SIMULATION
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SIMULATION ◽  
2022 ◽  
pp. 003754972110699
Author(s):  
José V C Vargas ◽  
Sam Yang ◽  
Juan Carlos Ordonez ◽  
Luiz F Rigatti ◽  
Pedro H R Peixoto ◽  
...  

A simplified three-dimensional mathematical model for electronic packaging cabinets was derived from physical laws. Tridimensionality resulted from the domain division in volume elements (VEs) with uniform properties, each with one temperature, and empirical and theoretical correlations allowed for modeling their energetic interaction, thus producing ordinary differential equations (ODEs) temperatures versus time system. The cabinet (2048 mm × 1974 mm × 850 mm) thermal response with one heat source was measured. Data set 1 with a 1.6-kW power source was used for model adjustment by solving an inverse problem of parameter estimation (IPPE) having the cabinet internal average air velocities as adjustment parameters. Data set 2 obtained with a 3-kW power source validated model results. The converged mesh had a total of 7500 VE. The steady-state solution took between 16 and 19 s of CPU time to reach convergence and less than 3 min to obtain the 6500-s cabinet dynamic response under variable loading conditions, in an Intel CORE i7 computer. After validation, the model was used to study the impact of heat source height on system thermal response. Fundamentally, a sharp minimum junction temperature Tjct,min = 98.5 °C was obtained in the system hot spot at an optimal heat source height, which was 25.7 °C less than the highest calculated value within the investigated range (0.1 m < zjct < 1.66 m) for the 1.6-kW power setting, which characterizes the novelty of the research, and is worth to be pursued, no matter how complex the actual cabinet design may be.


SIMULATION ◽  
2022 ◽  
pp. 003754972110725
Author(s):  
Yu Zhang ◽  
Hongwei Tian ◽  
Ran Li ◽  
Xiaolei Liang ◽  
Jun Li

As an important project on the golden waterway of the Yangtze River in China, the Three Gorges–Gezhouba Dams (TGGD) plays a pivotal role in the construction of the Yangtze River Economic Belt. To improve the efficiency and safety of ship traffic, some novel navigation regulations have been implemented that change the TGGD operation obviously. For example, a piecewise control strategy proposed in the regulations is applied to control the traffic flow of ships under a sectional manner. With the implementation of these regulations, how to understand the dynamic effects of new changes on TGGD has been an important problem. The purpose of this work is to evaluate the navigation performance of the TGGD via a data- and event-driven hybrid simulation model developed by multi-agent and discrete-event modeling theories. The model simulates the three significant navigable scenarios inherent in the actual operating environment: dry season, wet season, and flood season, reflecting the real situations. The input data come from the statistical analysis of the actual navigation data provided by the Three Gorges Navigation Administration. The validity and reliability of the model are verified by comparing the output results with actual data. Moreover, a set of test experiments are designed to explore the TGGD navigation limit and analyze the key factors that restrict the navigation capacity of the TGGD system. The work is expected to provide a certain decision support for the future cooperative scheduling optimization of the TGGD.


SIMULATION ◽  
2022 ◽  
pp. 003754972110688
Author(s):  
Liyan Wu ◽  
Wanpeng Li ◽  
Yonggang Ni ◽  
Wenbing Liu ◽  
Zeyu Liu ◽  
...  

In the context of the rapid development of bionic technology, inspired by the swimming behavior of fish, a variety of robotic fish have been designed and applied to different underwater works and even military applications. However, in some operations, such as detection and salvage, vehicles need to travel under mud, a medium that is different from fluids. This complicating factor put higher requirements on robotic fish design. In this study, Paramisgurnus dabryanus, a fish species adept at swimming into the mud, was taken as a research object to investigate its profile and mud swimming behavior. First, a three-dimensional (3D) image scanner is used for profile scanning to acquire the point cloud data of the profile features of the loach. After modification, data coordinate points are extracted and used to fit the profile curve of loach and build geometric and mathematical models by means of Fourier function fitting. The next step includes the analysis of the motion of loach, determination of main parameters of the wave equation, and establishment of the fish body wave curve of a loach in the swimming using MATLAB software. Saturated mud having a water content of 37% is adopted as an environmental medium to numerically simulate the swimming behavior in mud, identifying the distribution of vortex path, and velocity field of loach’s motion. The rationality of simulation results is verified by the loach mud swimming test, and the simulating results agree well with the experimental data. This study lays a preliminary foundation for the outer contour design of the robotic fish operating under mud and aims to carry out the drag reduction and accelerating design of the robotic fish. The robotic loach may be applied in fishery breeding, shipwreck salvage operations, and so on.


