High-precision Simulation Research Articles

Impact of Future Development Scenario Selection on Landscape Ecological Risk in the Chengdu-Chongqing Economic Zone

The management of regional eco-environmental risks is the key to promoting regional economic sustainability from the macro level, and accurate evaluation of the evolutionary trends of regional ecological risk in the future is of high importance. In order to clearly identify the possible impact of future development scenario selection for the Chengdu-Chongqing Economic Zone (C-C E Zone) on the evolution of landscape ecological risk (LER), we introduced the Patch-generating Land Use Simulation (PLUS) model to simulate land use data for the C-C E Zone from 2030 to 2050 for two scenarios: natural development (ND) and ecological protection (EP). Based on the ecological grid and landscape ecological risk index (LERI) model, the landscape ecological risk (LER) evolutionary trends seen in the C-C E Zone from 2000 to 2050 were analyzed and identified. The results showed that: (1) The PLUS model can obtain high-precision simulation results in the C-C E Zone. In the future, the currently increasing rate of land being used for construction will be reduced, the declining rates of forest and cultivated land area will also be reduced, and the amount of land being used for various purposes will remain stable going into the future. (2) This study found that the optimal size of the ecological grid in the LERI calculation of the mountainous area was 4 × 4 km. Additionally, the mean values of the LERI in 2030, 2040, and 2050 were 0.1612, 0.1628, and 0.1636 for ND and 0.1612, 0.1618, and 0.1620 for EP. (3) The hot spot analysis results showed that an area of about 49,700 km2 in the C-C E Zone from 2000 to 2050 belongs to high agglomeration of LER. (4) Since 2010, the proportions of high and extremely high risk levels have continued to increase, but under the EP scenario, the high and extremely high risk levels in 2040 and 2050 decreased from 14.36% and 6.66% to 14.33% and 6.43%. Regional analysis showed that the high and extremely high risk levels in most regions increased over 2010–2050. (5) Under the ND scenario, the proportions of grids with decreased, unchanged, and increased risk levels were 15.13%, 81.48%, and 3.39% for 2000–2010 and 0.54%, 94.75%, and 4.71% for 2040–2050. These trends indicated that the proportion of grids with changed risk levels gradually decreased going into the future. This study analyzed the evolutionary trends of LER at the C-C E Zone for the ND and EP scenario. On the whole, the LER for the C-C E Zone showed an upward trend, and the EP scenario was conducive to reducing the risk. These research results can serve as a valuable data reference set for regional landscape optimization and risk prevention and control.

Metaheuristics Based Modeling and Simulation Analysis of New Integrated Mechanized Operation Solution and Position Servo System

Inadequate environmental protection is a problem, and to address it, the efficiency and quality grade of mechanical operations should be improved. A new comprehensive mechanized operation solution is proposed. The position control of a servo motor utilizing a PID (proportional, integral, derivative) controller and soft computing optimization approaches is explored in this paper. The essential technological realization techniques are reviewed and assessed, which serves as a reference for comprehensive mechanization solutions. The simulation model may be used to examine system features and explore control strategy by reflecting the characteristics of the actual system. A PID controller is designed by establishing a mathematical model based on the position servo system. It is verified that the PID control link is added to the pneumatic position servo control system. Through the comparison of the PID control experiment and PID control simulation data, the system can achieve high-precision position control, and the error is less than ±20 mm, meeting the requirements of rust removal and spraying design, and showing that the control system works stably and reliably to achieve high-precision simulation of the pneumatic position servo system.

