Pub Date : 2023-06-16DOI: 10.1177/00375497231175927
N. Tengesdal, Gaute Fotland, C. Holden, Bjørn Haugen
Simple and computationally efficient drill string models running real-time describing motion in all axes in directional wells are important for the implementation of closed-loop control and assisted monitoring during drilling operations. This paper proposes a new simplified three-dimensional model based on a parametric curve and lumped-parameter modeling, where Kane’s method is used to establish the equations of motion. Validation of the steady-state motion and convergence for the lumped model in vertical and horizontal alignment was compared with a finite-element model. The configuration and restoring forces show good results compared with finite-element analysis. Hence, the model demonstrate the axial contraction as a function of the body restoring forces being oriented to the inertial frame, inherently producing nonlinear coupled axial tension forces. The qualitative response of the model is confirmed in simulation case studies, being showcased by a deviated J-well configuration. Traveling block velocity and top drive torque are included as actuated inputs to analyze off-bottom friction and contact along the wellbore. The model is proposed to act as a virtual sensor for drilling directional wells.
{"title":"Modeling of drill string dynamics in directional wells for real-time simulation","authors":"N. Tengesdal, Gaute Fotland, C. Holden, Bjørn Haugen","doi":"10.1177/00375497231175927","DOIUrl":"https://doi.org/10.1177/00375497231175927","url":null,"abstract":"Simple and computationally efficient drill string models running real-time describing motion in all axes in directional wells are important for the implementation of closed-loop control and assisted monitoring during drilling operations. This paper proposes a new simplified three-dimensional model based on a parametric curve and lumped-parameter modeling, where Kane’s method is used to establish the equations of motion. Validation of the steady-state motion and convergence for the lumped model in vertical and horizontal alignment was compared with a finite-element model. The configuration and restoring forces show good results compared with finite-element analysis. Hence, the model demonstrate the axial contraction as a function of the body restoring forces being oriented to the inertial frame, inherently producing nonlinear coupled axial tension forces. The qualitative response of the model is confirmed in simulation case studies, being showcased by a deviated J-well configuration. Traveling block velocity and top drive torque are included as actuated inputs to analyze off-bottom friction and contact along the wellbore. The model is proposed to act as a virtual sensor for drilling directional wells.","PeriodicalId":49516,"journal":{"name":"Simulation-Transactions of the Society for Modeling and Simulation International","volume":null,"pages":null},"PeriodicalIF":1.6,"publicationDate":"2023-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77074377","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-14DOI: 10.1177/00375497231178303
Carole Adam, Hélène Arduin
This paper describes agent-based models of epidemics dynamics, willingly simplified with the goal not to predict the evolution of the epidemics, but to explain the underlying mechanisms in an interactive way. They allow to compare screening prioritization strategies, and vaccination priority strategies, on a virtual population. The models are implemented in Netlogo in two simulators, published online at https://nausikaa.net/index.php/simulating-epidemics/ to let people experiment. This paper reports on model design, implementation, and experimentations. We have compared screening strategies to assess the epidemics versus control it by quarantining infectious people; and we have compared vaccinating older people with more risk factors, versus younger people with more social contacts.