SIMULATION ◽  
2022 ◽  
pp. 003754972110628
Author(s):  
Ali Mollajan ◽  
Hossein Iranmanesh ◽  
AmirHossein Khezri ◽  
Amin Abazari

To control manufacturing processes, integration of flows of manufacturing information is an important starting point. In this regard, an effective Integrated Manufacturing Information System (IMIS) which is capable of monitoring, analyzing, and inspecting manufacturing processes properly is critical. Often, most of difficulties in achieving an effective IMIS stem from a poor design for the system architecture. This study particularly addresses the problem of coupling in architecture of an IMIS and its effect on the system performance. This study employs “Independence Axiom” of the Axiomatic Design (AD) theory to deal with the problem and uses “times in process” and “utilized capacities of available resources” as two important criteria for evaluating the system performance. To verify the proposed methodology, a real IMIS is addressed, its stochastic behavior is simulated in Visual SLAM and AweSim (version 3.o) software environment, and the outcomes are analyzed by using logistic regression method for each level of system decomposition. Results of the analyses indicate that fulfillment of independence axiom of AD theory can significantly enhance performance of the concerned IMIS.


SIMULATION ◽  
2022 ◽  
pp. 003754972110688
Author(s):  
George Datseris ◽  
Ali R. Vahdati ◽  
Timothy C. DuBois

Agent-based modeling is a simulation method in which autonomous agents interact with their environment and one another, given a predefined set of rules. It is an integral method for modeling and simulating complex systems, such as socio-economic problems. Since agent-based models are not described by simple and concise mathematical equations, the code that generates them is typically complicated, large, and slow. Here we present Agents.jl, a Julia-based software that provides an ABM analysis platform with minimal code complexity. We compare our software with some of the most popular ABM software in other programming languages. We find that Agents.jl is not only the most performant but also the least complicated software, providing the same (and sometimes more) features as the competitors with less input required from the user. Agents.jl also integrates excellently with the entire Julia ecosystem, including interactive applications, differential equations, parameter optimization, and so on. This removes any “extensions library” requirement from Agents.jl, which is paramount in many other tools.


SIMULATION ◽  
2021 ◽  
pp. 003754972110641
Author(s):  
Aurelio Vivas ◽  
Harold Castro

Since simulation became the third pillar of scientific research, several forms of computers have become available to drive computer aided simulations, and nowadays, clusters are the most popular type of computers supporting these tasks. For instance, cluster settings, such as the so-called supercomputers, cluster of workstations (COW), cluster of desktops (COD), and cluster of virtual machines (COV) have been considered in literature to embrace a variety of scientific applications. However, those scientific applications categorized as high-performance computing (HPC) are conceptually restricted to be addressed only by supercomputers. In this aspect, we introduce the notions of cluster overhead and cluster coupling to assess the capacity of non-HPC systems to handle HPC applications. We also compare the cluster overhead with an existing measure of overhead in computing systems, the total parallel overhead, to explain the correctness of our methodology. The evaluation of capacity considers the seven dwarfs of scientific computing, which are well-known, scientific computing building blocks considered in the development of HPC applications. The evaluation of these building blocks provides insights regarding the strengths and weaknesses of non-HPC systems to deal with future HPC applications developed with one or a combination of these algorithmic building blocks.


SIMULATION ◽  
2021 ◽  
pp. 003754972110639
Author(s):  
Sogol Mousavi ◽  
Seyed Mojtaba Sajadi ◽  
Akbar AlemTabriz ◽  
Seyyed Esmaeil Najafi

The increasing frequency of natural disasters and the necessity of proper planning to minimize the impact and casualties of such crises have always been matters of great concern to human societies. In this study, a hybrid mathematical-simulative location-allocation model is proposed to carry out disaster management (DM) efforts with maximum coverage in the immediate aftermath of an earthquake. The proposed model consists of two phases: determining the optimal location of the temporary emergency stations (TECs), followed by optimal and hierarchical allocation of casualties to said temporary medical centers (TMCs). Given the contradictory nature of the model’s two objectives, that is, minimizing the cost of setting up TMCs and the time taken to transfer casualties to TMC. In the second phase, a simulation-based optimization approach is employed to simulate casualties’ behavior at the onset of the disaster and to determine the optimal capacity of the medical centers. The findings indicate that the costs and distance traveled by casualties during the earthquake have been reduced by 15%.