Mechanical response and response mechanism of AlSi10Mg porous structures manufactured by laser powder bed fusion: Experimental, theoretical and numerical studies

In order to correctly understand the bearing capacity, failure mode and failure mechanism of AlSi10Mg porous optimized structures at different strain rates under compressive load, a series of experimental and simulative studies were carried out. Through quasi-static and modified Split Hopkinson Pressure Bar (SHPB) experiments, the damage failure modes of the AlSi10Mg porous structures with three different volume fractions are obtained at different strain rates. The stress-strain curves of AlSi10Mg porous structures obtained from the experimental results at different high strain rates show that its mechanical behavior is not sensitive to strain rates. Combined with meso-structure analysis and high-precision numerical simulation, it is found that the shear failure of AlSi10Mg porous structures due to relative dislocation along the inclined section under axial compressive load is the most direct cause of failure, which reveals its failure mechanism. Combining experimental research and theoretical analysis, the energy absorption characteristics and influencing factors of AlSi10Mg porous structures are determined at different strain rates. At the same time, the prediction models of dynamic elastic modulus and dynamic compressive strength of AlSi10Mg porous structures are constructed, which accurately describe the variation law between dynamic elastic modulus, dynamic compressive strength and structural volume fractions. These research works in this paper will provide an important reference for the structure optimal design of lightweight, strong energy absorption and impact resistance.

High-precision real-space simulation of electrostatically confined few-electron states

In this paper, we present a computational procedure that utilizes real-space grids to obtain high precision approximations of electrostatically confined few-electron states such as those that arise in gated semiconductor quantum dots. We use the full configuration interaction method with a continuously adapted orthonormal orbital basis to approximate the ground and excited states of such systems. We also introduce a benchmark problem based on a realistic analytical electrostatic potential for quantum dot devices. We show that our approach leads to highly precise computed energies and energy differences over a wide range of model parameters. The analytic definition of the benchmark allows for a collection of tests that are easily replicated, thus facilitating comparisons with other computational approaches.

A Novel Layered Slice Algorithm for Soil Heat Storage and Its Solving Performance Analysis

According to the structural and heat transfer characteristics of soil heat storage, a novel layered slice algorithm is proposed to realize the rapid and accurate solution to the problem. The heat transfer process between the double U-tube heat exchanger and the surrounding soil is taken as an example to analyze its solving performance. The study finds that the layered slice algorithm has higher simulation precision and faster solving speed. Its maximum relative error of temperature is only 0.19%. Compared with the traditional 3D simulation algorithm, it can accelerate about 2.2~2.56 times. At the same time, the layered slice algorithm has an excellent parallel characteristic. Its maximum parallel speedup ratio is more than twice that of the traditional 3D algorithm. Due to the superior solving performance, the proposed algorithm can help the optimization design of the buried-tube heat exchangers.

Fine corrections in the effective string describing SU(2) Yang-Mills theory in three dimensions

We present a study of the effective string that describes the infrared dynamics of SU(2) Yang-Mills theory in three dimensions. By combining high-precision lattice simulation results for Polyakov-loop correlators at finite temperatures close to (and less than) the deconfinement one with the analytical constraints from renormalization-group arguments, from the exact integrability of the two-dimensional Ising model that describes the universality class of the critical point of the theory, from conformal perturbation theory, and from Lorentz invariance, we derive tight quantitative bounds on the corrections to the effective string action beyond the Nambu-Gotō approximation. We show that these corrections are compatible with the predictions derived from a bootstrap analysis of the effective string theory, and have a value which does not allow to prove the Axionic String Ansatz for this model.

A joint standard-exceeding risk assessment of multiple pollutants based on robust geostatistics with categorical land-use type data: A case study of soil nitrogen and phosphorus

