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This paper explores how investments in research and development (R&D) and government policies impact the growth of renewable energy in Brazil, Chile, and Colombia up to 2040. The study presents four scenarios to understand how different levels of R&D investment and the presence or absence of supportive policies affect the spread of renewable technologies such as solar and wind energy. The scenarios range from an optimistic one with high R&D funding and strong policy support to a worst-case scenario with low R&D efforts and weak policies. The findings emphasize the importance of solid government backing and strategic R&D investments in promoting renewable energy and increasing the number of green patents. On the other hand, scenarios with limited policy support and R&D funding show much slower growth, highlighting the challenges posed by economic constraints and tough market conditions. The study shows that strong renewable energy policies could boost renewable energy adoption by 100% to 200%. Overall, this research adds to the discussion on sustainable energy policies and provides useful insights for policymakers and stakeholders to develop strategies that maximize the potential of renewable energy in the region.

Profitability is a complex notion, intertwined with theoretical, socio-economic, and modern economic considerations. While traditionally linked to monopoly advantages, contemporary views broaden this to include shareholder value creation. In agriculture, profitability faces impediments such as rising input costs, market volatility, and economic disparities, emphasizing technological innovation, market conditions, and policy as crucial determinants. This study presents an econometric simulation model to analyze and forecast wheat production profitability in Poland from 2023 to 2027, providing insights into production efficiencies, market dynamics, and policy impacts. Using a system of recursive equations, the model forecasts profitability, integrating econometric techniques with expert insights. It examines variables like resource use, production levels, and price changes, validated through FADN data. The findings reveal that price relations and production efficiencies are the key to profitability. The model highlights market volatility, particularly through “price scissors”, as the main factor influencing profitability. Favorable price conditions significantly boost profitability and incentivize production. The model is a critical tool for analyzing wheat profitability, highlighting the influence of market and policy changes. Future work could extend the model’s use to other regions or crops, incorporating advanced technologies to improve accuracy. This study offers valuable insights for agricultural economics, aiding stakeholders in strategic decision-making.

The heating system is an essential component of the glass molding process. It is responsible for heating the glass to an appropriate temperature, allowing it to soften and be easily molded. However, the energy consumption of the heating system becomes particularly significant in large-scale production. This study utilized G-11 glass for the simulation analysis and developed a finite element model for the thermal conduction of a 3D ultra-thin glass molding system, as well as a thermal bending model for smartwatches. Using finite element software, the heat transfer between the mold and the glass was modeled, and the temperature distribution and thermal stress under various processing conditions were predicted. The findings of the simulation, when subjected to a numerical analysis, showed that heating rate techniques significantly affect energy consumption. This study devised a total of four heating strategies. Upon comparison, optimizing with heating strategy 4, which applies an initial heating rate of 35 mJ/(mm2·s) during the initial phase (0 to 60 s) and subsequently escalates to 45 mJ/(mm2·s) during the second phase (60 to 160 s), resulted in a reduction of 4.396% in the system’s thermal output and a notable decrease of 7.875% in the heating duration, respectively. Furthermore, a single-factor research method was employed to study the forming process parameters. By comparing the numerical simulation results, it was found that within the temperature range of 615–625 °C, a molding pressure of 25–35 MPa, a heating rate of 1.5–2.5 °C/s, a cooling rate of 0.5–1 °C/s, and a pulse pressure of 45–55 Hz, the influence on residual stress and shape deviation in the glass was minimal. The relative error range was within the 20% acceptable limit, according to the experimental validation, which offered crucial direction and ideas for process development.

Farmland use regulation strictly regulates the conversion of agricultural land for other agricultural purposes and the construction of agricultural facilities, thereby optimizing the land use pattern in rural areas. However, different measures and intensities of farmland use regulation can affect the overall performance of green and low-carbon development in rural areas. This study utilizes system dynamics modeling and simulation to conduct a case study based on current land use data from 10 towns in Liyang City, China. The empirical results indicate the following: (1) Based on comprehensive measurements of green and low carbon development performance, Liyang City exhibits a pattern of higher indices in the south and lower indices in the north. Towns such as Tianmu Lake, Daibu, and Shezhu show relatively high average comprehensive indices of 0.31, 0.30, and 0.28, significantly higher than other towns. (2) Simulation of farmland use regulation’s impact on green and low carbon development performance reveals that Scenario One, involving additional construction land occupying farmland, achieves a comprehensive index of only 0.23, significantly lower than the other scenarios. (3) Based on calculations and field surveys, Liyang City’s villages are categorized into four types, with the largest number being industry-integrated villages (94 villages). Accordingly, policies for farmland use regulation are designed for different village types. Therefore, future farmland use regulation should be tailored with differentiated institutional designs according to the development needs of different villages. This study’s findings provide insights into green and low-carbon development in rural areas.

A current challenge of irrigationengineering is to modernize surface irrigation. For example, surge flow irrigation has the potential to increase the efficiency of applying irrigationwater. The objective of this study was to perform a sensitivity analysis using the performance indices: Application Efficiency (AE), Storage Efficiency (SE), Distribution Efficiency (DE), Deep Percolation (DP), and Runoff (RO), and to investigate their relationship with the main system variables: length (L), unit flow rate (Qo), surge cycles and surge time, using the SIRMOD model. The SIRMOD model simulates the hydraulics of surface irrigation at the field level. The model with the best fit of AE, DE, DP, and RO as a function of L, Qo, or surge cycles and surge time was a quadratic polynomial function with an R2 > 0.70. The model reflects the goodness of fit to the variable that is intended to be explained. The AE is an increasing function of L and a decreasing function of Qo, while DE and RO are decreasing functions of L and are increasing functions of Qo. The number of surges has an impact on the stream size of each surge and on the volume of water stored, but not on the performance indices. It was demonstrated that the SIRMOD model provided the ability to adjust the system parameters and design variables, giving answersto any surge flow configuration. The potential application efficiency (AEpot) (>80%) can be achieved by establishing, e.g., an optimal flow rate (Qopt), with a schedule for the cycle number and surge time, according to soil characteristics.

The aim of this research is to devise a continuous simulation model for predicting ship crane failures to increase their reliability and reduce unplanned downtime during cargo loading and unloading operations. To predict the condition of the hydraulic system, a database from the GALIOT software package was used for carrying out maintenance on cranes at m/v “O” over a period of 120,000 working hours. In the research, fault tree analysis (FTA) was used to identify causal relationships between system failures and basic events, while the Markov mathematical model was used to model the system state and predict transitions between different failure states. A system dynamics simulation model was developed to simulate the behavior of a system using POWERSIM PowerSim Constructor 2.5.d (4002), and regression analysis was performed to analyze the simulation results and understand the relationships between dependent and independent variables. The results show that a model for predicting failures in the hydraulic motors and pumps of ship cranes was developed, and the Markov model makes it possible to estimate the frequency of transitions between states under the condition that the sum of reliability equals one. The simulation model shows high reliability of the cranes and a constant frequency of failures throughout the 120,000 operating hours, while the regression analysis confirms the validity of the simulation model and shows a strong correlation between the analyzed variables. These models are used to improve the planning of ship crane maintenance, reduce unplanned downtime, and predict and promptly detect failures, which overall minimizes maintenance costs and failures.

