Discrete Simulation Model Research Articles

Calibration of Discrete Element Simulation Parameters and Model Construction for the Interaction Between Coastal Saline Alkali Soil and Soil-Engaging Components

There are approximately 36.7 million hectares of saline alkali land available in China. To enhance the comprehensive utilization value of coastal saline alkali land and boost crop yields in such areas, it is essential to conduct research on optimizing the operational performance of high-performance soil contact components in light of the soil characteristics of coastal saline alkali land. Discrete element simulation can be employed to investigate the operational mechanisms of various key components. Nevertheless, at present, there is a dearth of discrete element models for the key physical parameters and soil structure of coastal saline alkali land soil. In this article, typical coastal saline alkali field soil was sampled, and the physical properties of the saline alkali soil, including salt content, moisture content, particle size distribution, and particle size, as well as intrinsic parameters such as soil compaction, density, Poisson’s ratio, and shear modulus, were measured. The Hertz Mindlin with Bonding contact model was employed. Physical experiments on soil accumulation angles at different depths were carried out using the cylindrical lifting method. Subsequently, by means of the discrete element method and the BBD experimental design method, a response surface model was established, and an optimization analysis was performed on the optimal parameters for the soil–soil collision recovery coefficient, static friction coefficient, and dynamic friction coefficient at each depth. Test benches for measuring the collision recovery coefficient, static friction coefficient, and rolling friction coefficient of saline alkali soil at -65Mn were set up, calculation formulas for each parameter were derived, and the contact parameters between soil at different depths and 65Mn were obtained. The results of the sliding friction angle test on different depths of saline alkali soil at -65Mn were further verified using the discrete element method, with a maximum error of 3.11%, which falls within the allowable range. This suggests that the calibration results of the discrete element simulation parameters for the interaction between soil and contact components are reliable, providing data and model support for future research on enhancing the operational performance of high-performance contact components.

Examining the potential impact of universal basic income on labor supply: Focusing on the South Korean models

AbstractOne of the most contentious facets of universal basic income (UBI) debates revolves around its impact on labor supply. Against this backdrop, this study aims to replicate how labor supply responds to changes in net income caused by the implementation of UBI. Using data from the 15th wave of the National Survey of Taxes and Benefits (N = 9342) and a discrete choice simulation model, this study estimated labor supply outcomes under two specific UBI models. The results suggest that UBI exerts minimal negative effects on labor supply among full‐time and part‐time workers and appears to encourage labor force entry among unemployed individuals. These findings offer empirical evidence on UBI's effects, suggesting it may support labor participation without substantial disincentives for employment.

A transient source-function-based embedded discrete fracture model for simulation of multiscale-fractured reservoir: Application in coalbed methane extraction

The classic embedded discrete fracture model (EDFM) may cause certain errors when simulating the transient flow process within the multi-scale fractured system. In this study, the transient transmissibility was derived by using the point (matrix-fracture) and line (fracture-fracture) source functions. The transient source-function-based EDFM (tSEDFM) is established via this method. Then, based on the dual criteria that dNNC is less than a certain distance and its projection point is within the corresponding fracture domain, a 3D fracture meshing method for arbitrary fracture geometry and orientation is established. The finite volume method is used to discrete the fluid flow equations for matrix and fracture systems, considering the multi-deformation-induced permeability evolution. Consequently, the numerical simulation framework of FVM-tSEDFM is proposed to investigate the transient mass transfer characteristics. Compared with the current pEDFM, the pressure drop near fractures of the proposed model is higher and the gap narrows as pressure wave further spreads. Compared with AEDFM, the Tmf of tSEDFM is almost the same, but AEDFM's Tff is substantially higher in the initial stage and the attenuation rate is slower, resulting in an error of nearly 15% at the hydraulic fracture location. As fracture density increases, more transient flow makes AEDFM- and EDFM-calculated BHP values deviate from tSEDFM. History matching using the tSEDFM with only 10000 meshes shows better results where the mismatching rate is larger than 90%. Simulation of CBM extraction indicate that sharp pressure decline occurs near the fractures, resulting in gas desorption enhancement and rapid productivity increment. The tSEDFM demonstrates good practicality in calculating the production and long-term permeability evolution. Results also show that the tSEDFM can correct the underestimation of mass exchange in the early stage and overestimation since the pseudo-steady stage, and can be better applied to the numerical simulation of multi-scale fractured reservoirs. As the dominant factor for gas extraction, sensitivity analyses of fracture properties are also documented.

