with flexible characteristics. Based on the above work, the models that were proposed in this paper for three varieties of wheat were validated by comparing the experimental data and simulation results in terms of the plant stacking test, vibration screening test and impact threshing test. The results demonstrated that the simulation results for all three varieties were similar to the experimental results, which showed the feasibility and effectiveness of the general modeling method proposed in this paper for wheat plants in the mature period. The results of this study lay a foundation for the analysis of the wheat harvest process by the discrete element method.

In discrete element method (DEM) simulations, accurate simulation parameters are very important. For ellipsoidal soybean seed particles, the rolling friction coefficient between seed particles (RFCP-P) and the rolling friction coefficients between seed particle and boundary (RFCP-B) are difficult to measure experimentally and therefore need to be calibrated. In this paper, soybean seed particles of three varieties with different sphericities were taken as the research objects. Through the simulation analysis of repose angle and self-flow screening, it was shown that the above two parameters needed to be accurately calibrated. In addition, the sensitivity of the RFCP-P and RFCP-B to the angle of repose was analyzed by simulating the repose angle test. The results showed that the RFCP-P had a significant effect on the test results of the repose angle, and the RFCP-B had little effect on the test results of the repose angle. Therefore, the RFCP-P was calibrated using a single-factor test of repose angle, and the RFCP-B was calibrated using the repose angle test with soybean particles mixed with organic glass spheres. The accuracy of the calibration parameters was verified by rotating cylinder test and self-flow screening test.

We successfully prepared a dynamically oleophobic epoxy coating with low contact angle hysteresis (< 5.2?) for different low surface-tension liquids. Due to significant enrichment of covalently bonded polydimethylsiloxane (PDMS) at the coating surface, the obtained coating displays remarkable repellency against various low surfacetension liquids, including hexadecane, dodecane, decane, and soybean oil, as well as anti-smudge property and strong interfacial adhesion towards various substrates. Moreover, these excellent surface/interfacial properties have demonstrated to be very robust after being subjected to different environments (low pH, high pH, heating, and UV exposure). This type of coating may find promising applications in a broad range of fields where oil repellency is desired.

This paper investigated the problem of multi-target tracking (MTT) over a vehicle sensor network. A novel adaptive square root cubature joint probabilistic data association (ASRCJPDA) was proposed. Motivated by enhancing the stability of joint probabilistic data association (JPDA) in practical application, the proposed methodology implemented a numerically stabled cubature Kalman filter for JPDA state estimate process. It improved numerical stability and acquired more accurate estimated results. Additionally, enlightened by enhancing the real time efficiency of JPDA, an adaptive tracking gate designed for the JPDA measurement associate process was proposed. It combined with the kinematics of vehicle to reduce the computational complexity of data association, which improved the robustness of MTT in complex scenarios. The virtual vehicle target tracking scenarios were built in PreScan software in order to better simulate the real traffic condition. Simulations of target tracking examples are presented to show great effectiveness and superiority of the proposed method.