Proactive prevention and fighting fire at industrial facilities, often located in urbanized clusters, should include the use of modern methods for modeling danger zones that appear during the spread of the harmful combustion products of various chemicals. Simulation modeling is a method that allows predicting the parameters of a danger zone, taking into account a number of technological, landscape, and natural-climatic factors that have a certain variability. The purpose of this research is to develop a mathematical simulation model of the formation process of a danger zone during an emergency at an industrial facility, including an explosion of a container with chemicals and fire, with the spread of an aerosol and smoke cloud near residential areas. The subject of this study was the development of a simulation model of a danger zone of combustion gases and its graphical interpretation as a starting point for timely decision making on evacuation by an official. The mathematical model of the process of danger zone formation during an explosion and fire at an industrial facility presented in this article is based on the creation of a GSL library from data on the mass of explosion and combustion products, verification using the Wald test, and the use of algorithms for calculating the starting and ending points of the danger zone for various factor values’ variables, constructing ellipses of the boundaries of the distribution of pollution spots. The developed model makes it possible to calculate the linear dimensions and area of the danger zone under optimistic and pessimistic scenarios, constructing a graphical diagram of the zones of toxic doses from the source of explosion and combustion. The results obtained from the modeling can serve as the basis for making quick decisions about evacuating residents from nearby areas.

Temperature and light are the key factors affecting the formation of tomato fruit quality in greenhouse cultivation. However, there are few simulation models that examine the relationship between tomato fruit quality formation and temperature and light. In this study, a model was established that investigated the relationships between soluble sugar (SSC), organic acid content (OAC), and SSC/OAC and the cumulative product of thermal effectiveness and photosynthetically active radiation (TEP) during the fruit-ripening period in a solar greenhouse. The root mean square error (RMSE) values were calculated to compare the consistency between the simulated and measured values, and the RMSE values for SSC, OAC, and SSC/OAC were 0.09%, 0.14%, and 0.358, respectively. The combined weights of quality indicators were obtained using the analytic hierarchy process (AHP) and entropy weighting method, ranking as SSC > OAC > SSC/OAC > CI > lycopene > Vc > fruit firmness. The comprehensive fruit quality evaluation value was obtained using the TOPSIS method (Technique for Order Preference by Similarity to an Ideal Solution) and a simulation model between comprehensive tomato fruit quality and TEP was explored. This study could accurately simulate and quantify the accumulation of tomato fruit quality during fruit ripening in response to environmental conditions in a solar greenhouse.

To investigate the mechanical behavior and design methodology of column-free QRST (quasi-rectangular segmental tunnel) structures, a theoretical analysis based on prototype experiments and simulation models is conducted. Initially, a prototype experimental investigation is conducted to reveal the structural behavior at the service stage. Subsequently, the ESHR model (Equivalent Stiffness Homogeneous Ring), the BS model (Beam Spring), and the MBS model (Modified Beam Spring) are used to simulate structural behavior. For design purposes, the design methodology is explored based on the ESHR model, followed by a sensitivity analysis of several key load parameters. Based on the experimental results, weak parts of the column-free QRST structure are found to include several joints (Joint 1, Joint 5, Joint 3, and Joint 8), and corresponding optimization measures are proposed. By comparing the test results, the above-mentioned three models demonstrate their applicability in structural simulation, with the ESHR model having sufficient design accuracy. A model-based deformation mechanism analysis found that joints contribute approximately 2/3 of the structural deformation. For the structural design of the column-free QRST using the ESHR model, amplifying the calculated results of structures directly subjected to the service stage by 10% suffices to meet engineering requirements. Based on the test and study, special attention should be paid to the negative bending moment regions at the waists of the structure during both the design and service stages.

The US Environmental Protection Agency (USEPA) employs a tiered process for assessing risks of pesticides to bees. The model discussed in this paper focuses on honey bees (Apis mellifera L.). If risks to honey bees are identified at the first tier based on exposure and toxicity data for individual adult and larval honey bees, then effects are evaluated in higher-tier studies using honey bee colonies. Colony-level studies require large amounts of resources (to conduct and review) and can yield data complicated by the inherent variability of colonies, which are influenced by factors that cannot readily be controlled, including weather, pests, diseases, available forage, and bee management practices. To better interpret these data, the USEPA and the US Department of Agriculture (USDA) developed a simulation model, BeePop+, that assesses potential honey bee colony-level effects of pesticides. Here, we describe this model using the population model guidance, use, interpretation, and development for ecological risk assessment (Pop-GUIDE) framework, which is a conceptual framework for the development and evaluation of population models. Within the context of Pop-GUIDE, BeePop+ is considered a “realistic-precise” model and reflects the inherent variability of colony response to pesticide exposure by simulating many outcomes. This model meets the desired features needed for use in pesticide risk assessments as its required data inputs are typically available, it is applicable to different US locations, and the outputs are both relevant to USEPA’s protection goals for honey bees and are consistent with the outcomes of empirical studies. This model has also been evaluated using available empirical colony-level data; however, additional evaluation with other studies may still be done in the future prior to completing implementation.

In this paper, we will discuss a calibration algorithm for a digital antenna array that diagnoses its real performance. It can be applied at such stages of the antenna system life cycle as design, tuning, and especially maintenance. A calibration implementation using a scalar method for a multi-beam digital antenna array is proposed and investigated. On-the-fly calibration ensures a continuous improvement in beam pointing accuracy by reducing internal errors in the receiving (transmitting) channels. The purpose of the study is to experimentally examine the capabilities of digital beamforming to increase the angle-of-arrival estimation accuracy. A simulation model of the receiving antenna was created in an anechoic chamber with a planar antenna positioner. The possibility of precise estimation of the direction of arrival using the digital beamforming with electronic scanning was demonstrated. The proposed simulation model made it possible to observe the convergence of the antenna array calibration process using the proposed method for various errors in the signal paths, as well as different signal-to-noise ratios. It has been proven that even under adverse conditions early in the calibration algorithm, the phase error detection converges with high accuracy, and its value decreases uniformly even to the fractions of an angular degree.

