Analysis of Influence of Different Parameters on Numerical Simulation of NACA0012 Incompressible External Flow Field under High Reynolds Numbers

Currently, influence analysis of simulation parameters, especially the trailing edge shape and the corresponding modeling method on the force coefficients of NACA0012 under a high Reynolds number, is relatively sparse. In this paper, two trailing edge shapes are designed by three modeling methods and combined with three far-field distances to establish eighteen two-dimensional external flow fields. The same number of structured grids are generated by a unified grid strategy and the SST k-omega and the Spalart–Allmaras models are adopted to solve the NS equations to realize the numerical simulations. Unlike under low Reynolds numbers, the analysis results show that although the accuracy difference between the sharp trailing edge and the blunt trailing edge decreases as the attack angle range increases, the former is preferred in all studied ranges. As to the corresponding modeling methods, the NACA4 and the definition formula are preferred, the choice of which depends on the studied range. In particular, a greater number of data points adopted into the definition formula is not necessarily better. Considering the error ratios comprehensively, the simulation configurations of sharp trailing edge + 20 m far-field distance + SA/SST/SST/SST/SST/SA turbulence model obtains optimal simulation effects.

University Operations During a Pandemic: A Flexible Decision Analysis Toolkit

Modeling infection spread during pandemics is not new, with models using past data to tune simulation parameters for predictions. These help in understanding of the healthcare burden posed by a pandemic and responding accordingly. However, the problem of how college/university campuses should function during a pandemic is new for the following reasons: (i) social contact in colleges are structured and can be engineered for chosen objectives; (ii) the last pandemic to cause such societal disruption was more than 100 years ago, when higher education was not a critical part of society; (iii) not much was known about causes of pandemics, and hence effective ways of safe operations were not known; and (iv) today with distance learning, remote operation of an academic institution is possible. As one of the first to address this problem, our approach is unique in presenting a flexible simulation system, containing a suite of model libraries, one for each major component. The system integrates agent-based modeling and the stochastic network approach, and models the interactions among individual entities (e.g., students, instructors, classrooms, residences) in great detail. For each decision to be made, the system can be used to predict the impact of various choices, and thus enables the administrator to make informed decisions. Although current approaches are good for infection modeling, they lack accuracy in social contact modeling. Our agent-based modeling approach, combined with ideas from Network Science, presents a novel approach to contact modeling. A detailed case study of the University of Minnesota’s Sunrise Plan is presented. For each decision made, its impact was assessed, and results were used to get a measure of confidence. We believe that this flexible tool can be a valuable asset for various kinds of organizations to assess their infection risks in pandemic-time operations, including middle and high schools, factories, warehouses, and small/medium-sized businesses.

INTEREST: INteractive Tool for Exploring REsults from Simulation sTudies

Simulation studies allow us to explore the properties of statistical methods.They provide a powerful tool with a multiplicity of aims; among others: evaluating and comparing new or existing statistical methods, assessing violations of modelling assumptions, helping with the understanding of statistical concepts, and supporting the design of clinical trials.The increased availability of powerful computational tools and usable software has contributed to the rise of simulation studies in the current literature.However, simulation studies involve increasingly complex designs, making it difficult to provide all relevant results clearly.Dissemination of results plays a focal role in simulation studies: it can drive applied analysts to use methods that have been shown to perform well in their settings, guide researchers to develop new methods in a promising direction, and provide insights into less established methods.It is crucial that we can digest relevant results of simulation studies.Therefore, we developed INTEREST: an INteractive Tool for Exploring REsults from Simulation sTudies.The tool has been developed using the Shiny framework in R and is available as a web app or as a standalone package.It requires uploading a tidy format dataset with the results of a simulation study in R, Stata, SAS, SPSS, or comma-separated format.A variety of performance measures are estimated automatically along with Monte Carlo standard errors; results and performance summaries are displayed both in tabular and graphical fashion, with a wide variety of available plots.Consequently, the reader can focus on simulation parameters and estimands of most interest.In conclusion, INTEREST can facilitate the investigation of results from simulation studies and supplement the reporting of results, allowing researchers to share detailed results from their simulations and readers to explore them freely.