SIMULATION ◽  
2021 ◽  
pp. 003754972110633
Author(s):  
Andre N Costa ◽  
Felipe LL Medeiros ◽  
Joao PA Dantas ◽  
Diego Geraldo ◽  
Nei Y Soma

As simulation becomes more present in the military context for variate purposes, the need for accurate behaviors is of paramount importance. In the air domain, a noteworthy behavior relates to how a group of aircraft moves in a coordinated way. This can be defined as formation flying, which, combined with a move-to-goal behavior, is the focus of this work. The objective of the formation control problem considered is to ensure that simulated aircraft fly autonomously, seeking a formation, while moving toward a goal waypoint. For that, we propose the use of artificial potential fields, which reduce the complexities that implementing a complete cognition model could pose. These fields define forces that control the movement of the entities into formation and to the prescribed waypoint. Our formation control approach is parameterizable, allowing modifications that translate how the aircraft prioritize its sub-behaviors. Instead of defining this prioritization on an empirical basis, we elaborate metrics to evaluate the chosen parameters. From these metrics, we use an optimization methodology to find the best parameter values for a set of scenarios. Thus, our main contribution is bringing together artificial potential fields and simulation optimization to achieve more robust results for simulated military aircraft to fly in formation. We use a large set of scenarios for the optimization process, which evaluates its objective function through the simulations. The results show that the use of the proposed approach may generate gains of up to 27% if compared to arbitrarily selected parameters, with respect to one of the metrics adopted. In addition, we were able to observe that, for the scenarios considered, the presence of a formation leader was an obstacle to achieving the best results, demonstrating that our approach may lead to conclusions with direct operational impacts.


SIMULATION ◽  
2021 ◽  
pp. 003754972110648
Author(s):  
Enlai Zhang ◽  
Jiading Lian ◽  
Jingjing Zhang ◽  
Jiahe Lin

Aiming at the characteristics of high decibels and multiple samples for forklift noise, a subjective evaluation method of rank score comparison (RSC) based on annoyance is presented. After pre-evaluation, comprehensive evaluation and data tests on collected 50 noise samples, the annoyance grades of all noise samples were obtained, and seven psycho-acoustic parameters including linear sound pressure level (LSPL), A-weighted sound pressure level (ASPL), loudness, sharpness, roughness, impulsiveness and articulation index (AI) were determined by correlation calculation. Considering the nonlinear characteristics of human ear subjective perception, objective parameters, and annoyance were used as input and output variables correspondingly and then three nonlinear mathematical models of forklift acoustic annoyance were established using traditional artificial neural network (ANN), genetic-algorithm neural network (GANN), and particle-swarm-optimization neural network (PSONN). Moreover, the prediction accuracy of the three models was tested and compared by sample data. The results indicate that the average relative error (ARE) between the experimental and predicted values of acoustic annoyance based on PSONN model is 3.893%, which provides an effective technical support for further optimization and subjective evaluation.


SIMULATION ◽  
2021 ◽  
pp. 003754972110612
Author(s):  
Yi Song ◽  
Bin Hu ◽  
Heqiang Xue

Crowdsourcing logistics is a business model for the modern logistics industry. However, the employee behavior of crowdsourcing logistics remains unstable due to the dynamic nature of crowdsourcing logistics. With a small change in environmental factors, e.g., the delivery price, employee opinion may show frequent polarization or reversal that can lead to employee turnover. To explore the mechanism of sudden change in employee opinion and turnover, a cusp catastrophe model is embedded into the relative agreement (RA) model of opinion dynamics to form a catastrophe-embedded RA model. Text data about employee opinion of the crowdsourcing logistics company DaDa are collected for modeling and validation of the catastrophe-embedded RA model. Simulation experiments explore the impact of network structure and delivery price on employee opinion evolution and employee turnover. The catastrophe theory–embedded RA model extends the application of the RA model in the field of opinion dynamics with frequent polarization or reversal.


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