Search

The attitude of the craftsmen and work station models in embroidery companies that are uncomfortable and safe for the body coupled with work organization that is not yet well organized often causes various problems for the body. The results of previous studies note that there are several angles that need attention: (1) the angle formed between the upper leg and buttocks, (2) the angle formed by the upper arm with the shoulder and (3) the angle formed between the upper arm and the forearm . Based on this, we have designed a work station model that measures the dimensions of the three angles above. However, the model still needs to be tested for community acceptance. The method used in testing the work station model is the acceptance analysis approach using the modified Technology Acceptance Model (TAM) measurement method so that it can be used to determine the level of user acceptance of the work station model created. This research was conducted in three stages by considering several factors, such as the number of researchers, time and budget of funds. Respondents in this study were embroidery workers who had worked for at least 1 year totaling 100 people from various embroidery industries in the city of Tasikmalaya. Before distributing the questionnaire. Respondents are invited to use the work station model for 45 - 60 minutes to carry out sewing activities in general. Because there is only one work station model, each respondent alternates using the work station model until all respondents use it. The trial process lasted for 20 days, namely per day there were 5 respondents who tested using the work station model. Keywords : TAM; Stasion Kera; Bordir

The dense shipping activity in the Surabaya West Access Channel (SWAC) is accompanied by a high rate of piracy which had 13 cases during 2013–2018. An Unmanned Surface Vehicle (USV) with Remote Controlled Weapon Station (RCWS) was created to overcome this piracy, increase work effectiveness, and reduce potential casualties. This study aims to create a design of USV equipped with RCWS complies with the requirements then analyzes the stability and seakeeping (roll motion) because it is one of the most determining factors of the stability and safety of the ship. The research method in this study is a simulation process based on system engineering theory starting from the formulation of requirements, design making, and then simulation. Five design models are created and simulated to analyze their stability and seakeeping performance. The design results are a monohull USV equipped with an RCWS with the main dimension of 1.7 m long, 0.9 m wide, and 1.04 m high. The stability simulations conclude that Model 4 is the most stable platform with the highest peak value of GZ for 0.112 m in angle degree of 108.2°. The seakeeping simulations show that at wave heading 45°, model 3 has the highest RAO with the peak value of 4.703 at the frequency of 0.4 rad/s. At wave heading 90°, model 5 has the highest RAO with the peak value of 0.095 at the frequency of 0.4 rad/s. At wave heading 135°, model 1 has the highest RAO of 0.012 at the frequency of 0.581 rad/s.

Although hydrogen refueling stations (HRSs) are becoming widespread across Japan and are essential for the operation of fuel cell vehicles, they present potential hazards. A large number of accidents such as explosions or fires have been reported, rendering it necessary to conduct a number of qualitative and quantitative risk assessments for HRSs. Current safety codes and technical standards related to Japanese HRSs have been established based on the results of a qualitative risk assessment and quantitative effectiveness validation of safety measures over ten years ago. In the last decade, there has been much development in the technologies of the components or facilities used in domestic HRSs and much operational experience as well as knowledge to use hydrogen in HRSs safely have been gained through years of commercial operation. The purpose of the present study is to conduct a quantitative risk assessment (QRA) of the latest HRS model representing Japanese HRSs with the most current information and to identify the most significant scenarios that pose the greatest risks to the physical surroundings in the HRS model. The results of the QRA show that the risk contours of 10−3 and 10−4 per year were confined within the HRS boundaries, whereas the risk contours of 10−5 and 10−6 per year are still present outside the HRS. Comparing the breakdown of the individual risks (IRs) at the risk ranking points, we conclude that the risk of jet fire demonstrates the highest contribution to the risks at all of the risk ranking points and outside the station. To reduce these risks and confine the risk contour of 10−6 per year within the HRS boundaries, it is necessary to consider risk mitigation measures for jet fires.

This paper deals with the proposal of the reworking station in the automotive company. The paper consists of four parts. The first part is about Tecnomatix Plant Simulation, which is now one of the best software for simulation tasks. The second part deals with analysis of real production process in the selected company and some parts are also dedicated to the main product – external handle. The third part treats with simulation of production process in Plant Simulation in selected company and the final fourth part is oriented on proposal of the reworking station in Plant Simulation.