{"title":"Agent-based epidemics simulation to compare and explain screening and vaccination prioritization strategies","authors":"Carole Adam, Hélène Arduin","doi":"10.1177/00375497231178303","DOIUrl":"https://doi.org/10.1177/00375497231178303","url":null,"abstract":"This paper describes agent-based models of epidemics dynamics, willingly simplified with the goal not to predict the evolution of the epidemics, but to explain the underlying mechanisms in an interactive way. They allow to compare screening prioritization strategies, and vaccination priority strategies, on a virtual population. The models are implemented in Netlogo in two simulators, published online at https://nausikaa.net/index.php/simulating-epidemics/ to let people experiment. This paper reports on model design, implementation, and experimentations. We have compared screening strategies to assess the epidemics versus control it by quarantining infectious people; and we have compared vaccinating older people with more risk factors, versus younger people with more social contacts.","PeriodicalId":49516,"journal":{"name":"Simulation-Transactions of the Society for Modeling and Simulation International","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135915275","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-12DOI: 10.1177/00375497231177123
Zhi Zhu, Tao Wang, H. Sarjoughian, Weiping Wang, Yuehua Zhao
As knowledge and data increase in scale and complexity, it is more difficult to apply these two key assets to achieve optimal effectiveness in engagement simulation. The aim of this study was to investigate the techniques of knowledge and data integration with respect to the development of smart agents to predict accurate behaviors in tactical engagements. To reduce the complexity of combat behavior representation, with respect to the functions, we represented subject matter expert operational knowledge by proposing multiple levels of cascaded hierarchical structure, namely, the function decision tree, to increase the readability and maintainability of the behavioral model. For decision points in a behavioral model, smart agents can be trained based on data samples collected from rounds of constructive simulations which provide validated physical models and tactical principles. As a proof of concept, we constructed a simulation testbed of multi-warhead ballistic missile penetration, which generated 129,600 constructive simulations over a total of 84 h. Thereafter, we selected 5817 data samples (i.e. ~4.5% of the simulations) using an operational metric of total rewards exceeding 100. The data samples are used to train an artificial neural network and then this network is used to develop a deep reinforcement learning agent. The results revealed that the training process iterated nearly 17,000 epochs until the policy loss decreased to an acceptable low value. The smart agent increased the ratio of ballistic missile target hits by 18.96%, a significant increase when compared with the traditional rule-based behavioral model.
{"title":"Knowledge-based and data-driven behavioral modeling techniques in engagement simulation","authors":"Zhi Zhu, Tao Wang, H. Sarjoughian, Weiping Wang, Yuehua Zhao","doi":"10.1177/00375497231177123","DOIUrl":"https://doi.org/10.1177/00375497231177123","url":null,"abstract":"As knowledge and data increase in scale and complexity, it is more difficult to apply these two key assets to achieve optimal effectiveness in engagement simulation. The aim of this study was to investigate the techniques of knowledge and data integration with respect to the development of smart agents to predict accurate behaviors in tactical engagements. To reduce the complexity of combat behavior representation, with respect to the functions, we represented subject matter expert operational knowledge by proposing multiple levels of cascaded hierarchical structure, namely, the function decision tree, to increase the readability and maintainability of the behavioral model. For decision points in a behavioral model, smart agents can be trained based on data samples collected from rounds of constructive simulations which provide validated physical models and tactical principles. As a proof of concept, we constructed a simulation testbed of multi-warhead ballistic missile penetration, which generated 129,600 constructive simulations over a total of 84 h. Thereafter, we selected 5817 data samples (i.e. ~4.5% of the simulations) using an operational metric of total rewards exceeding 100. The data samples are used to train an artificial neural network and then this network is used to develop a deep reinforcement learning agent. The results revealed that the training process iterated nearly 17,000 epochs until the policy loss decreased to an acceptable low value. The smart agent increased the ratio of ballistic missile target hits by 18.96%, a significant increase when compared with the traditional rule-based behavioral model.","PeriodicalId":49516,"journal":{"name":"Simulation-Transactions of the Society for Modeling and Simulation International","volume":null,"pages":null},"PeriodicalIF":1.6,"publicationDate":"2023-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87590940","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-01Epub Date: 2022-11-19DOI: 10.1177/00375497221135214
Abdessalem Jerbi, Faouzi Masmoudi
The development of safe and effective vaccines against COVID-19 has been a turning point in the international effort to control this disease. However, vaccine development is only the first phase of the COVID-19 vaccination process. Correct planning of mass vaccination is important for any policy to immunize the population. For this purpose, it is necessary to set up and properly manage mass vaccination centers. This paper presents a discrete event simulation model of a real COVID-19 mass vaccination center located in Sfax, Tunisia. This model was used to evaluate the management of this center through different performance measures. Three person's arrival scenarios were considered and simulated to verify the response of this real vaccination center to arrival variability. A second model was proposed and simulated to improve the performances of the vaccination center. Like the first model, this one underwent the same evaluation process through the three arrivals scenarios. The simulation results show that both models respond well to the arrival's variability. Indeed, most of the arriving persons are vaccinated on time for all the studied scenarios. In addition, both models present moderate average vaccination and waiting times. However, the average utilization rates of operators are modest and need to be improved. Furthermore, both simulation models show a high average number of persons present in the vaccination center, which goes against the respect of the social distancing condition. Comparison between the two simulation models shows that the proposed model is more efficient than the actual one.