Joint standard-exceeding risk and its spatial uncertainty of soil available nitrogen (AN) and available phosphorus (AP) under the specific constraints are essential for guiding the joint regulation of pollutants but were rarely considered by previous studies. Moreover, traditionally-used spatial simulation models are not only non-robust but also ignoring valuable categorical information (e.g., land-use types), which may hinder the acquisition of high-precision spatial simulation results. This study first established optimally robust semi-variogram estimators to identify the spatial outliers of soil AN and AP in Jintan County, China. Then, robust sequential Gaussian simulation (RSGS) with land-use types (RSGS-LU) was proposed and further compared with RSGS, SGS-LU, and SGS in the spatial simulation accuracy. Last, a joint standard-exceeding probability model under the specific constraints was proposed, and the corresponding high-risk areas were delineated for the joint regulation of soil AN and AP. Results showed that: (i) 23 and 17 spatial outliers were identified for soil AN and AP, respectively; (ii) removing outliers or combining land-use types could improve the spatial simulation accuracy of soil AN and AP; (iii) RSGS-LU generated the highest spatial simulation accuracy for both soil AN and AP; (iv) the area with the joint standard-exceeding (AP > 30 mg kg−1∪ AN > 130 mg kg−1) probability >75% accounted for 9.98% of the county's area; (iv) the area with the joint standard-exceeding (AP > 30 mg kg−1∩ AN > 130 mg kg−1) probability >75% accounted for 2.29% of the county's area. It is concluded that RSGS-LU and joint standard-exceeding probability model under the specific constraints could provide more accurate and flexible spatial decision support for the joint regulation of soil AN and AP at a regional scale. Moreover, the methods recommended in this study also provide valuable tools for the joint standard-exceeding risk assessment of other multiple soil pollutants.

Nonlinear Modeling of Dynamic Characteristics of Pump-Turbine

Hydropower is a kind of clean energy, which can effectively reduce the consumption of fossil energy and is one of the main fields of new energy development. Pumped storage power station not only provides a solution for storing electric energy and generating excess, but also is a clean, efficient, economical and safe power system regulation method with high quality. Accurate modeling of a pump-turbine, as the core equipment of a pumped storage unit, is the key to safe and stable operation of the pumped storage unit. At present, a method of simplifying the external characteristics of a pump-turbine into a first-order linear model is widely used, which cannot effectively and accurately reveal the nonlinear dynamic characteristics of the unit in transition process. In order to meet the demand of high-precision simulation of the unit, a new method of identifying Taylor series expansion considering nonlinearity based on the torque characteristic formula and the flow characteristic formula is proposed, which is applied to the pump-turbine external characteristic model, and retains the second derivative term, making the model a second-order nonlinear model, and thus, the pump-turbine model becomes a nonlinear model. The nonlinear model established is used to simulate the load increase and load rejection of the unit, and the results are compared with those for the linear model. The comparison shows that the nonlinear model established for the pump-turbine can reveal the dynamic response of the unit more effectively and accurately than the linear model, and provide a further guarantee for the safe and stable operation of pumped-storage units, which is of great significance to hydropower energy development.

Design and practice of a platform for monitoring, early-warning and simulation of algal blooms in Lake Chaohu