The main characteristics of high-efficiency switching-mode solid-state power amplifiers with envelope elimination and restoration (EER) methods depend on all their elements. In this article, we study the influence of the types and parameters of the envelope path low-pass filters (LPFs) on the EER transmitter out-of-band emissions. This article presents for the first time an analysis of EER transmitter operation where the output impedance of the PWM modulator is not equal to zero, as usual (with a one-sided loaded LPF), but is matched with the low-pass filter and the load (with a double-sided loaded LPF). Theoretical comparisons of EER transmitters’ out-of-band emissions were carried out with four envelope path LPF configurations (one-sided and double-sided loaded LPFs with a smooth and sharp transition, respectively), for both the nominal load (broadband antenna) and resonant antennas with a limited bandwidth. The analysis showed that for the case of transmitter operation on a resonant antenna with a limited bandwidth, the preferable option was the use of a sixth-order double-sided loaded LPF with a smooth transition. The use of the proposed modulator configuration allowed the transmitter to operate on an antenna with VSWR = 1.07 at the edges of the transmitted signal band with a minimum LPF bandwidth equal to 5.8 bands of the amplified signal. This could significantly expand its application capabilities and allow one to reduce the PWM clock frequency and increase efficiency.

The external gear pump, like any other hydraulic component, is vulnerable to failure, which may lead to downtime as well as the failure of other components linked to it, thereby causing production loss. Therefore, establishing a condition monitoring system is crucial in identifying failure at an early stage. Traditional condition monitoring approaches rely on experimental data that are collected by means of sensors. However, the sensors utilized in the experiments may have calibration issues, which lead to inaccurate measurements. The availability of experimental data is also limited as it is difficult and expensive to create and detect a fault in a component. Hence, it is essential to develop a simulation model that mimics the performance of the actual system. The data generated from the model can be utilized to create the data source required for automated condition monitoring. A new methodology based on a detailed geometric model for simulating the External Gear Pump is described and compared to two models analyzed in the authors’ previous work, namely Schlosser’s loss model and simple geometric model. In this paper, the three models are compared with experimental data and the method utilized for fault injection. Schlosser’s loss model, as well as the detailed geometric model, are found to be suitable in terms of validation; however, the latter is a better candidate in terms of fault injection. Hence, the detailed geometric model can be implemented as a tool to generate the data source for condition monitoring applications.

The paper describes the developed curvilinear motion simulation model for a vehicle with two traction electric motors moving on a solid surface used to study the dynamic properties of a wheeled vehicle and to subject the developed methods to virtual testing. The simulation model of the electric all-wheel drive vehicle is carried out in the Simcenter Amesim environment to account for the dynamic characteristics and features of the vehicle. The simulation model was developed based on the drawn requirements while the assumptions were justified. Inertia characteristics, tire characteristics, suspension elements, grip characteristics, and surface and air resistance were considered, as these factors affect the vehicle longitudinal and transverse dynamics. The article presents the model implemented in the “Labcar” system and confirms its adequacy by comparing it with the data obtained during the full-scale prototype tests. The bench and range tests of a test vehicle with electric transmission equipped with a measuring complex confirmed the adequacy of the developed model. The results of comparative tests allow for the conclusion that the developed model complex is suitable for modeling purposes, including studying, debugging and initial calibrations of the algorithm of torque distribution on the driving axles of all-wheel drive electric vehicle.

Background: OncoSim-Breast is a Canadian breast cancer simulation model to evaluate breast cancer interventions. This paper aims to describe the OncoSim-Breast model and how well it reproduces observed breast cancer trends. Methods: The OncoSim-Breast model simulates the onset, growth, and spread of invasive and ductal carcinoma in situ tumours. It combines Canadian cancer incidence, mortality, screening program, and cost data to project population-level outcomes. Users can change the model input to answer specific questions. Here, we compared its projections with observed data. First, we compared the model’s projected breast cancer trends with the observed data in the Canadian Cancer Registry and from Vital Statistics. Next, we replicated a screening trial to compare the model’s projections with the trial’s observed screening effects. Results: OncoSim-Breast’s projected incidence, mortality, and stage distribution of breast cancer were close to the observed data in the Canadian Cancer Registry and from Vital Statistics. OncoSim-Breast also reproduced the breast cancer screening effects observed in the UK Age trial. Conclusions: OncoSim-Breast’s ability to reproduce the observed population-level breast cancer trends and the screening effects in a randomized trial increases the confidence of using its results to inform policy decisions related to early detection of breast cancer.

Research on the correlation between wind and block spatial form focuses mainly on hot and humid cities. However, cold regions are also experiencing high summer temperatures due to global climate change. Enhancing wind speed in blocks through urban spatial control improves comfort. Existing research cannot be directly applied to cold regions due to natural differences. Using Xi’an as an example, this study explores the impact of high-rise residential block spatial form on internal and external wind environments through field measurements and simulations. Optimal strategies for block planning and architectural design are identified to improve the wind environment. Results show that blocks with high buildings on the south and north sides and low buildings in the middle achieve a more comfortable internal wind environment. Gradually increasing building height from south to north has minimal impact on downwind blocks. Reducing the angle between the main facade and dominant wind direction enhances the residential area’s wind environment. Specific spatial planning and design strategies are summarized for early-stage decision-making.

The use of surface plasmon resonance sensors allows for the fabrication of highly sensitive, label-free analytical devices. This contribution reports on a grating coupler to enable surface plasmon resonance studies using silver on silicon oxide technology to build long-term stable plasmonic structures for biological molecule sensing. The structural parameters were simulated and the corresponding simulation model was optimized based on the experimental results to improve its reliability. Based on the model, optimized grating nanostructures were fabricated on an oxidized silicon wafer with different structural parameters and characterized using a dedicated optical setup and scanning electron microscopy. The combined theoretical and experimental results show that the most relevant refractive index range for biological samples from 1.32–1.46 may conveniently be covered with a highest sensitivity of 128.85°/RIU.

Smoking causes substantial amount of mortality and morbidity. This article presents the findings from simulation models that projected the impact of five potential Tobacco Endgame strategies on smoking prevalence in Ontario by 2035 and expected impact of smoking prevalence “less than 5 by 35” on tax revenue. We used Ontario SimSmoke simulation for modelling the expected impact of four strategies: plain packaging, free cessation services, decreasing the number of tobacco outlets, and increasing tobacco taxes. Separate models were used to project the impact of increasing the minimum age to legally purchase tobacco to 21 years on smoking prevalence and impact of price and tax increase to achieve “less than 5 by 35” on taxation revenue. The combined effect of four strategies in Ontario SimSmoke Model are expected to reduce smoking prevalence by 8.5% in 2035. Increasing tobacco taxes had the greatest independent predicted decrease in smoking prevalence (2.8%) followed by raised minimum age for legal purchase to 21 years (2.4%), decreasing tobacco outlets (1.5%), free cessation services (0.7%), and plain packaging (0.6%). Increasing tobacco excise tax and prices are projected to have minimal impact on taxation revenue, with a decrease from 1.5 billion to 1.2 billion annual tax receipts.