{"title":"Simulation modeling assessment and improvement of a COVID-19 mass vaccination center operations.","authors":"Abdessalem Jerbi, Faouzi Masmoudi","doi":"10.1177/00375497221135214","DOIUrl":"10.1177/00375497221135214","url":null,"abstract":"<p><p>The development of safe and effective vaccines against COVID-19 has been a turning point in the international effort to control this disease. However, vaccine development is only the first phase of the COVID-19 vaccination process. Correct planning of mass vaccination is important for any policy to immunize the population. For this purpose, it is necessary to set up and properly manage mass vaccination centers. This paper presents a discrete event simulation model of a real COVID-19 mass vaccination center located in Sfax, Tunisia. This model was used to evaluate the management of this center through different performance measures. Three person's arrival scenarios were considered and simulated to verify the response of this real vaccination center to arrival variability. A second model was proposed and simulated to improve the performances of the vaccination center. Like the first model, this one underwent the same evaluation process through the three arrivals scenarios. The simulation results show that both models respond well to the arrival's variability. Indeed, most of the arriving persons are vaccinated on time for all the studied scenarios. In addition, both models present moderate average vaccination and waiting times. However, the average utilization rates of operators are modest and need to be improved. Furthermore, both simulation models show a high average number of persons present in the vaccination center, which goes against the respect of the social distancing condition. Comparison between the two simulation models shows that the proposed model is more efficient than the actual one.</p>","PeriodicalId":49516,"journal":{"name":"Simulation-Transactions of the Society for Modeling and Simulation International","volume":null,"pages":null},"PeriodicalIF":1.6,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9679319/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72695554","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-09DOI: 10.1177/00375497231171138
B. Hu, Yuxiao Du
Nowadays, the introduction of digital technology improves the condition of the workplace and employees’ productivity, but the unstable behavior of employees is still typical in Internet enterprises in China. Sometimes, employees frequently show their behavior reversals between cooperation and conflict. An integrated analysis method with three steps is performed to explore its reason. First, an evolutionary game model is employed to examine the strategies of individual employee’s behavior selection between cooperation and conflict. Second, the cellular automata are developed to simulate the evolution of employee group behavior selection over time. The frequent behavior turnovers between cooperation and conflict are illustrated. Third, catastrophe theory and method are used to identify the hidden cusp catastrophe patterns under the evolution of group behavior selection. Research results reveal that individual employee selects cooperation if the penalty exceeds half the cost. Simulation results show intense and sudden changes in employee group behavior selection, in which cusp catastrophe patterns exist. The cusp catastrophe model can intuitively interpret the mechanism by which factors, such as average perceived payoff and proportion of cooperation employees, influence the behavior state of the employee group. The mechanism of catastrophe in frequent behavior turnover is explored. This methodology, which is based on the theoretical framework of social exchange theory, integrates evolutionary game theory, simulation, and catastrophe theory to identify the catastrophe mechanism in behavior turnover and make theoretical and practical contributions to behavior selection research.