This paper presents a grid impact analysis of heavy-duty electric vehicle (EV) charging stations. In this work, heavy-duty EVs have battery capacities high enough to provide a range of 250–500 miles on a single charge, such as long-haul trucks. Heavy-duty EVs will require extremely fast charging rates to reduce charging time and will induce very high charging loads (at the multiple-megawatt scale) if several vehicles charge at the same time. Therefore, analysis is needed to understand the impact of charging station loads on the electric power grid and set the baseline for developing mitigation plans and necessary system upgrades. We develop a systematic procedure to analyze the potential impact of the placement of charging stations on the grid. Charging load is modeled using a DC fast-charging station model. A voltage load sensitivity matrix approach is leveraged to investigate the challenges of placing charging stations on the feeder. Given the charging load profiles and suggested charging station locations, time-series simulations are performed on various connection points on the feeder to understand the impact. The analysis is performed on both the IEEE 34-bus system and a realistic feeder from California. Initial mitigation solutions are developed based on insights from this analysis.

Evacuation is a critical issue at metro stations, where damage, or even death, could be caused due to unexpected accidents if without proper evacuation. Multi-objectives are often desired in the evacuation management, and evacuation strategies should be tailored due to the dynamic features of overcrowded passengers and high uncertainty at the metro stations. A simulation-based approach integrating Light Gradient Boosting Machine (LightGBM) and Non-dominated Sorting Genetic Algorithm III (NSGA-III) is proposed to realize the automatic evacuation evaluation and adaptive optimization at metro stations. A framework consisting of 3 objectives and 9 influential factors is developed for the evacuation evaluation and adaptive optimization. A LightGBM based meta-model is used to construct the relationship between influential factors and objectives. A LightGBM and NSGA-III integrated optimization algorithm is employed to automatically evaluate the evacuation events and seek the adaptive strategies for the station renovation in order to achieve a safe evacuation under specific conditions. A station model simulating a metro station in Singapore is constructed to test the effectiveness and applicability of the proposed approach. It is found that (1) Among 50 target station based cases, 33 failing cases (at least one of the objectives fails) are identified, and the automatic evaluation results indicate the studied metro station could successfully evacuate the passengers when the passenger volume is no more than 1000, but it is very likely to fail when a higher volume exists; (2) Adaptive optimization strategies can be found for every different scenario, and an average 24.8% of the improvement degree can be achieved for all scenarios; (3) The adaptive multi-objective optimization is more cost-effective, presenting an average cost efficiency 2.04, which is significantly higher than the average of the non-adaptive optimization cost efficiency, 0.57. The novelty of this research lies in that (a) A LightGBM-based meta-model is built to construct the relationship between desired multi-objectives and the influential factors, which lays the foundation for the evacuation management from multi-objective optimization perspective; (b) The LightGBM and NSGA-III integrated model can realize the automatic evacuation evaluation and accordingly provide the adaptive strategies under specific conditions. Ministry of Education (MOE) Nanyang Technological University The Ministry of Education Tier 1 Grants, Singapore (No. 04MNP000279C120, No. 04MNP002126C120) and the Start-Up Grant at Nanyang Technological University, Singapore (No. 04INS000423C120) are acknowledged for their financial support of this research.