Double-twisted hexagonal gabion wire mesh is a type of reinforced soil material that is used in gabion retaining walls to stabilize the soil slope in geotechnical engineering. In this study, a series of tensile tests were conducted to investigate the tensile behavior of hexagonal gabion wire mesh. Meanwhile, numerical models of gabion wire mesh were built to investigate the whole tensile loading-strain process. The influence of wire diameter, mesh width, and mesh length on the tensile strength of hexagonal gabion wire mesh were evaluated based on laboratory tests and numerical simulation. The quantitative relationship of tensile strength versus wire diameter, mesh width, and mesh length was typically fitted by a quadratic function, linear function, and monotonically decreasing exponential function. The numerical result presents a good consistency with those obtained from the experiment. The result of the loading-strain curve obtained by both experiment and simulation exhibits an “S” shape with a distinct serrated characteristic. The loading-strain curve can be divided into the following four stages: mesh distortion stage, wire stretching stage, overall yield stage, and wire fracture stage, which well reflects the tensile behavior of double-twisted hexagonal wire mesh. The tensile behavior of gabion wire mesh is influenced by the structure pattern of wire mesh and the mechanical characteristic of steel wire.

A pathogen, healthy, latently infected, infectious, and diseased plant (PHLID) model for botanical epidemics was defined for tomato bacterial canker (TBC) caused by the pathogenic plant bacteria, Clavibacter michiganensis subsp. michiganensis (Cmm). First, the incubation period had to be defined to develop this type of model. To estimate the parameter of incubation period, inoculation experiments were conducted in which it was assumed that infection is transferred to healthy plants by cutting with contaminated scissors after cutting infected plants with early symptoms or symptomless. The concentration of Cmm was increased over 1 × 106 cells/g plant tissue at 20 cm away from the inoculated point on the stem 10 days after inoculation, and then the approximate incubation period of TBC in symptomless infected plants was defined as 10 days. The developed PHLID model showed the dynamics of diseased plants incidence and fitted the curve of the proportion of diseased plants observed in fields well. This model also contains the factors of pathogen and disease control, and it was able to simulate the control effects and combined two different control methods, which were the soil and scissors disinfections to prevent primary and secondary transmissions, respectively. Thus, this PHLID model for TBC can be used to simulate not only the increasing number of diseased plants but also suppressing disease increase.

In this study, we present a novel simulation model and case study to explore the long-term dynamics of early detection of disease, also known as routine population screening. We introduce a realistic and portable modeling framework that can be used for most cases of cancer, including a natural disease history and a realistic yet generic structure that allows keeping track of critical stocks that have been generally overlooked in previous modeling studies. Our model is specific to prostate-specific antigen (PSA) screening for prostate cancer (PCa), including the natural progression of the disease, respective changes in population size and composition, clinical detection, adoption of the PSA screening test by medical professionals, and the dissemination of the screening test. The key outcome measures for the model are selected to show the fundamental tradeoff between the main harms and benefits of screening, with the main harms including (i) overdiagnosis, (ii) unnecessary biopsies, and (iii) false positives. The focus of this study is on building the most reliable and flexible model structure for medical screening and keeping track of its main harms and benefits. We show the importance of some metrics which are not readily measured or considered by existing medical literature and modeling studies. While the model is not primarily designed for making inferences about optimal screening policies or scenarios, we aim to inform modelers and policymakers about potential levers in the system and provide a reliable model structure for medical screening that may complement other modeling studies designed for cancer interventions. Our simulation model can offer a formal means to improve the development and implementation of evidence-based screening, and its future iterations can be employed to design policy recommendations to address important policy areas, such as the increasing pool of cancer survivors or healthcare spending in the U.S.

The economic evaluation of mastitis control is challenging. The objective of this study was to perform the economic evaluation of mastitis control, under different intervention scenarios, quantifying the total cost of mastitis caused by S. aureus in Holstein cows in Argentina. A model was set for a dairy herd of Holstein cows endemically infected with S. aureus. A basic mastitis control plan including proper milking procedures, milking machine test, dry cow therapy, and treatment for clinical mastitis, was compared against other more complex and costly interventions, such as segregation and culling of chronically infected cows. Sensitivity analysis was performed by modifying the intramammary infection transition probabilities, economic parameters, and efficacy of treatment strategies. The basic mastitis control plan showed a median total cost of USD88.6/cow per year, which was close to the infected cows culling scenarios outputs. However, the segregation scenario was the most efficient, in which the total cost was reduced by about 50%. Such cost was more sensitive to probabilities and efficacy than the economic parameters. The model is flexible and can be customized by producers and veterinarians according to different control and herd settings.

A city’s transport and distribution system requires the effective organization of urban freight deliveries that take into consideration the economic, ecological, and social impact. Implementation of the concept of green logistics necessitates the use of environmentally friendly and energy-efficient modes of transport, which consider the existing infrastructure and the possibility of its development. The aim of this work was to facilitate the transfer to rail transport, using the existing tramway infrastructure, those shipments which previously entered the city center by road. The paper proposes a simulation model for small consignments delivered by freight trams in the city of Poznań, Poland. Operational planning is carried out in conditions of uncertainty and risk. The uncertainty is due to the stochastic nature of the demand for products. The risk is characterized by the probability that, due to technological and technical limitations, a given customer will not be fully served from the distribution center. The authors provide a decision support tool for evaluating the possible locations of tram depots and for route planning. The assignment of the routes, with the criterion of minimizing the costs for the carrier, and with a limitation on tram operating time, is based on the use of genetic algorithms, which makes it possible to obtain a solution that is close to optimal, within a reasonable time period. As a result of a series of simulation experiments and statistical data processing, the distribution laws and expected average values of the technological parameters were determined for the functioning of the city transport and distribution system under conditions of uncertainty and risk.

The article describes a study of ship delays on the Świnoujście-Szczecin waterway observed by the VTS operator. The research has led to an understanding of the factors that affect delays of ships calling at the ports of Szczecin and Police, as well as the possibilities of predicting and preventing these delays. This article presents the results of the study on the traffic intensity on the investigated waterway and the process of identifying the port regulation that causes the most frequent delays. Based on the obtained results from the statistical analysis and from using multiple regression, a statistical model has been developed that has the ability to estimate expected delays. Additionally, the model has been expanded to calculate financial losses resulting from delays, taking into account the daily cost of maintaining the studied ships. The study took place during ongoing project “Modernization of the Świnoujście-Szczecin waterway to a depth of 12.5 m” but does not include delays resulting from this project.