{"title":"Integrated analysis of employee cooperation and conflict behaviors in the context of digital technology","authors":"B. Hu, Yuxiao Du","doi":"10.1177/00375497231171138","DOIUrl":"https://doi.org/10.1177/00375497231171138","url":null,"abstract":"Nowadays, the introduction of digital technology improves the condition of the workplace and employees’ productivity, but the unstable behavior of employees is still typical in Internet enterprises in China. Sometimes, employees frequently show their behavior reversals between cooperation and conflict. An integrated analysis method with three steps is performed to explore its reason. First, an evolutionary game model is employed to examine the strategies of individual employee’s behavior selection between cooperation and conflict. Second, the cellular automata are developed to simulate the evolution of employee group behavior selection over time. The frequent behavior turnovers between cooperation and conflict are illustrated. Third, catastrophe theory and method are used to identify the hidden cusp catastrophe patterns under the evolution of group behavior selection. Research results reveal that individual employee selects cooperation if the penalty exceeds half the cost. Simulation results show intense and sudden changes in employee group behavior selection, in which cusp catastrophe patterns exist. The cusp catastrophe model can intuitively interpret the mechanism by which factors, such as average perceived payoff and proportion of cooperation employees, influence the behavior state of the employee group. The mechanism of catastrophe in frequent behavior turnover is explored. This methodology, which is based on the theoretical framework of social exchange theory, integrates evolutionary game theory, simulation, and catastrophe theory to identify the catastrophe mechanism in behavior turnover and make theoretical and practical contributions to behavior selection research.","PeriodicalId":49516,"journal":{"name":"Simulation-Transactions of the Society for Modeling and Simulation International","volume":null,"pages":null},"PeriodicalIF":1.6,"publicationDate":"2023-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88046778","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Medication administration errors account for a relatively high proportion of medical errors, with more than 50% occurring at the nursing administration stage. Nursing is characterized by a large amount of work, rigid working hours, high information cognitive intensity, and frequent information updates. The high workload of nurses is a significant cause of medication administration errors. In this study, a literature analysis was used to determine the elements of the system dynamics model, and the causal loop diagram was used to draw the relationship framework among the elements. Vensim personal learning edition and interview surveys were then used for model validation and simulation. First, 302 case analyses of medication administration errors collected from the three metropolitan area hospitals were used to construct the causal loop diagram, the stock and flow map of the medication administration error system, and the dynamics model; second, the model was tested from theoretical and historical data simulation perspectives; finally, the system dynamics model proposed in this study was used to simulate a medical institution from overtime and policy perspectives. Through system dynamics modeling, the inducing mechanism of workload on medication administration errors in nursing operations was elucidated, and corresponding suggestions for prevention were provided. In addition, ideas and basis for optimizing the medication administration process, improving workload, and preventing medication administration errors considering workload were provided.
{"title":"Effects of workload on medication administration errors in nursing: an analysis based on system dynamics modeling","authors":"H. Jin, Zhibin Xiao, Junhan Yao, Zibo Gong, Haiying Wang, Yinan Zhao","doi":"10.1177/00375497231168631","DOIUrl":"https://doi.org/10.1177/00375497231168631","url":null,"abstract":"Medication administration errors account for a relatively high proportion of medical errors, with more than 50% occurring at the nursing administration stage. Nursing is characterized by a large amount of work, rigid working hours, high information cognitive intensity, and frequent information updates. The high workload of nurses is a significant cause of medication administration errors. In this study, a literature analysis was used to determine the elements of the system dynamics model, and the causal loop diagram was used to draw the relationship framework among the elements. Vensim personal learning edition and interview surveys were then used for model validation and simulation. First, 302 case analyses of medication administration errors collected from the three metropolitan area hospitals were used to construct the causal loop diagram, the stock and flow map of the medication administration error system, and the dynamics model; second, the model was tested from theoretical and historical data simulation perspectives; finally, the system dynamics model proposed in this study was used to simulate a medical institution from overtime and policy perspectives. Through system dynamics modeling, the inducing mechanism of workload on medication administration errors in nursing operations was elucidated, and corresponding suggestions for prevention were provided. In addition, ideas and basis for optimizing the medication administration process, improving workload, and preventing medication administration errors considering workload were provided.","PeriodicalId":49516,"journal":{"name":"Simulation-Transactions of the Society for Modeling and Simulation International","volume":null,"pages":null},"PeriodicalIF":1.6,"publicationDate":"2023-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77590397","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-04-26DOI: 10.1177/00375497231168630
