SIMULATION: Transactions of The Society for Modeling and Simulation International

Qin, Lincan; You, Zhiwei; Liu, Bo; Luo, Chunmei

doi: 10.1177/00375497241238025pmid: N/A

Objective:A virtual reality (VR)-based training system for combat musculoskeletal trauma care (CMTC) was meticulously crafted to enhance trainees’ theoretical understanding, familiarity with care processes, and decision-making abilities in the realm of combat musculoskeletal trauma management.Method:Scenario scripts, descriptions of injuries, and foundational management plans for care under fire and tactical field care were constructed. Subsequently, the CMTC system was developed employing tools, such as Maya, Photoshop, Unity, SQLite, and Visual Studio. Finally, the system was tested by 30 civilian nurses. The trainees’ knowledge, satisfaction, and system usability were evaluated using the theoretical question bank module, questionnaire, and system usability scale (SUS).Results:This research resulted in the establishment of five types of processes for CMTC in the contexts of care under fire and tactical field care. The study indicated that the trainees’ scores after training (75.67 ± 6.91) was higher than before training (69.17 ± 10.91), p < 0.001, the t-statistic was −5.022. The resultant SUS score was 70.4 ± 9.40. An overwhelming 96.67% of the trainees expressed satisfaction with the teaching quality.Conclusion:The CMTC system, developed in alignment with Tactical Combat Casualty Care (TCCC) guidelines and infused with cutting-edge equipment and technologies, provides an interactive and modular simulation training experience. Its strengths include higher reality, enhanced safety, repeatability, cost-effectiveness, and the provision for performance analysis. Besides, it has good accessibility and reliability, and can cultivate students’ autonomous learning ability and deepen their understanding.

Issakhov, Alibek; Abylkassymova, Aizhan; Minnullina, Saniya

doi: 10.1177/00375497231156455pmid: N/A

In this paper, it was considered a numerical simulation of the water surface movement during the partial collapse of the destruction of a dam with complex terrain. The numerical simulations took into account debris after a partial collapse of the dam, which imitates debris and moves downstream with the water flow. Carrying out these calculations brings the results closer to the real scenario. The mathematical model was based on the Navier–Stokes equations and uses the turbulent large eddy method (LES) model describing the flow of an incompressible viscous fluid. To describe the movement of a two-phase fluid, the volume of fluid (VOF) methods for the phase were used, and the Discrete Phase Model (DPM) and Macroscopic Particle Model (MPM) were used to describe the movement of particles. For the numerical solution of this system of equations, the Pressure Implicit Split Operator (PISO) numerical algorithm was chosen. The results show that the model is accurate and capable of handling very complex interactions such as particle transport or hydrodynamic actions on structures if the appropriate scales are reproduced. Also in this work, a three-dimensional (3D) model of the flow of a dam break on uneven terrain was considered and combined problems were performed that are closer to real conditions. For combined problems, flood zones and flood times were determined, knowledge of which will help evacuate people from dangerous areas. The accuracy of the 3D model and the selected numerical algorithm were verified using two natural measurements.

Hudson, Christopher R; Wheeler, Warren; Goodin, Christopher; Carruth, Daniel W; Harvel, Nicholas; Ferguson, Joshua; Gabriel Monroe, J; McInnis, David P

doi: 10.1177/00375497241261412pmid: N/A

Autonomous ground vehicles (AGVs) operating in off-road terrain are influenced by a variety of factors that are unique to the off-road environment, especially the presence of vegetation. Accurately simulating the performance of AGV requires the creation of off-road virtual worlds that realistically present the characteristics of vegetation to simulations of the tires, chassis, and sensor systems. In this work, we present the development and implementation of a coupled soil moisture and vegetation growth model for generating synthetic off-road terrains for use in AGV simulations. These digital scenes have high geometric fidelity for simulating sensor systems used on AGV like terrestrial lidar. The vegetation model uses stored carbohydrates to predict growth cycles and takes multiple phenomenon into account including soil moisture, weather conditions, and seasonal variations. Results of AGV simulations in synthetic terrains are presented as a demonstration of the models utility.