近20年来，巢湖蓝藻水华频繁暴发，对流域内居民生活和社会生产产生了严重影响.由于缺乏蓝藻水华全方位监测、高精度模拟和智能化分析手段，传统方法难以实现现状掌握、异常识别、原因追溯、未来模拟的目标，无法满足巢湖蓝藻水华科学防控与应急处置的要求，蓝藻水华引起的突发事件随时可能发生.本文针对巢湖蓝藻水华的全面监测和应急决策问题，整合了卫星遥感、无人机监测、视频监控、浮标监测和人工巡测手段，构建了巢湖水质和水华全方位监测网络；结合巢湖水动力-水质-藻类耦合模拟模型，研制了蓝藻水华预测预警和蓝藻水华暴发应急处置模块，实现了蓝藻水华短期（未来2日逐时）和长期（未来7日逐日）模拟，并实现了未来5日蓝藻水华沿岸堆积模拟.最终，通过集成巢湖水质和水华监测、预测预警、应急处置等模块，研发了巢湖蓝藻水华监测预警与模拟分析平台，实现了全湖水质和水华现状迅速掌握、超标信息自动识别与高精度预测预警、沿岸重点区域水华堆积风险评估等功能，为巢湖蓝藻水华的科学防控和应急处置提供了科学依据和数据支撑.;Algal blooms occur frequently in Lake Chaohu in recent 20 years, producing a serious impact on the resident life and social production in Lake Chaohu watershed. Due to the lack of effective means in terms of comprehensive monitoring, high-precision simulation, and intelligent analysis, it is quite difficult for traditional methods to achieve the goal of status mastering, anomalies identifying, causes tracing, and trend simulating of water quality and algal blooms. Accordingly, the requirements of scientific prevention and emergency disposal of algal blooms in Lake Chaohu cannot be satisfied currently, and emergencies caused by algal blooms may occur at any time. Aiming at the requirements of comprehensive monitoring and emergency decision-making of algal blooms, a comprehensive monitoring network of water quality and algal blooms has been established in Lake Chaohu, by integrating several monitoring means, i.e., satellite remote sensing, UAV (unmanned aerial vehicle) monitoring, video monitoring, buoy and field monitoring. And modules of prediction, early-warning and emergency response of algal blooms are developed by combining the coupled hydrodynamic-water quality-algal blooms model. And both short-term (hourly in the next 2 days) and long-term (daily in the next 7 days) simulations of algal blooms are realized, as well as the simulation of algal blooms accumulation along the coast in the next 5 days. Finally, a platform for monitoring, early-warning and simulation of algal blooms in Lake Chaohu has been developed by integrating several function modules, e.g., monitoring of water quality and algal blooms, prediction and early-warning, emergency response, etc. By running this platform, the present situation, exceding standard limits information, and high-precision simulation and prediction of water quality and algae bloom in the whole lake can be grasped quickly and automatically, and risk assessment of algae bloom accumulation in key areas along the coast can also be realized. It shows that the implemented platform can provide scientific basis and data support for scientific prevention and emergency disposal of algal blooms in Lake Chaohu.

An Improved Two-Scale Model for Sea Surface Scattering in the Transition Range of Incidence Angles

An improved two-scale model (I-TSM) for the incidence angle transition range (5-11°) is proposed by analyzing the contributions of both quasi-specular and Bragg scatterings to the total sea surface scattering. With normalized radar cross section (NRCS) products of surface wave investigation and monitoring (SWIM) instrument, the mean square slope (MSS) and reflection coefficient of the geometrical optics (GO) model are modified to simulate the quasi-specular scattering in I-TSM, and a Bragg scattering contribution factor adaptive to the incidence angle and wind speed is fitted to provide the Bragg scattering component for I-TSM. At different incidence angles and wind speeds, I-TSM combines the quasi-specular and Bragg scatterings in variable proportions by the fitting factor. I-TSM avoids the critical angle selection and separation problems of the traditional TSM in the incidence angle transition range. Compared with the GO model and traditional TSM, I-TSM has significantly higher accuracies with root mean square error (RMSE) of 0.309dB, relative error (RE) of 2.019% and scattering index (SI) of 0.03 when SWIM NRCS products are the standard data in the validation. I-TSM will provide high-precision NRCS simulation data in the incidence angle transition range for scattering characteristics analysis and echo simulation of SWIM.

A symbiosis between cellular automata and dynamic weighted multigraph with application on virus spread modeling

The pattern of coronavirus spread at different geographical scales verifies that travel or shipment by air, sea or road are potential to transmit viruses from one location to somewhere far away in a very short time. Simulation and analysis of such a situation requires the development of models that support long distance transmission of viruses. Cellular Automata (CA) are a family of spatiotemporal computational models frequently employed in analysis of biomedical systems. A CA consists of a topological combination of units called cells as well as a transition function that propagates the configuration of cells locally and step by step. In this paper, we first present some patterns that show the local interaction between CA cells is not sufficient for virus spread modeling, especially at large spatial scales. Then, we generalize the concept of CA by providing a symbiosis between the neighborhood relationship of cells and the transmission channels represented by a dynamic weighted multigraph. Furthermore, we characterize the capabilities of the proposed modeling tool in simulation of the virus spread, and estimating the risk control during the movement restrictions and related health protocols. Finally, we simulate the coronavirus outbreak in the five study areas including three states and two countries. Our experiments using the proposed model verify that the proposed model is capable of formulating different ways of virus transmission, including long-distance transmission, and supports high-precision simulation of the pandemic.