Is it possible to develop a meaningful measure for the complexity of a simulation model? Algorithmic information theory provides concepts that have been applied in other areas of research for the practical measurement of object complexity. This article offers an overview of the complexity from a variety of perspectives and provides a body of knowledge with respect to the complexity of simulation models. The key terms model detail, resolution, and scope are defined. An important concept from algorithmic information theory, Kolmogorov complexity, and an application of this concept, normalized compression distance, are used to indicate the possibility of measuring changes in model detail. Additional research in this area can advance the modeling and simulation body of knowledge toward the practical application of measuring simulation model complexity. Examples show that KC and NCD measurements of simulation models can detect changes in scope and detail.

Hyper-compressors play an important role in polymer production. However, due to the extremely high pressure and complex geometries, it is difficult to monitor and calculate the thermodynamic characteristics and pressure pulsation. In this research, a three-dimensional (3D) computational fluid dynamics (CFD) model of a hyper-compressor with a central valve and piston movements based on a real gas model (RGM) was developed to analyze the thermodynamic performance and pressure pulsation. Then, the p−θ diagram of the working chamber and the dynamic pressure internal pipe were constructed using a nondestructive testing approach and showed a strong correlation with the pressure sensor data. The 3D-CFD model’s results correlated well with the experimental data. The deviation error between simulation values and experimental data of the indicated power was 1.77%. Lastly, the numerical model was used to analyze the hyper-compressor’s performance, power loss, dynamic features of the central valve and pressure pulsation.

Bacillus anthracis, the causative agent of anthrax in humans, livestock, and wildlife, exists in a community with hundreds of other species of bacteria in the environment. Work on the genetics of these communities has shown that B. anthracis shares a high percentage of chromosomal genes with both B. thuringiensis and B. cereus, and that phenotypic differences among these bacteria can result from extra-chromosomal DNA in the form of plasmids. We developed a simple hypothetical individual-based model to simulate the likelihood of detecting plasmids with genes encoding anthrax toxins within bacterial communities composed of B. anthracis, B. thuringiensis, and B. cereus, and the surrounding matrix of extra-cellular polymeric substances. Simulation results suggest the horizontal transfer of plasmids with genes encoding anthrax toxins among Bacillus species persisting outside the host could function as a proximate factor triggering anthrax outbreaks.

A field water balance model for efficient irrigation water management of corn was developed using Excel VBA. The model consists of five sub-components or modules, namely, (1) a plant subcomponent, (2) an effective rainfall subcomponent, (3) an evapotranspiration subcomponent, (4) a soil water dynamics subcomponent for the modeling of water flow into and within the soil layers, and (5) an irrigation subcomponent for the estimation of the required amount and timing of irrigation. The model was calibrated and validated using observed data from field experiments and the results showed a reasonably good agreement between the observed and simulated soil moisture values (MAE = 5.76 mm to 12.00 mm, RMSE = 6.83 mm to 13.12 mm, NRMSE = 0.102 to 0.196, and NSE = 0.37 to 0.90). The simulations emphasized that a significant amount of water savings can be achieved when rainfall is properly accounted for in managing water in the field, and that the frequency of rainfall occurrences is as important as the magnitude of rainfall received by the crops. The wide-ranging user-friendliness and simplicity of the model developed in this study can pave the way to eliminating the barriers which cause farmers to resist advancements in their farming practices as the model can easily be used not only by researchers and scientists but also by farmers, especially those with basic knowledge of spreadsheets.

The discrete element parameters of cabbages (Brassica oleracea L.) were calibrated for the design and parameter optimization of a cabbage harvester. The cabbage model was created based on the study of cabbage material characteristics and the simulation model parameters of cabbage were calibrated. The intrinsic parameters and partial contact parameters of cabbages were obtained by direct measurement. The cabbage accumulation angle was determined by a plate drawing test. Through the steepest ascent test and the orthogonal rotation combination test, a regression model of the cabbage accumulation angle error was established. The optimal contact parameters between the cabbages were obtained by the minimum error modeling. These calibrated parameters were applied in the verification test, and the results indicated that the error between the simulated and measured values of the cabbage accumulation angle was only 1.63%, which demonstrated that the results were dependable. This study can provide a theoretical support for designing and optimizing the parameters of cabbage harvesting machines with the discrete element method (DEM).

The pantograph–catenary arc of urban rail has the characteristic of high temperature, which directly acts on the surface of the pantograph–catenary system, will seriously ablate pantograph and contact line, and affect the flow of the pantograph–catenary system. In this paper, based on MHD, a mathematical model of the arcing of urban rail pantograph–catenary system is established. COMSOL finite element software was used to simulate the arc temperature field of the pantograph–catenary arc. Through the temperature distribution cloud diagram and related images, the relationship between the arc central temperature, the duration, and the gap of the pantograph arc were studied. It is found that the arc temperature increases with the increase in arc duration when the arc gap is fixed. When the arc duration is fixed, the arc center temperature changes inversely with the increase in the arc gap. The feasibility of the simulation model is verified by the pantograph–catenary arc experiment platform. The research conclusion of this paper can provide a certain basis for the research of arc erosion on the surface of the pantograph–catenary system.

To observe the evolution mechanism of physical fields in the welding deformation rectification process by a traveling induction heating, research on simulation models of welding—induction heating continuous process were carried out. High-strength steel plates were selected for welding deformation experiment and induction heating rectification experiment in turn, and the stress field and strain field distribution after various processes were measured and recorded. Then, according to the construction process, an integrated model of welding-induction heating based on moving mesh method was analyzed and established by Ansys FE software, moreover, another progressive integrated model established based on the re-defined element attributes method was studied, and the calculation accuracy of these models were compared as well as the characteristics were analyzed. The research results show that these two integrated models can accurately reflect the evolution law of each physical field in the process of welding and induction heating, and the re-defined element attributes method is more suitable for the research of welding deformation and induction heating rectification process.

In this article, a calculation model for a fuel system of a light helicopter was developed for experimental and operational testing. The model analyzes the operation of not only the units, but also the whole fuel system, offering the basis for functional tests and failure detection. For an actual model-based design, it is necessary to ensure that the model conforms to a real object or process. This article addressed the problems of ensuring the accuracy of the calculation and the computational speed when developing a reliable mathematical model of an actual technological system using structural modeling methods. A system with evaluation criteria allows complex field tests to be replaced with validated calculation models.