Analyzing Passenger Flows in an Airport Terminal: A Discrete Simulation Model

This paper introduces a simulation model designed as a decision-making tool to assess and analyze various crowd management strategies with a focus on enhancing sustainability in airport operations. This model specifically addresses the challenges and risks associated with managing passenger flows within airport terminals. By simulating different scenarios, the model aims to provide valuable insights into how to effectively handle crowd dynamics and enhance overall terminal efficiency, safety, and sustainability. This case study was conducted at Henri Coanda International Airport, ARENA 12 simulation software being used in order to model the passenger flows within the airport terminal. Two scenarios were considered: The first one involves maintaining a fixed number of security and check-in desks for the two airline groups. In contrast, the second scenario allows for a variable number of security and check-in desks for the same airline groups. By optimizing resource allocation and minimizing waiting time, this model contributes to more sustainable airport management operations. Three measures of performance (MOPs) were selected to assess the system activity: the average passenger waiting time, the average passenger number queue length, and the average utilization rate. Comparing the results, we concluded that the second scenario shows a relative improvement in almost all performance measures when compared to the first scenario.

Study on the Characteristics of Residual Film–Soil–Root Stubble Complex in Maize Stubble Fields of the Hexi Corridor and Establishment of a Discrete Element Model

Plastic film mulching is one of the key technologies for improving agricultural productivity in arid and semi-arid regions. However, residual plastic film can severely disrupt the structure of the topsoil in farmland, leading to a decrease in crop yield. The Hexi Corridor, as the largest seed maize production base in the arid regions of Northwest China, is facing an increasingly prominent issue of residual plastic film recovery. This study designed experiments based on the typical maize planting model in the Hexi Corridor. A discrete element simulation model of the residual film–soil–root stubble complex was established using the Bonding-V2 model and API rapid filling technology. The reliability of the simulation model was verified through shear and puncture tests. The study revealed that the soil type in the Hexi Corridor is heavy sandy soil. The differences between the average maximum shear forces in the simulated and actual shear tests for root stubble–soil complexes at depths of 30 mm, 50 mm, and 100 mm were 4.8%, 6.4%, and 6.5%, respectively. Additionally, the differences in the average maximum vertical loading forces in the simulated and actual puncture tests for root stubble–soil complexes at depths of 50 mm and 100 mm were 6.4% and 12.37%, respectively. The small discrepancies between the simulated and actual values, along with the consistency of particle movement trends with real-world conditions, confirmed the reliability and accuracy of the simulation model. This indicates that the established discrete element flexible model can effectively represent actual field conditions, providing discrete element model parameters and theoretical support for optimizing the design of key components in China’s mechanized root stubble handling and residual film recovery machinery.

Simulacija procesa izdavanja uporabne dozvole

In this paper, a discrete simulation model was developed for the certificate of occupancy (CO) for certain buildings issuance process in the Republic of Croatia. The model demonstrates the multistage nature of the process, with site inspections being the most time-consuming stage and a potential bottleneck. The model also shows that senior professional associates have the highest workloads. A what-if analysis was conducted to simulate the failure of the eDozvola system and to demonstrate the significant impact of such an interruption. A cost analysis of the CO issuance process demonstrated the potential for cost savings and efficiency gains through process optimization. Thus, simulation modelling can significantly improve the CO issuance process, resulting in cost savings, increased efficiency, greater stakeholder satisfaction, and better decision-making.

Pemodelan Dinamis Proses Produksi Batch Satu Tahap Dalam Satu Mesin Dengan Memperhatikan Waktu Loading dan Waktu Proses

In the batch process, the company uses the same process facilities to produce various types of products. This allows businesses to change production in response to changes in market demand. Batch processes are widely used in industry. In many cases, batch processes provide several benefits over continuous processes, especially when the industry wants to ensure and maintain the quality standards of its products. This paper proposes a behavioral model of a single-stage batch processing system, using the language of system dynamics. When run, the behavioral model will provide an overview of how the system behaves. The system dynamics language is a formulation of a system of ordinary differential equations that is extracted from the real system being studied, in the form of a stock and flow diagram. The computation of this diagram is further implemented using software. Because it is actually a calculus method, the system dynamics language provides output data much faster than discrete simulation modeling. In this paper, the system behavior modeled is mainly loading, processing and unloading activities. The verification results carried out by testing it on two different case examples show that the model can sufficiently describe the behavior of the conceptual system logically so that the model can enrich experimental tool options related to batch production processes in the future.