Optimization and realization on the coordination control strategy for auxiliary power unit of range-extended electric vehicle

The auxiliary power unit (APU) is a major power source of range-extended electric vehicle (R-EEV). Excellent coordination control strategy of APU has a great significance impact on improving the overall electrical control system performance of R-EEV. A coordination control strategy based on parameters adapt fuzzy-PID is proposed to ensure the dynamic and static response characteristics of the coordination control system. Firstly, the APU high precision simulation control model is built in GT-Power and Matlab-Simulink. Three coordination control strategies based on traditional PID control method are designed, namely, engine speed control model (ESCM), generator torque control model (GTCM), and APU speed-torque control model (AS-TCM). The three coordination control strategies are simulated on working conditions, which include start-up working condition, power raised working condition, and power reduced working condition. Combined with the PID control principle, the control performance and inherent limitations of three traditional PID control strategies (TPCS) are analyzed and compared. Then, according to the above simulation results of analysis and comparation, the parameters adapt fuzzy-PID control strategy (PAF-PCS) is designed and simulated. The results show that three control parameters ( kp, ki, kd) are changed in real time to ensure the flexibility and adaptability of the control system and improve the stability and robustness of control system. Finally, the results of bench test show that power responds quickly and no oscillation and fixed-point power generation works smoothly, which are basically consistent with the simulation results. Therefore, the PAF-PCS proposed in this paper has good feasibility and effectiveness.

Neural-network-based method for improving measurement accuracy of four-quadrant detectors.

Due to the high accuracy and fast response, measurement systems based on four-quadrant detectors (4QDs) are widely used. There is a non-linear relationship between the output signal offset (OSO) of the 4QD and the actual spot position, resulting in limited measurement accuracy. Existing methods improve detection accuracy by collecting large amounts of data and approximating the OSO curve. On one hand, they require much difficult-to-obtain real data; on the other hand, the accuracy of the fit using specific functions is limited. To address this issue, this paper proposes a neural-network-based method for improving the measurement accuracy of 4QDs. Compared to existing methods, the proposed method significantly improves measurement accuracy with a small amount of real data. To obtain sufficient data to train the neural network, we first propose a method for generating large amounts of high-precision simulation data. Then, specifically for the 4QD-based measurement system, we construct a backpropagation neural network. Finally, based on a large amount of simulation data and a small amount of real data, we design a new training strategy to train a high-precision measurement network. The experimental results show that the proposed method can significantly improve measurement accuracy with less real data and has extensive application value.

Construction and application of a high precision 3D simulation model for geomechanics of the complex coal seam

The high-precision 3D simulation model for geomechanics of a complex coal seam is the necessary premise for the research on intelligent shearer and unmanned mining. However, at present, a simulation model for geomechanics of a complex coal seam generally has the problems of simplifying complex geological structures and low accuracy for structures. In order to meet the needs of a coal seam simulation model in the mining process of an intelligent shearer, it is necessary to optimize the simplified model of a coal seam. Therefore, based on a 3D simplified simulation model constructed with discrete element technology, the complex coal seam application plug-in was compiled with the help of an Application Program Interface. Moreover, according to the geological characteristics, new attributes were added to the structures to complete the construction of the model of a complex coal seam. Finally, the model was verified with laboratory experiments. The results showed that the high-precision 3D simulation model for geomechanics of a complex coal seam effectively improved the accuracy of the modeling. The real-time transmission and the real-time sharing of multi-source data were realized by considering the 3D simulation model for geomechanics of a complex coal seam as the core. Additionally, the purpose of the real-time sensing of the coal cutting state was achieved in order to lay the foundation for the realization of unmanned mining.