Guo, Lihao; Li, Guodong; Li, Shanshan; Li, Pengfeng; Wu, Shuang

doi: 10.1177/00375497241261410pmid: N/A

During the construction of a concrete dam, constant strong winds pose a safety risk to the operation of cable cranes, making it difficult to safely place concrete buckets and endangering personnel and property. However, in previous studies, safe operation strategies of cable cranes that did not consider wind conditions had been mainly developed. In this paper, a numerical simulation of the wind environment during the construction of a hydropower station dam project was presented using a three-dimensional computational fluid dynamics method. The wind characteristics of the cable crane operating area are analyzed, and both local and full-section windproof measures are performed. The research findings indicate that full-section windproof measures provide better protection for cable cranes than local windproof measures. The latter only offer sufficient protection when the dam crest elevation is below 700 m. Compared with natural conditions, the low wind speed area of full-section windbreak measures is 10–15 times that of natural conditions. It is 3–10 times that of local wind protection measures. These results will offer significant reference value for similar projects.

Yu, Lugang; Li, Dezhi; Zhou, Shenghua; Zhu, Xiongwei

doi: 10.1177/00375497241265730pmid: N/A

Although the citizens’ satisfaction in smart cities (CSSC) has become a vital criterion for smart cities, which symbolizes the people-centric concept, the previous research on simulating CSSC only considered the technological innovation and policy changes at the macro level, resulting in the neglect of the micro emotional contagion between citizens. To address this gap, a simulation approach is proposed to consider the influence caused by emotional contagion through the agent-based model (ABM). Supported by the expectation confirmation model (ECM) and the emotional contagion theory (ECT), the ABM simulation is implemented through the Anylogic platform, based on survey data from 19 smart cities in China. The results of various scenarios show that citizens’ expectations are the key factor affecting the CSSC, and the influence of emotional contagion cannot be ignored, especially in the acquaintance society. As social networks become more intimate, the impact of emotional contagion will turn the citizen group into an “antithetical society,” which means a situation with severe polarization of CSSC. This study also discusses the possible threshold of this transition process. Based on the analysis of multiple scenarios, it is implied that CSSC should be evaluated by considering the emotional contagion, and smart cities prioritize quality over quantity.

Bortolotto, Mario; Migoni, Gustavo

doi: 10.1177/00375497241261408pmid: N/A

This paper proposes a new modeling approach to obtain accurate and fast simulations of pulse width–modulated (PWM) inverters with minimal loss of information. The idea of this methodology combines the use of precise switched models and fast averaged models. Switched models are used during transient evolution, and averaged models on periodic steady-state (PSS) regimen . In this way, the switching behavior of an inverter can be obtained even in the context of a long-term simulation where switched models cannot be used because of the central processing unit (CPU) requirement. The novel modeling strategy implements an algorithm that, based on the evolution of some variables, detects the transient or periodic steady state condition and automatically performs the commutation between both models. Furthermore, the mentioned algorithm also estimates the averaged model parameters when the precise switched model is used. Consequently, it is not necessary to calculate the average parameters to create the model and accurate results are obtained regardless of the operating point. This paper also reports simulation experiments of a single-phase PWM boost inverter model to clarify the idea of the modeling strategy and shows the simulation time and accuracy advantages of the proposed modeling approach. The Modelica language was used to program the novel modeling strategy and build the boost inverter examples.

Hurtado-Beltran, Antonio; Pérez-Cruz, José R; Madrigal-Arteaga, Víctor M

doi: 10.1177/00375497241284641pmid: N/A

One of the most important characteristics of microsimulation is the ability to model the temporal and spatial nature of traffic demand. Every traffic microsimulation has a vehicle generation model that determines how and when the driver–vehicle units are introduced in the simulation. While microsimulation use has become increasingly popular, it is unclear how the vehicle generation options affect the final result. The purpose of this paper is to examine the stochastic component of the vehicle generation model and how it may affect the simulation output. Three scenarios, including the passenger car equivalent (PCE) model of the Highway Capacity Manual (HCM-7), were used for assessing stochastic volumes and their impacts on performance measures. Results indicate a statistically significant impact of the variability of stochastic volumes on the estimation of performance measures at the breakdown flow phase and synchronized flow phase for interrupted and uninterrupted flow conditions, respectively. This finding highlights the importance of reporting vehicle generation as a calibration parameter, enabling others to replicate the experiments. When utilizing microsimulations for the assessment of roadway/system performance, it is crucial for users to have a thorough understanding of demand generation.