Evacuation is critical for safety management due to the highly overcrowded passengers in the metro stations. A simulation-based approach integrating Random Forest (RF) and Non-dominated Sorting Genetic Algorithm III (NSGA-III) is proposed to perform the evacuation evaluation and optimization at metro stations. A 3D model of the metro station is built to simulate the dynamic process of passenger evacuation in metro stations. A framework consisting of 9 influential factors and 3 objectives is developed to model the input-output relationship in passenger evacuation. An RF-based meta-model is used to construct the relationship between influential factors and objectives. At last, NSGA-III is applied to seeking the optimal solutions for the station renovation in order to achieve a safe evacuation. A station model simulating a real metro station in Singapore is constructed to test the effectiveness and applicability of the proposed approach. It is found that (1) A safe evacuation could be achieved for the station, but along with the increasing passenger volume and panic level, the requirement of evacuation objectives, the evacuation time and density, may not be met. Especially under the high passenger volume conditions, the passenger density could reach up to 6.2 unit/m2 (extremely dangerous); (2) An average improvement degree, 7.5%, can be achieved for the optimization of 20 test cases, and a maximum improvement degree, 22.5%, can be achieved for the evacuation optimization at metro stations; (3) It could be difficult to keep both of the evacuation time and density within the standards if one major exit is closed, even after the optimization. But a larger average improvement degree, 10.8%, can be achieved by the proposed optimization approach, which indicates the optimal solutions still could reduce the risk to a great extent. The novelty of this research lies in that (a) An RF algorithm is incorporated to build the meta-model that can properly represent the relationship between influential factors and objectives, despite the complexity and even conflicting between them; (b) Optimal measures for the evacuation improvement are provided from the MOO perspective by integrating NSGA-III. This hybrid approach can be used as a decision tool to assist regulatory authorities in developing effective emergency evacuation evaluation and optimization plans with adequate consideration of the complexity and multi-objective nature under evacuation events. Ministry of Education (MOE) Nanyang Technological University The authors declare no conflict of interest. The Ministry of Education Tier 1 Grant, Singapore (No. 04MNP002126C120, No. 04MNP000279C120) and the Start-Up Grant at Nanyang Technological University, Singapore (No. 04INS000423C120) are acknowledged for their financial support of this research. The 1st author is grateful to Nanyang Technological University, Singapore for his Ph.D. research scholarship.

Large-scale passenger flows occur frequently during the peak hours of urban rail transit stations and on holidays. Thus, the timely and accurate early warning of impending large-scale passenger flows can positively impact the operational safety of the entire station. By further deepening the definition of passenger flow warnings in stations, a new model of urban rail transit station passenger flow based on system dynamics is constructed. The method of determining the key area of passenger flows in the early warning stage based on streamlines is proposed; the key indicators and thresholds affecting early warnings are studied. Finally, taking a typical station as an example, a station model is built using Anylogic software. The parameter sensitivity analysis is used to determine the impact of each key indicator on the passenger flow in the key area of the station early warning, and the reference threshold of each indicator is determined.

Soil station system seismic issues have been highly valued in recent years. In order to investigate the dynamic seismic behaviors of the intermediate column in soil station systems, a hybrid test of a soil station system was conducted. The soil station model was performed with OpenSees. Virtual hybrid simulation was fulfilled with adapter elements. A hybrid model, composed of the steel column specimen and the remainder numerical model, was assembled using the OpenFresco framework. An intermediate column was treated as the physical substructure, while the rest of the soil station system was treated as the numerical substructure in a hybrid simulation. The hybrid test results are compared with the analytical results. The data obtained from such tests show that the system can accurately reflect the mechanical properties of intermediate columns in soil station systems. A hybrid simulation would be a proper way to assess the seismic performance of a soil station system.

The construction of the TOD apartment at the Pondok Cina Station will have an impact on the level of service at the venue. This has a positive impact because there is an increase in KRL users, but it also has the potential to cause problems due to the increased volume. This study aims to analyze the impact of TOD station Pondok Cina apartment development on station service level in 2022 condition and find the best solution to improve service level. The station model is created using PTV VISWALK 10. Validation testing is needed to determine the model is acceptable or not by comparing the model results and actual conditions in the field. Analysis of service level using HCM as a reference. There are several models performed, such as the condition of existing year 2018, condition year 2022 without apartment, condition 2022 with apartment, and alternative condition. Alternative conditions of total change in Pondok Cina station. After the simulation, see the performance of all models based on service level and travel time. The result show given the influence of the apartment, if nothing is done then the level of service worsens from LOS B to LOS E while travel time increases drastically from 78 seconds to 429 seconds by 2022.