Salma Lahmar, M. Maalmi, R. Idchabani
Multiobjective building design optimization is a challenging problem because it involves finding a set of solutions that simultaneously optimize multiple conflicting objectives. Simulations-based optimization is widely used, but it is a computationally expensive process in terms of time, as it requires a large number of evaluations of the objective functions. Metamodel-based optimization is an alternative to reduce the time-consuming simulations during the optimization process. Metamodels can approximate the building simulation model with analytical expressions. However, the accuracy of metamodels depends on the number of simulations used to train the model and the sampling strategy used to select informative samples over the design space. This study proposes an efficient sequential sampling approach to fit the metamodels toward the regions of the design space where their accuracy is higher and can improve all objectives simultaneously. To demonstrate the effectiveness of this approach, it was applied to optimize the energy and investment costs of a multi-story residential building. The optimization results were compared with those obtained using a non-dominated sorted genetic algorithm II (NSGA-II). The results of this study show that the proposed method reduces the number of building energy simulations required by up to 50% while guaranteeing accurate optimization results. Fifteen energy-efficient buildings designs were proposed, with a wide range of trade-offs between energy and investment costs. This study highlights the potential of the proposed approach to achieve faster and accurate building design optimization and allowing for a larger design space, leading to more creative and innovative solutions.
{"title":"Multiobjective building design optimization using an efficient adaptive Kriging metamodel","authors":"Salma Lahmar, M. Maalmi, R. Idchabani","doi":"10.1177/00375497231168630","DOIUrl":"https://doi.org/10.1177/00375497231168630","url":null,"abstract":"Multiobjective building design optimization is a challenging problem because it involves finding a set of solutions that simultaneously optimize multiple conflicting objectives. Simulations-based optimization is widely used, but it is a computationally expensive process in terms of time, as it requires a large number of evaluations of the objective functions. Metamodel-based optimization is an alternative to reduce the time-consuming simulations during the optimization process. Metamodels can approximate the building simulation model with analytical expressions. However, the accuracy of metamodels depends on the number of simulations used to train the model and the sampling strategy used to select informative samples over the design space. This study proposes an efficient sequential sampling approach to fit the metamodels toward the regions of the design space where their accuracy is higher and can improve all objectives simultaneously. To demonstrate the effectiveness of this approach, it was applied to optimize the energy and investment costs of a multi-story residential building. The optimization results were compared with those obtained using a non-dominated sorted genetic algorithm II (NSGA-II). The results of this study show that the proposed method reduces the number of building energy simulations required by up to 50% while guaranteeing accurate optimization results. Fifteen energy-efficient buildings designs were proposed, with a wide range of trade-offs between energy and investment costs. This study highlights the potential of the proposed approach to achieve faster and accurate building design optimization and allowing for a larger design space, leading to more creative and innovative solutions.","PeriodicalId":49516,"journal":{"name":"Simulation-Transactions of the Society for Modeling and Simulation International","volume":null,"pages":null},"PeriodicalIF":1.6,"publicationDate":"2023-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84449152","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-04-26DOI: 10.1177/00375497231168628
Shanbi Peng, Xue Luo, Bin Yu, Li Huang, Enbin Liu
Negative pressure wards are significant in preventing the spread of infectious pathogens which play a crucial role in fighting against COVID-19. Owing to the negative pressure, contaminated air with pathogens is not able to flow from the wards to non-contaminated zones while fresh filtered air will be transported to the ward via the ventilation system. As airflow controlled by ventilation systems affects the motion of pathogens, for example, infectious aerosol particles, the ability of a negative pressure ward to reduce the risk of infection highly relies on an effective ventilation system. In this investigation, impacts of airflow patterns under various human postures and ventilation processes aerosols diffusion are analyzed via the computational fluid dynamics (CFD) simulation. According to the results, among three airflow patterns, the highest contaminant removal efficiency is 57% at 200 s with the top supply and bottom return mode; besides, in three postures, in the case that the patient is in a standing position, the contaminant removal efficiency is the highest. Furthermore, it is found that the best airflow scheme is a slit tuyere in the ward, with a top supply and side return mode and a sitting position for the patient. This study may provide a reference for the design of airflow in negative pressure isolation wards, control of contaminants, and prevention of viral infections, so as to ensure a good working and recovery environment for medical staff and patients.