Deep Reinforcement Learning and Discrete Simulation-Based Digital Twin for Cyber–Physical Production Systems

One of the goals of developing and implementing Industry 4.0 solutions is to significantly increase the level of flexibility and autonomy of production systems. It is intended to provide the possibility of self-reconfiguration of systems to create more efficient and adaptive manufacturing processes. Achieving such goals requires the comprehensive integration of digital technologies with real production processes towards the creation of the so-called Cyber–Physical Production Systems (CPPSs). Their architecture is based on physical and cybernetic elements, with a digital twin as the central element of the “cyber” layer. However, for the responses obtained from the cyber layer, to allow for a quick response to changes in the environment of the production system, its virtual counterpart must be supplemented with advanced analytical modules. This paper proposes the method of creating a digital twin production system based on discrete simulation models integrated with deep reinforcement learning (DRL) techniques for CPPSs. Here, the digital twin is the environment with which the reinforcement learning agent communicates to find a strategy for allocating processes to production resources. Asynchronous Advantage Actor–Critic and Proximal Policy Optimization algorithms were selected for this research.

Research on an Accurate Simulation Modeling and Charge Motion Quantitative Evaluation Method for Ball Mill in Confined Space

A ball mill is a type of complex grinding device. Having knowledge of its charge-load behavior is key to determining the operating conditions that provide the optimum mill throughput. An elaborate description of the charge movement inside the ball mill is essential. This study focuses on a laboratory-scale ball mill and utilizes a discrete element simulation model to investigate the impact of mill speed and ball filling on charge-load behavior. Initially, the EDEM 2.7 (Engineering Discrete Element Method) software contact parameters were calibrated through heap-angle experiments. Subsequently, four charge-motion characteristic parameters were defined and analyzed based on Powell’s theory to understand the variations in charge-load behavior. This research proposes a theoretical calculation model for predicting power in a ball mill, highlighting the significance of the CoC (Center of Circulation) and CoM (Center of Mass) in reflecting changes in charge-load behavior. The theoretical model for mill-power prediction is effective and aligns well with the EDEM simulation and experimental results, providing valuable insights for optimizing large-scale ball mill structures and controlling charge motion during production.

Numerical simulation method of seed pelletizing: Increasing seed size by powder adhesion

Seed pelletizing can effectively increase the seed size. However, observing the microscopic process of seed pelletizing using physical tests is challenging. This study used the discrete element method (DEM) to simulate the process. Discrete elemental simulation models and contact parameters of seed and powder had been determined by particle scaling theory and parameter calibration tests, respectively. The contact model (modified model) between the seed and powder was established, which could effectively characterize the effect of the water addition on the viscosity. The seed pelletizing numerical simulation test was carried out with the average number of contact particles as the main evaluation index. The results showed that the amount of powder adhering to the surface of individual seeds was 43. Bench test results show that the quality of pelletized seeds met relevant criteria. KeywordsDiscrete element method (DEM)Numerical simulationSeed pelletizingContact modelRepose angle

Material Removal Mechanism of SiC Ceramic by Porous Diamond Grinding Wheel Using Discrete Element Simulation.

SiC ceramics are typically hard and brittle materials. Serious surface/subsurface damage occurs during the grinding process due to the poor self-sharpening ability of monocrystalline diamond grits. Nevertheless, recent findings have demonstrated that porous diamond grits can achieve high-efficiency and low-damage machining. However, research on the removal mechanism of porous diamond grit while grinding SiC ceramic materials is still in the bottleneck stage. A discrete element simulation model of the porous diamond grit while grinding SiC ceramics was established to optimize the grinding parameters (e.g., grinding wheel speed, undeformed chip thickness) and pore parameters (e.g., cutting edge density) of the porous diamond grit. The influence of these above parameters on the removal and damage of SiC ceramics was explored from a microscopic perspective, comparing with monocrystalline diamond grit. The results show that porous diamond grits cause less damage to SiC ceramics and have better grinding performance than monocrystalline diamond grits. In addition, the optimal cutting edge density and undeformed chip thickness should be controlled at 1-3 and 1-2 um, respectively, and the grinding wheel speed should be greater than 80 m/s. The research results lay a scientific foundation for the efficient and low-damage grinding of hard and brittle materials represented by SiC ceramics, exhibiting theoretical significance and practical value.