CALIBRATION OF BONDING MODEL PARAMETERS FOR COATED FERTILIZERS BASED ON PSO-BP NEURAL NETWORK

In this paper, the ultimate crushing displacement and ultimate crushing load of the coated fertilizer granules were obtained by uniaxial compression test as 0.450 mm and 58.668 N, respectively. Then the DEM model of the encapsulated fertilizer was established, and the Plackett-Burman and Steepest ascent tests were taken to determine the factors that had significant effects on the results and their ranges of values, respectively. Finally, the PSO_BP neural network was trained using full-factor test data, and the correlation coefficients of training process, validation process, testing process and overall performance were obtained as 0.98057, 0.95781, 0.96724 and 0.97459, respectively, indicating that the trained PSO_BP neural network fits well and can predict the ultimate crushing displacement and ultimate crushing load. The ultimate crushing displacement Y1 and ultimate crushing load Y2 are 0.450 mm and 58.703 N, with a minimum relative error of 0.06% from the actual value. This study can provide new methods and ideas for the calibration of discrete element simulation parameters.

Calibration and Tests for the Discrete Element Simulation Parameters of Fallen Jujube Fruit

Discrete element method (DEM) simulation is an important method to analyze the interaction relationship between materials and equipment, and to develop machinery and/or equipment. However, it is necessary to input specific simulation parameters when establishing a DEM simulation model. In this study, the interval values were measured through angle of repose tests of fallen jujube fruit (FJF), and the simulation angle of repose tests for FJF were established with EDEM software (DEM Solutions Ltd. Edinburgh, Scotland, UK). Then, the Plackett-Burman design, steepest ascent search experiment, and center composite design experimental methods were utilized to obtain the specific values of the simulation parameters from the interval values. The results showed that significant influencing factors in the simulation angle of repose include the Poisson’s ratio, the static friction coefficient between FJF, and the static friction coefficient between FJF and the steel plate, for which the optimal values were 0.248, 0.480, and 0.309, respectively. The angle of repose tests’ results showed that the error was 0.53% between the simulation angle of repose (29.69°) and the angle of repose (29.85°). In addition, the flow rate test results showed that the average error was 5.84% between the physical and simulation tests. This indicated that the calibrated parameters were accurate and reliable, and that the simulation model can accurately represent the physical tests. Consequently, this study provides an EDEM model of FJF that was essential in designing machinery and equipment through the EDEM simulation method.

Novel Step-Up Topologies of Zigzag Autotransformer

Zigzag autotransformer is widely used in multi-pulse rectifier system. However, the traditional zigzag autotransformer does not have the step-up function. Meanwhile, by improving the zigzag autotransformer structure, the output voltage can be increased without additional auxiliary components. Therefore, based on the 12 pulse rectifier system, this paper analyzes and designs three zigzag autotransformer step-up topologies, establishes the corresponding mathematical topology, studies the relationship between the transformation ratio and system main parameters, and deduces the step-up range of the three topologies. When the transformation ratio is greater than or equal to 1.0353 and less than 2.0705 and when the transformation ratio is greater than or equal to 2.0705, the equivalent capacity of the three topologies are compared. Based on the comparison, the optimal topology is obtained in different cases. Finally, according to the theoretical analysis, the simulation parameters are set, the simulation circuit is built, and the results are analyzed combined with corresponding mathematical topologies.

Optimization of Fuzzy Logic Based Virtual Pilot for Wargaming

This paper deals with the design of an autopilot based on a set of fuzzy controllers. The model of the aircraft that the autopilot controls is defined as a model with 6 degrees of freedom, where the inputs to this model are the settings of the engine thrust (DX), rudder rotation (Dl) and elevators (Dm and Dn). The fuzzy controllers are of the Mamdani type, where the set of parameters defining the controller allow the derivation of membership functions of the input variables and membership functions of the output variables. The parameters of fuzzy controllers are determined by the optimization process. For the purpose of optimization, a fitness function is defined, which derives the simulation parameters from its parameter (vector), and the simulation subsequently performed and evaluated determines whether it is a feasible solution in addition the value of this solution. By this optimization process, the sub-optimal solution is found and is then used to define the settings of the fuzzy controllers and, therefore, the autopilot. This paper contains a description of each step of the solution of the described problem, and with the help of the obtained results, it is determined that the presented procedure allows us to find an autopilot capable of controlling the defined model of the aircraft. In addition, there is a brief description regarding the misconceptions explored during the development of the experiment.