Review of Artificial Neural Network and Its Application Research in Distillation

With the development of rectification technology, the scale of its production equipment has continued to expand, and its calculation requirements have become more complex. The use of traditional optimized control methods can no longer meet the requirements. Artificial neural networks imitate the human brain for self-learning and optimization, intelligently process various complex information, and have been widely used in various chemical processes. Because the artificial neural network has the advantages of self-learning, associative storage, and high-speed search for optimized solutions, it can perform high-precision simulation and prediction of rectification operations, and has been widely used in the optimal control of rectification towers. This article gives a basic overview of artificial neural networks, and introduces the application research of artificial neural networks in distillation at home and abroad.

Modeling viscoacoustic wave propagation using a new spatial variable-order fractional Laplacian wave equation

We have developed a new time-domain viscoacoustic wave equation for simulating wave propagation in anelastic media. The new wave equation is derived by inserting the complex-valued phase velocity described by the Kjartansson attenuation model into the frequency-wavenumber domain acoustic wave equation. Our wave equation includes one second-order temporal derivative and two spatial variable-order fractional Laplacian operators. The two fractional Laplacian operators describe the phase dispersion and amplitude attenuation effects, respectively. To facilitate the numerical solution for our wave equation, we use the arbitrary-order Taylor series expansion (TSE) to approximate the mixed-domain fractional Laplacians and achieve the decoupling of the wavenumber and the fractional order. Then, our viscoacoustic wave equation can be directly solved using the pseudospectral method. We adopt a hybrid pseudospectral/finite-difference method (HPSFDM) to stably simulate wave propagation in arbitrarily complex media. We validate the high accuracy of our approximate dispersion term and approximate the dissipation term in comparison with the accurate dispersion term and accurate dissipation term. The accuracy of the numerical solutions is evaluated by comparison with the analytical solutions in homogeneous media. Theory analysis and simulation results indicate that our viscoacoustic wave equation has higher precision than the traditional fractional viscoacoustic wave equation in describing constant- Q attenuation. For a model with Q < 10, the calculation cost for solving the new wave equation with TSE HPSFDM is lower than that for solving the traditional fractional-order wave equation with TSE HPSFDM under the high numerical simulation precision. Furthermore, we examine the accuracy of HPSFDM in heterogeneous media using several numerical examples.

Shedding vortex simulation method based on viscous compensation technology research

Owing to the influence of the viscosity of the flow field, the strength of the shedding vortex decreases gradually in the process of backward propagation. Large-scale vortexes constantly break up, forming smaller vortexes. In engineering, when numerical simulation of vortex evolution process is carried out, a large grid is needed to be arranged in the area of outflow field far from the boundary layer in order to ensure the calculation efficiency. As a result, small scale vortexes at the far end of the flow field cannot be captured by the sparse grid in this region, resulting in the dissipation or even disappearance of vortexes. In this paper, the effect of grid scale is quantified and compared with the viscous effect through theoretical derivation. The theoretical relationship between the mesh viscosity and the original viscosity of the flow field is established, and the viscosity term in the turbulence model is modified. This method proves to be able to effectively improve the intensity of small-scale shedding vortexes at the far end of the flow field under the condition of sparse grid. The error between the simulation results and the results obtained by using fine mesh is greatly reduced, the calculation time is shortened, and the high-precision and efficient simulation of the flow field is realized.

Development of a Chemical-Kinetic Mechanism of a Four-Component Surrogate Fuel for RP-3 Kerosene.