Analysis of Solvent‐Free Intensive‐Dry‐Mixed NMC‐Based Lithium‐Ion Battery Cathodes: Numerical Investigations on Performance Determinants

AbstractA numerical investigation on the implications of intensive‐dry mixing on the resulting cathode microstructure and hence, the electrochemical performance has been presented in this contribution. In this regard, characterization as well as scale‐resolving electrochemical performance simulations were carried out. The basis for these numerical investigations were computer generated cathode geometries, generated by means of a discrete element method simulation model, presented in our previous work. Consequently, three different stages of comminution of the conductivity additive during intensive dry mixing with nickel rich active material were incorporated into computational half cells and classified based on the simple quality parameter, bulk density. Furthermore, the possible coating phenomenon occurring during the process, to which the bulk density measurements are not susceptible, was modelled with the help of a numerical parameter called the coating factor. It was found that bulk density of cathode blends, which is a rather trivial parameter to measure from intensive dry mixed blends, could be strongly correlated to cathode performance under the consideration of solvent free manufacturing. The findings suggest that, while considering limited volume during cell design, higher bulk density of dry cathode components delivers the best performance under higher energy and low current conditions. At high power and high current condition however, a compromise between energy and power dictates the choice. Conversely, if the material mass is the constraining factor, the lower bulk density tends to perform the best due the best utilisation of the available energy.

小区小麦联合收获机割台清理离散元仿真参数标定

The analysis of the clearing process of the cutting deck of a small plot wheat combine harvester requires the use of discrete element simulation methods. However, the current simulation test lacks the contact parameters such as wheat stalk and stalk-seed. In this paper, the wheat stalks and seeds at harvest time were taken as the research objects, and the calibration study of the discrete element simulation model parameters of stalks and stalk-seeds was carried out by means of mechanical test determination and EDEM software simulation. The stiffness coefficients of wheat stalks were determined by mechanical tests; the average values of wheat stalk stacking angle of 39.22° and wheat stalk-seed stacking angle of 44.41° were obtained by stacking angle tests. By the steepest climb test and binary regression test, the stalk normal stiffness coefficient was determined to be 5e+08N/m2 and tangential stiffness was determined to be 6.35e+08N/m2; the stalk-stalk collision recovery coefficient was obtained to be 0.551, static friction coefficient was obtained to be 0.797, and rolling friction coefficient was obtained to be 0.079 by the two-level analytical factorization test, the steepest climb test, and the three-factor response surface test. Based on this, the average value of wheat stalk-seed stacking angle was obtained to be 39.22° and the average value of wheat stalk-seed stacking angle was obtained to be 44.41° by the stacking angle test. On this basis, the coefficient of recovery of stalk-stalk collision was 0.434, the coefficient of static friction was 0.884, and the coefficient of rolling friction was 0.339 obtained by the three-factor response surface test. Three validation experiments were carried out by substituting the obtained parameters into the simulation test, and the error values were close to the error value %0.255 in the model, which proved that the experimental data were reliable.

Calibration and Testing of Parameters for the Discrete Element Simulation of Soil Particles in Paddy Fields