Coffee (Coffea species) and Cocoa (Theobroma cacao) are important cash crops grown in the tropics but traded globally. This study was conducted to apply the ALMANAC model to these crops for the first time, and to test its ability to simulate them under agroforestry management schemes and varying precipitation amounts. To create this simulation, coffee was grown on a site in Kaua’i, Hawai’i, USA, and cocoa was grown on a site in Sefwi Bekwai, Ghana. A stand-in for a tropical overstory tree was created for agroforestry simulations using altered parameters for carob, a common taller tropical tree for these regions. For both crops, ALMANAC was able to realistically simulate yields when compared to the collected total yield data. On Kaua’i, the mean simulated yield was 2% different from the mean measured yield, and in all three years, the simulated values were within 10% of the measured values. For cocoa, the mean simulated yield was 3% different from the mean measured yield and the simulated yield was within 10% of measured yields for all four available years. When precipitation patterns were altered, in Ghana, the wetter site showed lower percent changes in yield than the drier site in Hawai’i. When agroforestry-style management was simulated, a low Leaf Area Index (LAI) of the overstory showed positive or no effect on yields, but when LAI climbed too high, the simulation was able to show the detrimental effect this competition had on crop yields. These simulation results are supported by other literature documenting the effects of agroforestry on tropical crops. This research has applied ALMANAC to new crops and demonstrated its simulation of different management and environmental conditions. The results show promise for ALMANAC’s applicability to these scenarios as well as its potential to be further tested and utilized in new circumstances.

Robotic bin-picking performance has been gaining attention in recent years with the development of increasingly advanced camera and machine vision systems, collaborative and industrial robots, and sophisticated robotic grippers. In the random bin-picking process, the wide variety of objects in terms of shape, weight, and surface require complex solutions for the objects to be reliably picked. The challenging part of robotic bin-picking is to determine object pick-points correctly. This paper presents a simulation model based on ADAMS/MATLAB cosimulation for robotic pick-point evaluation for a 2-F robotic gripper. It consists of a mechanical model constructed in ADAMS/View, MATLAB/Simulink force controller, several support functions, and the graphical user interface developed in MATLAB/App Designer. Its functionality can serve three different applications, such as: (1) determining the optimal pick-points of the object due to object complexity, (2) selecting the most appropriate robotic gripper, and (3) improving the existing configuration of the robotic gripper (finger width, depth, shape, stroke width, etc.). Additionally, based on this analysis, new variants of robotic grippers can be proposed. The simulation model has been verified on a selected object on a sample 2-F parallel robotic gripper, showing promising results, where up to 75% of pick-points were correctly determined in the initial testing phase.

In this paper, a mathematical simulation model of an electric vehicle traction battery has been developed, in which the battery was studied during the dynamic modes of its charge and discharge for heavy electric vehicles in various driving conditions—the conditions of the urban cycle and movement outside the city. The state of a lithium-ion battery is modeled based on operational factors, including changes in battery temperature. The simulation results will be useful for the implementation of real-time systems that take into account the processes of changing the characteristics of traction batteries. The developed mathematical model can be used in battery management systems to monitor the state of charge and battery degradation using the assessment of the state of charge (SOC) and the state of health (SOH). This is especially important when designing and operating a smart battery management system (BMS) in virtually any application of lithium-ion batteries, providing information on how long the device will run before it needs to be charged (SOC value) and when the battery should be replaced due to loss of battery capacity (SOH value). Based on the battery equivalent circuit and the system of equations, a simulation model was created to calculate the electrical and thermal characteristics. The equivalent circuit includes active and reactive elements, each of which imitates the physicochemical parameter of the battery under study or the structural element of the electrochemical battery. The input signals of the mathematical model are the current and ambient temperatures obtained during the tests of the electric vehicle, and the output signals are voltage, electrolyte temperature and degree of charge. The resulting equations make it possible to assign values of internal resistance to a certain temperature value and a certain value of the degree of charge. As a result of simulation modeling, the dependence of battery heating at various ambient temperatures was determined.

The World Health Organization estimates that 5 to 15% of amputees in any given population have access to a prosthesis. This figure is likely to worsen as the amputee population is expected to double by 2050, straining the limited capacity of prosthetics services. Without proper and timely prosthetic interventions, amputees with major lower-limb loss experience adverse mobility outcomes, including the loss of independence, lowered quality of life, and decreased life expectancy. Presently, the use of digital technology in prosthetics (e.g., 3D imaging, digital processing, and 3D printed sockets) is contended as a viable solution to this problem. This paper uses system dynamics modeling to assess the impact of digital prosthetics service provision. Our simulation model represents the patient-care continuum and digital prosthetics market system, providing a feedback-rich causal theory of how digital prosthetics impacts amputee mobility and the corollary socio-health-economic outcomes over time. With sufficient resources for market formation and capacity expansion for digital prosthetics services, our work suggests an increased proportion of prosthesis usage and improved associated health-economic outcomes. Accordingly, our findings could provide decision support for health policy to better mitigate the accessibility problem and bolster the social impact of prosthesis usage.

The Theory of the Adjacent Possible (TAP) equation has been proposed as an appropriate description of super-exponential growth phenomena, where a phase of slow growth is followed by a rapid increase, leading to a “hockey stick” curve. This equation, initially conceived to describe the growth in time of the number of new types of artifacts, has also been applied to several natural phenomena. A possible drawback is that it may overestimate the number of new artifact types, since it does not take into account the fact that interactions, among existing types, may produce types which have already been previously discovered. We introduce here a Binary String World (BSW) where new string types can be generated by interactions among (at most two) already existing types. We introduce a continuous limit of the TAP equation for the BSW; we solve it analytically and show that it leads to divergence in finite time. We also introduce a criterion to distinguish this type of behavior from the familiar exponential growth, which diverges only as t → ∝. In the BSW, it is possible to directly model the generation of new types, and to check whether the newborns are actually novel types, thus discarding the rediscoveries of already existing types. We show that the type of growth is still TAP-like, rather than exponential, although of course in simulations one never can observes true divergence. We also show that this property is robust with respect to some changes in the model, as long as it deals with types (and not with individuals).

The peatlands of Western Siberia occupy an area of about 1 million km2 and act as important regulator of carbon exchange between the earth and the atmosphere. Extrapolation of the results of discrete field measurements of CO2 fluxes in bog ecosystems to such a territory is a difficult task, and one of the ways to overcome it is to use a simulation model such as DNDC. However, using this model with a specific territory requires ground verification to confirm its effectiveness. Here, we tested the DNDC model on the largest pristine bog ecosystem of the world, the Great Vasyugan Mire (GVM). The GVM of western Siberia is virtually undisturbed by anthropogenic activity and is the largest bog of Northern Eurasia (53,000 km2). Based on various ground-based observations, the performance of the Wetland-DNDC model was demonstrated (Thale coefficient 0.085 and R2 = 0.675 for CO2). Model input parameters specific to the GVM were constrained and model sensitivity to a wide range of input parameters was analyzed. The estimated annual terrestrial carbon fluxes in 2019 from the GVM test site are mainly controlled by plant respiration (61%) and forest floor degradation (38%). The net CO2 emission flux was 8600 kg C ha−1 year−1, which is in line with estimates from other independent studies.