RP-3 kerosene is the most widely used aviation kerosene in China, and research on its chemical-kinetic mechanism is significant for understanding the combustion characteristics. Based on a novel four-component surrogate fuel consisting of n-dodecane, 2,5-dimethylhexane, 1,3,5-trimethylbenzene, and decalin (54, 22, 14, and 10% by mole), the detailed chemical-kinetic mechanism of the corresponding RP-3 surrogate fuel with 1333 species and 6803 reactions has been developed and then reduced to 145 species and 818 reactions for high-temperature conditions. After that, the merged surrogate mechanism of surrogate fuel was validated by various experimental data sets for each individual surrogate component. Then, the surrogate mechanism was validated by comparing the simulation and experimental data of the ignition delay times, species concentrations in a jet-stirred reactor, and laminar flame speeds. Good agreements between simulations and experiments were observed. In addition, using the sensitivity analysis method, the key reactions of RP-3 surrogate fuels were compared and analyzed. In summary, the mechanism developed in this study can accurately predict the ignition, oxidation, and flame propagation characteristics of RP-3 aviation kerosene. The novel surrogate model can help deeply understand the combustion characteristics of RP-3 aviation kerosene, and it is used for high-precision numerical simulation of combustion reaction flow.

Study on rough surfaces: A novel method for high-precision simulation and interface contact performances analysis

Surface morphology of the components is a key factor that influences the quality and performance of precision systems. The influence of different morphologies on the contact performance of mating surfaces may be studied by simulating a real rough surface and calculating the contact performance. First, the micro-geometric characteristics of the surfaces of the machined parts are measured by a 3D surface profilometer (NV5000 5022S), and the distribution law of the surface micro-geometric characteristics is obtained by statistical and characterization methods. Second, the rough surface conforming to this law is simulated by a non-Gaussian mathematical algorithm, and the contact model between the mating parts with micro-geometric characteristics of the simulated surface is reconstructed using reverse engineering. Finally, the mechanical properties of the mating surfaces are obtained using a numerical algorithm based on Yoshimura's integral method and tests. The comparison of mechanical properties obtained from numerical analysis and test shows that the maximum errors in the contact stiffness obtained by the two methods are 9.4% (grinding surface) and 11.5% (milling surface), respectively. Therefore, it is feasible to use a non-Gaussian simulation method and Yoshimura's integral method to realize an effective simulation of the micro-geometric characteristics of the surface and the analysis of the contact performance of the mating surface respectively. The results obtained from this study is thus important as a reference for the analysis of the surface morphology and mechanical properties between the matching parts.

Discrete Element Simulation Based on Elastic–Plastic Damping Model of Corn Kernel–Cob Bonding Force for Rotation Speed Optimization of Threshing Component

Current corn kernel-cob bonding mechanics models (LSD models) uniformly consider the bonding force changes during the maize threshing operation as an elastic change, resulting in computational errors of up to 10% or more in discrete element simulations. Due to the inability to perform high-precision discrete element simulation of the mechanics characteristics during the corn threshing operation, the core operating parameters of the corn thresher (rotation speed of the threshing component) rely mainly on empirical settings, resulting in a consistent difficulty in exceeding 85% of the corn ear threshing rate. In this paper, by testing the mechanics characteristics of corn kernels, the bonding force is found to have both elastic and plastic changes during the threshing process. An elastic–plastic (EP) damping model of the corn kernel–cob bonding force was established by introducing a bonding restitution coefficient e to achieve an integrated consideration of the two changes. By testing the relationship between the properties of the corn ear itself and the model parameters, the pattern of the effect of the corn ear moisture content and the loading direction of the ear by force on the EP model parameters was found. By establishing a model of the relationship between the corn cob’s own properties and the model parameters, the EP model parameter values can be determined by simply determining the moisture content of the ear. In this paper, the EP model was established and the high-precision simulation and analysis of the process of bonding force variation between corn kernel and cob is realized on the self-developed AgriDEM software. At the meantime, the optimal values of the threshing component rotation speed under different conditions of moisture content of corn ear were obtained by establishing an optimization model of threshing component rotation speed. The test results showed that the corn ear threshing rate could reach more than 92.40% after adopting the optimized speed value of the threshing component in this paper. Meanwhile, the test results showed that the discrete element simulation results based on the EP model did not significantly differ from the measured results of the thresher. Compared with the most widely used LSD model, the EP model can reduce the computational error by 3.35% to 6.05%.