{"title":"The airflow distribution and aerosol diffusion rules in the negative pressure isolation ward","authors":"Shanbi Peng, Xue Luo, Bin Yu, Li Huang, Enbin Liu","doi":"10.1177/00375497231168628","DOIUrl":"https://doi.org/10.1177/00375497231168628","url":null,"abstract":"Negative pressure wards are significant in preventing the spread of infectious pathogens which play a crucial role in fighting against COVID-19. Owing to the negative pressure, contaminated air with pathogens is not able to flow from the wards to non-contaminated zones while fresh filtered air will be transported to the ward via the ventilation system. As airflow controlled by ventilation systems affects the motion of pathogens, for example, infectious aerosol particles, the ability of a negative pressure ward to reduce the risk of infection highly relies on an effective ventilation system. In this investigation, impacts of airflow patterns under various human postures and ventilation processes aerosols diffusion are analyzed via the computational fluid dynamics (CFD) simulation. According to the results, among three airflow patterns, the highest contaminant removal efficiency is 57% at 200 s with the top supply and bottom return mode; besides, in three postures, in the case that the patient is in a standing position, the contaminant removal efficiency is the highest. Furthermore, it is found that the best airflow scheme is a slit tuyere in the ward, with a top supply and side return mode and a sitting position for the patient. This study may provide a reference for the design of airflow in negative pressure isolation wards, control of contaminants, and prevention of viral infections, so as to ensure a good working and recovery environment for medical staff and patients.","PeriodicalId":49516,"journal":{"name":"Simulation-Transactions of the Society for Modeling and Simulation International","volume":null,"pages":null},"PeriodicalIF":1.6,"publicationDate":"2023-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75885817","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-04-05DOI: 10.1177/00375497231161146
Xiao-Ting Yuan, Tie-Qiao Tang, Liang Chen, Tao Wang
A cellular automaton (CA) model with a finer discretization of space is proposed to simulate a non-emergency evacuation process in a room with an obstacle. During the evacuation process, a triangle “evading region” phenomenon has been observed through simulation and experiment on the upstream side of the spatial obstacle. In this paper, we use a simple method to generate an obstacle floor field corresponding to the triangle. We investigate the relationship between the pedestrian trajectories and the obstacle’s position. We also study the effect of the obstacle on evacuation time and average evacuation speed. Our study provides insights into the simulation of obstacle avoidance behavior of pedestrians in simple scenarios.