The LNG terminals are characterized by a large number of ships entering the port during the winter season due to the seasonality of rapidly increasing demand for heating. In winter, there is a shortage of dolphin jetty wharf (dolphins), which increases the waiting rate for ships. Therefore, there is a practical argument that dolphins should be additionally built to solve the ship standby problem. This study proposes the proper LNG handling capacity of a terminal with multiple dolphins of different size. Studies on calculating the LNG handling capacity of LNG terminal dolphins have been proposed by UNCTAD and Ministry of Transport of China (MTC). The formula-based calculation of LNG handling capacity has the advantage of being simple, but it has the disadvantage of not reflecting the actual operation. In this study, the proper LNG handling capacity is measured using a simulation method to overcome the limitations of formula-based calculation for Incheon port in South Korea. In order to check whether the method by simulation is justified, it is compared with the unloading capacity by the calculation formula. This study finds that the proper (or optimal) LNG handling capacity of Incheon port is determined by a dolphin occupancy of 49%, where the dolphin’s profits are maximized. As the results of simulation model, the proper (or optimal) loading capacity is 38.5 million m3 when dolphin occupancy is 49%. The capacity of individual dolphin is estimated at 17.0 million m3 for 70,000 DWT dolphin and 21.2 million m3 for 120,000 DWT dolphin, respectively. The main points of this study to use simulation model are as follows: First, the number of non-working days should be considered. Second, the optimal dolphin occupancy should be determined by finding the maximum profit point of using the pier. Third, if the size of the dolphin is different, an appropriate simulation will be implemented. Fourth, the data of the peak season should be analyzed. Finally, it should be checked whether the ship waiting rate is acceptable level or not.

The objectives of this study are the development and verification of a simulation model of the partial PST (power-shift transmission) tractor based on actual field operations. The PST simulation model was verified for the asphalt driving condition, and performance was evaluated for asphalt driving, plow, and rotary tillage. In this study, the traditional, APS (Auto Power Shift) ECO, and APS power engine modes were used to analyze fuel consumption. The statistical analysis proved that the experimental and simulation results were in a linear relationship, with an accuracy of over 98%. Finally, the results suggested that users could utilize the 95-kW partial PST tractor in the APS ECO engine mode with higher fuel economy compared to the traditional and APS power modes.

With the trend of terminal automation and the requirement for port operation efficiency to be greatly improved, it is very necessary to optimize the traveling route of automatic guided vehicles (AGV) with reference to the connection of loading and unloading equipment. As a complex multi-equipment system, it is inevitable that AGV will collide when traveling due to various accidents in actual operation, which will lead to AGV locking and reduce the efficiency of terminal operation. Considering the locking problem of AGV, we propose a three-stage integrated scheduling algorithm for AGV route planning. Through joint optimization with quay cranes (QC) and yard blocks, a road network model is established in the front area of the container port to optimize the path of AGV in the road network, and a speed control strategy is proposed to solve the problem of AGV collision avoidance. In the first stage, we establish the AGV optimal route model with the goal of minimizing the AGV path according to the AGV road network situation. In the second stage, on the basis of the determination of AGV route planning, and when the container task is known, the AGV task assignment model is established with the goal of minimizing the maximum completion time, and the model is solved by genetic algorithm (GA). In the third stage, on the basis of AGV task assignment and route determination, the AGV route and AGV task assignment scheme are input into the simulation model by establishing the AGV collision avoidance control model for speed control, and establishing the AGV route network simulation model for automated terminals considering collision avoidance in plant simulation software. The maximum completion time obtained from the simulation model is compared with the completion time obtained from the genetic algorithm. The proposed three-stage joint scheduling algorithm can improve the loading and unloading efficiency of the port, reduce the AGV locking situation, and has a certain contribution to the formulation of the actual operation planning of the port.

We present a practical guide and step-by-step flowchart for establishing uncertainty intervals for key model outcomes in a simulation model in the face of uncertain parameters. The process starts with Powell optimization to find a set of uncertain parameters (the optimum parameter set or OPS) that minimizes the model fitness error relative to historical data. Optimization also helps in refinement of parameter uncertainty ranges. Next, traditional Monte Carlo (TMC) randomization or Markov Chain Monte Carlo (MCMC) is used to create a sample of parameter sets that fit the reference behavior data nearly as well as the OPS. Under the TMC method, the entire parameter space is explored broadly with a large number of runs, and the results are sorted for selection of qualifying parameter sets (QPS) to ensure good fit and parameter distributions that are centrally located within the uncertainty ranges. In addition, the QPS outputs are graphed as sensitivity graphs or box-and-whisker plots for comparison with the historical data. Finally, alternative policies and scenarios are run against the OPS and all QPS, and uncertainty intervals are found for projected model outcomes. We illustrate the full parameter uncertainty approach with a (previously published) system dynamics model of the U.S. opioid epidemic, and demonstrate how it can enrich policy modeling results.

A methanol island, powered by solar or wind energy, indirectly captures atmospheric CO2 through the ocean and combines it with hydrogen gas to produce a synthetic fuel. The island components include a carbon dioxide extractor, a desalinator, an electrolyzer, and a carbon dioxide-hydrogen reactor to complete this process. In this study, the optimal locations to place such a device in the Mediterranean Sea were determined, based on three main constraints: power availability, environmental risk, and methanol production capability. The island was numerically simulated with a purpose built python package pyseafuel. Data from 20 years of ocean and atmospheric simulation data were used to “force” the simulated methanol island. The optimal locations were found to strongly depend on the power availability constraint, with most optimal locations providing the most solar and/or wind power, due to the limited effect the ocean surface variability had on the power requirements of methanol island. Within this context, optimal locations were found to be the Alboran, Cretan, and Levantine Sea due to the availability of insolation for the Alboran and Levantine Sea and availability of wind power for the Cretan Sea. These locations were also not co-located with areas with larger maximum significant wave heights, thereby avoiding areas with higher environmental risk. When we simulate the production at these locations, a 10 L s−1 seawater inflow rate produced 494.21, 495.84, and 484.70 mL m−2 of methanol over the course of a year, respectively. Island communities in these regions could benefit from the energy resource diversification and independence these systems could provide. However, the environmental impact of such systems is poorly understood and requires further investigation.

The structural design and operating strategy of a free piston expander–linear generator (FPE–LG) has a major impact on performance. In this paper, the simulation model of single–piston FPE–LG was built and verified by combining the structural parameters of the existing test rig with a set of kinetic and thermodynamic equations. On this basis, the influence of the design and operating parameters of the device on the performance was studied, while keeping other parameters fixed. Then, a sensitivity analysis of power output and operating frequency was carried out. The results show that within a certain range of external load and intake beginning position, increasing the diameter of the intake and exhaust pipes, or reducing the piston rod diameter can improve the power output. Within a certain range of frictional coefficient and intake time, increasing the cylinder diameter and intake pressure, or reducing the piston assembly mass and back electromotive force (EMF) constant can increase the operating frequency. Both the power output and the operating frequency are most sensitive to the cylinder diameter among the design parameters. Among the operating parameters, power output is the most sensitive to intake pressure, and operating frequency is the most sensitive to intake beginning position. The optimization of structural design and operation strategy in expander provides important guiding significance for ORC waste heat recovery system.