Taiwan is located at the junction of the tropical and subtropical climate zones adjacent to the Eurasian continent and Pacific Ocean. The island frequently experiences typhoons that engender severe natural disasters and damage. Therefore, efficiently estimating typhoon rainfall in Taiwan is essential. This study examined the efficacy of typhoon rainfall estimation. Radar images released by the Central Weather Bureau were used to estimate instantaneous rainfall. Additionally, two proposed neural network-based architectures, namely a radar mosaic-based convolutional neural network (RMCNN) and a radar mosaic-based multilayer perceptron (RMMLP), were used to estimate typhoon rainfall, and the commonly applied Marshall&ndash, Palmer Z-R relationship (Z-R_MP) and a reformulated Z-R relationship at each site (Z-R_station) were adopted to construct benchmark models. Monitoring stations in Hualien, Sun Moon Lake, and Taichung were selected as the experimental stations in Eastern, Central, and Western Taiwan, respectively. This study compared the performance of the models in predicting rainfall at the three stations, and the results are outlined as follows: at the Hualien station, the estimations of the RMCNN, RMMLP, Z-R_MP, and Z-R_station models were mostly identical to the observed rainfall, and all models estimated an increase during peak rainfall on the hyetographs, but the peak values were underestimated. At the Sun Moon Lake and Taichung stations, however, the estimations of the four models were considerably inconsistent in terms of overall rainfall rates, peak rainfall, and peak rainfall arrival times on the hyetographs. The relative root mean squared error for overall rainfall rates of all stations was smallest when computed using RMCNN (0.713), followed by those computed using RMMLP (0.848), Z-R_MP (1.030), and Z-R_station (1.392). Moreover, RMCNN yielded the smallest relative error for peak rainfall (0.316), followed by RMMLP (0.379), Z-R_MP (0.402), and Z-R_station (0.688). RMCNN computed the smallest relative error for the peak rainfall arrival time (1.507 h), followed by RMMLP (2.673 h), Z-R_MP (2.917 h), and Z-R_station (3.250 h). The results revealed that the RMCNN model in combination with radar images could efficiently estimate typhoon rainfall.

This paper deals with the model of a biogas station. The introduction provides a description of principle employed in this model. The model works with data reflecting the quantity and type of the input biomass to determine the potential energy and offer a selection from various co-generation units. Other important input parameters comprise fermentors and mainly the material composition of their walls to help with determination of heat losses. The input parameters are accompanied by the energetic balance model for a Biogas Station (BPS) concerned. The next section of this paper provides verification of the model with respect to an actual BPS subject to a series of measurements. These measurements focus on electric and heat parameters. The outcome from these measurements was then used to obtain the energetic balance figure. The comparison of measurement results against the model produces slight deviations of the model from the real biogas station only. This paper has been processed pursuant to a long-term research on biogas stations. The biogas station model will be developed further to obtain a more detailed energetic balance for the biogas station.

Campus Express is an important window to observe the city consumption logistics service "last kilometer".The research on Campus Express service is not only conducive to campus environment improvement and service quality promotion, but also provides all types of community, agglomeration areas such as urban terminal "last kilometer" logistics with reference.This article first proposed the main problems of campus express service,analyzed the mode of smart express station and finally built a smart express station.

The paper presents the research undertaken to design and develop a 3D sustainable renewable power station model that is sustainable, competent and of high efficiency at reasonable cost. The paper focuses on the optimization of the 1D micro Hydropower systems. The constant and secure supply of green power is made possible through combined power plant using renewable energies resources. Studies reveal that water wheels are not as efficient as turbines but could offer efficiency in excess of 80% for overshoot & undershoot water wheels, with 75% for breastshot water wheels. The technical issues that limit the water wheel efficiency have been studied and a new design is presented in this paper. The simulation to the new design is hereby presented and some experimental measurements of efficiency and power can be delivered Keywords: 3D sustainable power station, Hydro wheels / turbines, efficiency.

Rapid development of the hydroelectric power industry has raised concerns about the stability of hydroturbine units among the scientific and engineering communities. Most existing approache...

KEYWORD This study analyzed the electric vehicle recharging station status with recharging time limitation due to long waitingtime, and figured out the user status by user interviews. And then this study verified the validity of hypothesis in terms of environmental design perspective and suggested layout of recharging station model. 21 recharging stations in Kore a and station operation cases of 7 countries were examined. Except for the USA, the reality of electric vehicle rechargingstation today is the 1st proving stage focusing on the infrastructure construction of electric vehicle recharging station. It focuses on performance of recharging facility, use efficiency and operation environment of electric vehicle. About the effective waiting time of the user to use it should be studied. The current conditions of recharging station are as follows :Lack of independent recharging space, lack of facility that reduces external effect of recharging space, and lack of lounge for users during the waiting time. These three are essential factors constructing a suggesting model after basic layout, which needs proper measurement on the long recharging time and long waiting time. The essential factors are applied to electric vehicle recharging station layout so that users might use ‘digital refresh” i.e. lounge and informatio ncontents service during the waiting time which provides convenience of recharging and emotional space with users. Such upgrade recharging station environmental model might resolve the burden of long recharging time which may contribute to the popularization of electric vehicles.ⓒ 2014 KIEAE Journal