The parameters of the discrete element simulation model for rice field soils serve as valuable data references for investigating the dynamic characteristics of the walking wheel of high-speed precision seeding machinery in paddy fields. The research specifically targets clay loam soil from a paddy field in South China. Calibration of essential soil parameters was achieved using EDEM_2022 software (and subsequent versions) discrete element simulation software, employing the Edinburgh Elasto-Plastic Adhesion (EEPA) nonlinear elastic-plastic contact model. The tillage layer and plough sub-base layer underwent calibration through slump and uniaxial compression tests, respectively. Influential contact parameters affecting slump and axial pressure were identified through a Plackett–Burman test. The optimal contact parameter combinations for the discrete element model of the tillage layer and plough sub-base layer were determined via a quadratic rotational orthogonal test. The accuracy of the discrete element simulation model’s parameters for paddy field soils was further validated through a comparative analysis of the simulation test’s cone penetration and the field soil trench test. Results indicate that the Coefficient of Restitution, surface energy, Contact Plasticity Ratio, and Tensile Exp significantly influence slump (p < 0.05). Additionally, the Coefficient of Restitution, Contact Plasticity Ratio, coefficient of rolling friction, and Tangential Stiff Multiplier significantly impact axial pressure (p < 0.05). Optimal contact parameters for the plough layer were achieved with a particle recovery coefficient of 0.49, a surface energy of 18.52 J/m2, a plastic deformation ratio of 0.45, and a tensile strength of 3.74. For the plough subsoil layer, optimal contact parameters were a particle recovery coefficient of 0.47, a coefficient of interparticle kinetic friction of 0.32, a plastic deformation ratio of 0.49, and a tangential stiffness factor of 0.31. Results from the cone penetration test reveal no significant disparity in compactness between the actual experiment and the simulation test. The calibrated discrete element model’s contact parameters have been verified as accurate and reliable. The findings of this study offer valuable data references for understanding the dynamic characteristics of the walking wheel of the entire machinery in high-speed precision seeding in paddy fields.

Parameter calibration and experimental verification of discrete element simulation model for Protaetia brevitarsis larvae bioconversion mixture

Parameter calibration and experimental verification of discrete element simulation model for Protaetia brevitarsis larvae bioconversion mixture

基于离散元模拟的白米仿真参数标定

Aiming at the lack of discrete element simulation models and parameters for rice polishing, grading, color sorting and other technologies and equipment, and the difficulty of guiding equipment design and optimization through simulation, this paper calibrates the simulation parameters of white rice based on angle of repose (AOR) test and simulation methods. Huanghuazhan and Dongnong 429 white rice were selected as research object. Numerical model of white rice was established by multi-sphere filling. According to physical test and references, the simulation parameter range of white rice particles was determined. Plackett-Burman test was used to screen parameters, and it was found that the particle-particle static friction coefficient and particle-particle rolling friction coefficient had significant effects on the AOR of white rice. The regression model between the AOR and the significance parameter was established according to the central composite design method. The simulation parameter combination that has significant influence on the physical AOR was determined through the optimization design, and verified by the simulation test. The simulation AOR was compared with the physical AOR, and the relative error of the two kinds of white rice was less than 3%. The results show that the calibration method proposed in this study can accurately simulate the physical AOR test, which can provide reference for discrete element simulation of white rice processing.

A Novel Projection-based Embedded Discrete Fracture Model (pEDFM) for Anisotropic Two-phase Flow Simulation Using Hybrid of Two-point Flux Approximation and Mimetic Finite Difference (TPFA-MFD) Methods

This paper presents a novel projection-based embedded discrete fracture model (pEDFM) applicable to general two-phase flow simulation in anisotropic reservoirs for the first time. The novel pEDFM is developed based on hybrid two-point flux approximation and mimetic finite difference (TPFA-MFD) methods, which retains the basic features of two-point flux approximation (TPFA) based generic pEDFM workflow and incorporates new features of mimetic finite difference (MFD) to handle full-tensor permeabilities. This is achieved by introducing the concept of effective connection, formulating additional pressure degrees of freedom for effective connections, assigning effective matrix-matrix (m-m) and matrix-fracture (m-f) connections to the corresponding sides of matrix-cell interfaces, presenting methods corresponding to different types of connections to handle low-conductivity fractures, and further deriving formulas of numerical fluxes for effective connections. The resulting global equation system is solved by a Newton-Raphson nonlinear solver with the temporary discretization of the implicit backward Euler scheme. The 2D and 2.5D numerical examples show the novel pEDFM could achieve the same level of computation accuracy and convergence as the reference discrete fracture model (DFM), while avoiding the gridding difficulty of complex fracture networks. It also significantly outperforms classical EDFM based on MFD and generic pEDFM workflow in the computational accuracy for cases with anisotropic full tensor permeabilities. The novel pEDFM, to our best knowledge, is for the first time proposed and developed for general anisotropic two-phase flow simulation and maybe the numerical simulation framework for multi-phase flow in fractured reservoirs with the best comprehensive performance so far.