Estimating the impact of neonatal abstinence system interventions on Medicaid: an incremental cost analysis

Background Neonatal abstinence syndrome (NAS) incidence has significantly increased in the US in recent years. It is therefore important to develop effective intervention protocols that mitigate the long-term consequences of this condition for the mother, her child, and the community. Methods We used Monte Carlo simulation to estimate the impact of four interventions for NAS and their combinations on pregnant women with opioid use disorder. The key outputs were changes in incremental costs from baseline from the Medicaid perspective and from a total systems perspective and effect size changes. Simulation parameters and costs were based on the literature and baseline model validation was performed using Medicaid claims for Indiana. Results Compared to baseline, the resulting simulation estimates showed that three interventions significantly decreased Medicaid incremental costs by 8% (mandatory opioid testing (MOT)), 4% (patient navigators), and 3% (peer recovery coaches). The combination of the three interventions reduced Medicaid direct costs by 26%. Reductions were similar for total system incremental costs (ranging from 2 to 24%), though MOT was found to increase costs of overdose death based on productivity loss. NAS case reductions ranged from 1% (capacity change) to 13% (MOT). Conclusions Using systems-based modeling, we showed that costs associated with NAS can be significantly reduced. However, effective implementation would require the involvement and coordination of several stakeholders. In addition, careful protocols for MOT should be considered to ensure pregnant women don’t forgo prenatal care for fear of punitive consequences.

The Method of Pose Judgment of Potential Motion Damage in 3D Image Analysis

Objective. This work aimed to study the posture judgment method of 3D image analysis of potential motion damage. Methods. The motion damage collection was implemented by the 3D image analysis method, and 3D image data were adopted to identify the motion damage data. Moreover, 3D image acquisition technology was adopted to analyze the model of potential motion damage and analyze the simulation judgment result of potential motion damage. Specifically, it included simulation parameters, motion damage posture collection effect, damage detection speed at the collection point, damage accuracy, and damage degree. Results. (1) The analysis of the damage monitoring speed at multiple collection points of the athletes in the sports environment confirmed that the range of changes in different time periods was different, and the changes showed a fast to slow to fast trend. (2) The 3D image analysis had high accuracy in analyzing the posture of potential motion damage, which rationalized the evolution of injuries. (3) The degree of motion damage under a 3D image changed from rising to gradual, which was in line with the theoretical results (all p < 0.05). Conclusion. 3D image analysis can collect a high degree of small-sample-size data, then perform specific analysis, judgment, and summary, and finally, obtain objective and reasonable data. It greatly reduced the risk of potential motion damage for athletes and also improved the efficiency of injury recognition. Moreover, it reduced the chances of blind prevention and error prevention by athletes, thereby avoiding waste of resources. The simulation test confirmed the advantages of 3D image data collection in the sports environment, and it was solved that the current athletes cannot accurately and timely judge the potential motion damage. It also met the instability needs of the movement personnel of the acquisition system in the changing sports environment and provided a reliable guarantee for the safety and health of the sport personnel.

Fire Safety of Integrated Pipeline Corridor Cable Block Based on Numerical Simulation

The comprehensive pipe gallery is a tunnel space built underground in the city, which can centrally lay all kinds of municipal pipes in the tunnel for unified management, which can not only protect the pipes, but also improve the land utilization rate. However, with the increasing of integrated pipe gallery construction and pipeline inclusion, various safety accidents have appeared, among which the fire risk of cable cabin is the greatest. This paper mainly studies the fire safety of cable cabins of integrated pipe gallery based on numerical simulation. In this paper, PyroSim fire software was used to simulate the fire accident in construction. Through the investigation of the construction site, simulation parameters were set to simulate the fire situation in a real and objective way. The temperature, smoke and visibility changes under different working conditions were studied by setting several groups of thermocouples, smoke sensing points and visibility slices.