The purpose of the work is to review and compare the existing paradigms of simulation modeling, as well as to choose the appropriate method of modeling the technological processes of rail transport systems to assess the operational reliability of its infrastructure. Results. The article highlights the main problems with the functioning of Ukrainian rail transport, which reduce its operational reliability. To solve the problem of obtaining an adequate assessment of the operational reliability of railway systems, it is proposed to use a simulation method. At present, three independent paradigms have emerged in simulation modeling – system dynamics, agent modeling, and discrete event modeling. These paradigms correspond to different levels of abstraction when creating a model, which requires the use of one or another approach. The paper describes the comparative characteristics of simulation approaches, their advantages and disadvantages. The origin history, implementation tools, features and scope of each simulation approach are considered. The expediency of modeling of dynamic processes on railway transport by discrete-event simulation is substantiated. The method and algorithms of formalization in the simulation model of the shunting work of a railway station are considered. The station model was created in the AnyLogic simulation environment and allows to evaluate the operational reliability of a railway station based on the magnitude of delays and downtime of rolling stock at the station due to the occupancy of tracks and locomotives. The practical significance of the work performed is to be able to more rationally approach the approach of modeling the work of different systems in solving problems related to obtaining a reliable estimate of their technical and technological parameters and operational reliability.

Electric vehicle (EV) is a promising technology for reducing environmental impacts of road transport. In this paper, a framework for optimal design of battery charging/swap stations in distribution systems based on life cycle cost (LCC) is presented. The battery charging/swap station models are developed to compare the impacts of rapid-charging stations and battery swap stations. Meanwhile, in order to meet the requirements of increased power provided during the charging period, the distribution network should be reinforced. In order to control this reinforcement cost, stations should be placed at appropriate places and be scaled correctly. For optimal cost-benefit analysis and safety operation, the LCC criterion is used to assess the project and a modified differential evolution algorithm is adopted to solve the problem. The proposed method has been verified on the modified IEEE 15-bus and 43-bus radial distribution systems. The results show that battery swap station is more suitable for public transportation in distribution systems.

This study was initiated to validate a tomato powdery mildew, caused by Leveillula taurica (Lev.) Arn., forecast model in Egypt. Environmentally acceptable control may be achieved using a weather based forecasting system due to the reduced use of agrochemicals and their residues in both environment and food. A computerized disease forecast model for tomato powdery mildew (Egy. Tom-PM) as named by the authors was validated during the 2006 and 2007 growing seasons. The micrometeorological parameters monitored hourly in tomato cano- py were ambient air temperature, relative humidity, leaf wetness duration, wind speed and global radiation using a wireless real-time automatic Agro-weather station model (Adcon Telemetry model A733, add wave). Results indicated that Egy.Tom-PM forecast model accurately defined disease risk appearance and reduced number of sprays in both years compared with the routine application (10D) and (7D) sprays in 2006 and 2007 respectively. Basic roles of system analysis for model validation and evaluation are discussed.

In recent years, service delivery systems employing a self-service approach have been rapidly spreading. Since a self-service system provides a lower product price, it attracts more customers. However, some system managers are still hesitant to accept a self-service system, because there is no systematic model to predict its performance. Therefore, this research attempts to provide a systematic and quantitative model to predict the performance of a self-service system, focused specifically on a self-service gas station. Under this model, the traditional queuing theory was adopted to describe the general self-service process, but it is also assumed that some changes occur in both the customer arrival rate and the service performance rate. In particular, the price elasticity was introduced to capture the change in the customer arrival rate, and the existence of learning effect and helpers were assumed to design the changed service performance rate. Under these assumptions, a simulation model for a self-service gas station is established, and three performance measurements, such as average number of customers, average waiting time, and Utilization are observed, depending on the changes in price difference and helper-operating time. In this research, the optimal operation strategy for price differentiation and helper-operating time is proposed in accordance with the level of the customer learning rate. Although this research confines the scope of the study to the self-service gas station model, the results of this research can be applied to any type of self-service system.