{"title":"A fine grid cellular automaton model for pedestrian evacuation considering the effect of an obstacle","authors":"Xiao-Ting Yuan, Tie-Qiao Tang, Liang Chen, Tao Wang","doi":"10.1177/00375497231161146","DOIUrl":"https://doi.org/10.1177/00375497231161146","url":null,"abstract":"A cellular automaton (CA) model with a finer discretization of space is proposed to simulate a non-emergency evacuation process in a room with an obstacle. During the evacuation process, a triangle “evading region” phenomenon has been observed through simulation and experiment on the upstream side of the spatial obstacle. In this paper, we use a simple method to generate an obstacle floor field corresponding to the triangle. We investigate the relationship between the pedestrian trajectories and the obstacle’s position. We also study the effect of the obstacle on evacuation time and average evacuation speed. Our study provides insights into the simulation of obstacle avoidance behavior of pedestrians in simple scenarios.","PeriodicalId":49516,"journal":{"name":"Simulation-Transactions of the Society for Modeling and Simulation International","volume":null,"pages":null},"PeriodicalIF":1.6,"publicationDate":"2023-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72475141","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-31DOI: 10.1177/00375497231164645
S. Djeffal, Chawki Mahfoudi
Multi-section continuum robots’ (CRs) behavior is still an outstanding problem because of the highly non-linearity of its equation of motions. To this end, in this paper, particle swarm optimization (PSO) is adopted to solve the inverse kinematic model (IKM) of CRs. First, the CR’s structure is properly described. Then, the aforementioned algorithm is elaborately discussed and implemented in figuring out the IKM of CR and verified through forward kinematic model by choosing the PSO parameters, namely, cognitive factors ( C 1 = C 2 = 1 . 2 ) and inertia weight ( ω = 0 . 79 ) for 200 positions on an arc-like trajectory. The optimal angle values ( θ = 0 . 0346 and φ = 0 . 00013 ) which ensure the lowest distance between the attainably desired position and the robot’s end effector are 1 . 04497 × 10 − 9 mm which is perfectly accurate. After that, simulation through MATLAB is carried out, namely, in the first simulation, a three-section CR follows a linear trajectory with a precision approximately equal to 0 . 75 × 10 − 9 mm . Furthermore, PSO takes 7 ms as a mean consumption time to make the robot’s end effector attain to each position. Then, a circular trajectory is followed using PSO. Comparatively speaking, PSO is compared with four meta-heuristic approaches; it is remarked that PSO is a good compromise between accuracy and time consumption. Based on the obtained results, PSO can be considered as a trade-off between accuracy and time consumption for solving the IKM of CRs with complex structure.
{"title":"Inverse kinematic model of multi-section continuum robots using particle swarm optimization and comparison to four meta-heuristic approaches","authors":"S. Djeffal, Chawki Mahfoudi","doi":"10.1177/00375497231164645","DOIUrl":"https://doi.org/10.1177/00375497231164645","url":null,"abstract":"Multi-section continuum robots’ (CRs) behavior is still an outstanding problem because of the highly non-linearity of its equation of motions. To this end, in this paper, particle swarm optimization (PSO) is adopted to solve the inverse kinematic model (IKM) of CRs. First, the CR’s structure is properly described. Then, the aforementioned algorithm is elaborately discussed and implemented in figuring out the IKM of CR and verified through forward kinematic model by choosing the PSO parameters, namely, cognitive factors ( C 1 = C 2 = 1 . 2 ) and inertia weight ( ω = 0 . 79 ) for 200 positions on an arc-like trajectory. The optimal angle values ( θ = 0 . 0346 and φ = 0 . 00013 ) which ensure the lowest distance between the attainably desired position and the robot’s end effector are 1 . 04497 × 10 − 9 mm which is perfectly accurate. After that, simulation through MATLAB is carried out, namely, in the first simulation, a three-section CR follows a linear trajectory with a precision approximately equal to 0 . 75 × 10 − 9 mm . Furthermore, PSO takes 7 ms as a mean consumption time to make the robot’s end effector attain to each position. Then, a circular trajectory is followed using PSO. Comparatively speaking, PSO is compared with four meta-heuristic approaches; it is remarked that PSO is a good compromise between accuracy and time consumption. Based on the obtained results, PSO can be considered as a trade-off between accuracy and time consumption for solving the IKM of CRs with complex structure.","PeriodicalId":49516,"journal":{"name":"Simulation-Transactions of the Society for Modeling and Simulation International","volume":null,"pages":null},"PeriodicalIF":1.6,"publicationDate":"2023-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81541507","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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