A Calibration of the Contact Parameters of a Sesbania Seed Discrete Element Model Based on RSM

In order to simulate and analyze the mechanized seeding process of sesbania seeds by using a discrete element method and improve the reliability of the discrete element simulation test, the contact parameters of sesbania seeds were calibrated in combination with the actual seed drop test and the simulated seed drop test. Through measurements, the intrinsic parameters of the sesbania seed were determined, and the discrete element simulation model of the sesbania seed was established. A measuring device that can simultaneously measure the resting angle and the stacking angle of the population was designed. The rest angle error and the stack angle error of the actual seed drop test and the simulated seed drop test were used as test indicators. The Plackett–Burman test screened out the contact parameters that had a significant effect on the test indicators. The response surface method (RSM) was used to carry out the three-factor quadratic rotation orthogonal combination test, and the mathematical regression model between the significant contact parameters and the test indexes was established. The optimal combination of contact parameters was determined using the multi-objective optimization method as follows: collision recovery coefficient between seeds of 0.463, static friction coefficient between seeds of 0.520, and rolling friction coefficient between seeds of 0.072. The discrete element model and calibration parameters of sesbania seeds were tested and verified using a fluted roller feed mechanism. The results showed that the average relative error between the measured value and the simulated value of the mass flow rate of the sesbania seeds was 2.74%, less than 5%, indicating that the discrete element simulation model of sesbania seeds and the calibration results of the contact parameters had high accuracy and reliability, which could be used for the discrete element simulation test of sesbania seeds.

A framework for modeling, generating, simulating, and predicting carbon dioxide dispersion indoors using cell-DEVS and deep learning

Carbon dioxide concentration in enclosed spaces is an air quality indicator that affects occupants’ well-being. To maintain healthy carbon dioxide levels indoors, enclosed space settings must be adjusted to maximize air quality while minimizing energy consumption. Studying the effect of these settings on carbon dioxide concentration levels is not feasible through physical experimentation and data collection. This problem can be solved by using validated simulation models, generating indoor settings scenarios, simulating those scenarios, and studying results. In previous work, we presented a formal Cellular Discrete Event System Specifications simulation model for studying carbon dioxide dispersion in rooms with various settings. However, designers may need to predict the results of altering large combinations of settings on air quality. Generating and simulating multiple scenarios with different combinations of space settings to test their effect on indoor air quality is time-consuming. In this research, we solve the two problems of the lack of ground truth data and the inefficiency of producing and studying simulation results for many combinations of settings by proposing a novel framework. The framework utilizes a Cellular Discrete Event System Specifications model, simulates different scenarios of enclosed spaces with various settings, and collects simulation results to form a data set to train a deep neural network. Without needing to generate all possible scenarios, the trained deep neural network is used to predict unknown settings of the closed space when other settings are altered. The framework facilitates configuring enclosed spaces to enhance air quality. We illustrate the framework uses through a case study.

Process Exploration of New Materials for Building Decoration Engineering Based on Multi-Objective Planning Modeling

Abstract Firstly, on the basis of the multi-objective planning model, we determine the objective function of building energy consumption, the objective function of material cost and the objective function of uncomfortable time percentage. We propose to use a multi-objective genetic algorithm to obtain the Pareto frontier solution for the decision variables of the model by selecting them. The target constraints are determined based on the construction of the building decoration project, and the model of remodeling material cost-schedule-carbon emission’ is constructed. The discrete simulation model of the decoration project is constructed based on the design parameters of the enclosure structure and air conditioning. Considering the structural rigor of the research and analysis, it is necessary to set and explain the parameters of the simulation model, and the materials of the decoration project are studied and analyzed. The results show that on the engineering case analysis, the value of building energy consumption, building cost and the value of uncomfortable time percentage have increased by 23%-45% compared with the value before optimization. In the simulation model, the optimized construction solution’s carbon emission, cost, and duration were reduced by 6.22%, 10.65%, and 45.48%, respectively, compared to the original solution. This study illustrates the aesthetic performance and functional performance on the basis of the process of new materials, which is a guiding reference value for the application of new materials in architectural decoration engineering.