Managed plantations of saltbush have the potential to increase the productivity and climate resilience of the farming systems of the low rainfall areas of the world, where livestock are important. The objective was to dynamically simulate the behaviour of grazing saltbush plantations with a new modelling capacity in the APSIM framework to enable the dynamic grazing of forage systems. Scenarios simulated included: the choice of plant species growing in the interrow area between shrub-rows, density of saltbush spatial arrangement, locations with different climates and soils, and grazing strategy by sheep. Comparisons of scenarios across systems were insightful during rainfall years when the shrub systems are of high value (i.e., driest/lowest 20% rainfall years in the simulation period). Overall, the efficient grazing of shrubs by dry sheep with little supplementary feeding, required the availability of a large amount of low quality interrow. Shrub plantations with an interrow of standing oats required least supplementation. Summer grazing was the optimal time for grazing shrub plantations in low rainfall years. Plantations with more shrubs relative to interrow increased the need for supplementary feeding but reduced the variation between years. This is one of the first uses of systems modelling to explore forage shrub system designs that maximise the grazing value of shrub plus interrow.

A crop–weed simulation model is presented to compare and evaluate integrated weed-management (IWM) strategies. Specifically, the model was parameterized for soybean crops in competition with Euphorbia davidii Subils. We used both weed and crop demographic data surveyed in agronomic fields of the central zone of the Buenos Aires province, Argentina, throughout two crop cycles (2011/2012 and 2013/2014). The proposed model underwent a calibration process and subsequent validation with a 70/30% data split, (N = 37). Two annual-based and one multiannual-based case studies were simulated to demonstrate the performance of the model. Different IWM strategies were compared under both operational and tactical planning horizons through the evaluation of different model outcomes (i.e., crop yield, interspecific competition, economic return, and environmental impact). Our results suggest that the inclusion of cultural management practices could reduce both weed interspecific competition by 46 to 97%, and weed seed production by 40 to 89 %. An increment in both expected crop yield, by 6 to 20%, and annual gross margin, by 44 to 199 USD.ha−1, were obtained in silico for similar levels of environmental impact.

An alluvial fan is a good area to install open-loop geothermal heat pump (GHP) systems due to shallower aquifers, faster groundwater flow, and fewer land subsidence risks. The natural temperature change in groundwater occurs in alluvial fans due to the recharge of river water and faster groundwater flow, and the thermal impact of the open-loop system has not been studied well in such areas. The purpose of this research is to understand the thermal impact of open-loop GHP systems on an alluvial fan. A regional 3D model of groundwater flow with heat transport was created to determine the distribution of flow velocity and temperature of groundwater. After that, two local models with different groundwater velocities were constructed to demonstrate the thermal impact of an open-loop GHP system using one extraction and one injection well. The results indicated that the local model with faster groundwater flow had a smaller thermal impact. The natural temperature change in groundwater causes groundwater temperature to be lower in the summer and higher in winter during the operation in the local model, with faster groundwater flow.

Compared with metal ball bearings, full ceramic ball bearings have more outstanding service performance under extreme working conditions. In order to reveal the lubrication mechanism and improve the operation performance and service life of full ceramic ball bearings, in this paper, the friction, vibration, and temperature rise characteristics of 6208 silicon nitride full ceramic deep groove ball bearing, under the condition of oil lubrication, are studied experimentally. Based on the test results, and through theoretical calculation and simulation analysis, the distribution of the lubricating oil film in bearing contact micro-zone under different working conditions was simulated. After that, the surface of contact micro-zone of full ceramic ball bearing was analyzed. It was found that there is an optimal oil supply for full ceramic ball bearing oil lubrication in service. Under the optimal oil supply lubrication, full film lubrication can be achieved, and the bearing exhibits the best characteristics of friction, vibration, and temperature rise. Compared with the load, the rotational speed of the bearing has a decisive influence on the optimal oil supply. When the rotational speed and load are constant, the minimum oil film thickness and oil film pressure in the contact area of the rolling body decrease with the increase of angle ψ from the minimum stress point of the rolling body. Under the action of high contact stress, thin oil film will be formed in the bearing outer ring raceway. In the field of full ceramic ball bearings, the research content of this paper is innovative. The research results of this paper have an important guiding significance for revealing the oil lubrication mechanism of full ceramic ball bearing and enriching its lubrication theory and methods.

Predominantly, field experiments aim to determine the optimal plant density for a unit area. High spatial variation results in lower attained yield than the genetic potential. To find the highest value of the product of mean individual production and crop density, their mathematical relationship is needed to be known. In this study, the relationship between the population and the weight of the individual fresh, dehusked ear of grain maize (Zea mays L.) was investigated, and a relevant mathematical simulation model was developed. Linear regression was disproved to describe this relationship properly based on the analysis of different mosaic sizes within a plot. The distribution of plant-to-plant distance was found to be binomial. The distribution of the ear weight was found to be lognormal. For the description of the population homogeneity, neither the standard deviation nor the variation coefficient was found to be applicable apart from the scale-independent relative variance. The simulation model, based on the above statistical functions, was validated with a real dataset, and it is recommended for the optimization of the plant population at farm scale.

In view of the problems of the violent crown fluctuation and unstable shape control in the endless rolling production line, the field measurement results show that the abnormal crown fluctuation is related to the shifting limit position of the work roll after the uneven wear occurs. For this reason, the asynchronous roll shifting strategy is developed, which has double attenuation of roll shifting amplitude and roll shifting step. By coupling the roll wear contour model, the roll thermal contour model and the rolls-strip integrated model, the strip crown calculation model of the whole rolling unit is established, and the causes of abnormal crown fluctuation are revealed theoretically. In addition, the simulation analysis of the important parameters of asynchronous roll shifting strategy of double attenuation working roll is made by using this model. The number of strips in a roll shifting cycle is found to be too large or too small, which is not benefited by the control of the strip crown stability due to the influence of roll wear and roll thermal crown. A rolling unit has many shifting cycles. When the roll shifting amplitude at the end of a rolling unit is smaller, which can make the amplitude difference between adjacent roll shifting cycles greater, it is easier to avoid the uneven edge wear area and to control the strip crown stability. The industrial test shows that the maximum crown fluctuation in a rolling unit decreases by 21.05%, and the maximum crown fluctuation of adjacent strips decreases by 28.57%, which significantly improves the stability of crown control.