In this study, a System Dynamics (SD) simulation model for the efficient operations of an industrial water supply system was developed by investigating the feedback loop mechanisms involved in the operations of the system. The system was modeled so that as demand is determined the water supply quantity of intake pumping stations and dams are allocated. The main feedback loop showed that many variables such as the combinations of pump operation, unit electric power(kWh/), unit electric power costs(won/), water level of water way tunnel, suction pressure and discharge of pumping station, and tank and service reservoir water level had causal effects and produced results depending on their causal relationship. The configurations of the model included an intake pumping station model, water way tunnel model, pumping station model (including the tank and service reservoir water level control model), and unit electric power model. The model was verified using the data from the case study industrial water supply system that consisted of a water treatment plant, two pumping stations and four dams with an annual energy costs of 5 billion won. It was shown that the electric power costs could have been saved 7~26% during the past six years if the operations had been based on the findings of this study.

Synchronization stations are commonly used to model kitting operations in manufacturing systems. At a kitting station, the components required for assembly are grouped together prior to release to the assembly line. When the supply process of components is stochastic, exact analysis is hard in a general setting. This paper presents an approximate analysis of a kitting station with multiple components. The stochastic supply process of each component is characterized by mean and variability parameters of the corresponding fabrication facility, and the system imposes a limit on total inventory for each component. The resulting synchronization station model is analyzed using an aggregation procedure that uses the analysis of a synchronization station with two inputs as a key building block. Numerical results indicate that the estimates of throughput and queue length obtained from the analysis validate well with those obtained from detailed simulations. The analysis also helps to quantify the effect of the number of components and variability on kitting delays.

A composite line source emission (CLSE) model was developed to specifically quantify exposure levels and describe the spatial variability of vehicle emissions in traffic interrupted microenvironments. This model took into account the complexity of vehicle movements in the queue, as well as different emission rates relevant to various driving conditions (cruise, decelerate, idle and accelerate), and it utilised multi-representative segments to capture the accurate emission distribution for real vehicle flow. Hence, this model was able to quickly quantify the time spent in each segment within the considered zone, as well as the composition and position of the requisite segments based on the vehicle fleet information, which not only helped to quantify the enhanced emissions at critical locations, but it also helped to define the emission source distribution of the disrupted steady flow for further dispersion modelling. The model then was applied to estimate particle number emissions at a bi-directional bus station used by diesel and compressed natural gas fuelled buses. It was found that the acceleration distance was of critical importance when estimating particle number emission, since the highest emissions occurred in sections where most of the buses were accelerating and no significant increases were observed at locations where they idled. It was also shown that emissions at the front end of the platform were 43 times greater than at the rear of the platform. Although the CLSE model is intended to be applied in traffic management and transport analysis systems for the evaluation of exposure, as well as the simulation of vehicle emissions in traffic interrupted microenvironments, the bus station model can also be used for the input of initial source definitions in future dispersion models.

In the railway domain, an interlocking is a computerised system that controls the railway signalling objects in order to allow a safe operation of the train traffic. Each interlocking makes use of particular data, called application data, that reflects the track layout of the station under control. The verification and validation of the application data are performed manually and is thus error-prone and costly. In this paper, we explain how we built an executable model in NuSMV of a railway interlocking based on the application data. We also detail the tool that we have developed in order to translate the application data into our model automatically. Finally we show how we could verify a realistic set of safety properties on a real-size station model by customizing the existing model-checking algorithm with PyNuSMV a Python library based on NuSMV., Comment: In Proceedings ESSS 2015, arXiv:1506.03250

Stochastic daily weather time series models (‘‘weather generators’’) are parameterized consistent with both local climate and probabilistic seasonal forecasts. Both single-station weather generators, and spatial networks of coherently operating weather generators, are considered. Only a subset of parameters for individual station models (proportion of wet days, precipitation mean parameters on wet days, and daily temperature means and standard deviations) are found to depend appreciably on the seasonal temperature and precipitation outcomes, so that extension of the single-station models to coherent multisite weather generators is straightforward. The result allows stochastic simulation of multiple daily weather series, conditional on seasonal forecasts. Example applications of spatially integrated extreme daily precipitation and snowpack water content are used to illustrate the method.

With the rapid growth of High-Speed Railway network in China, more and more stations has been designed. Based on the work of planning practice, this article has analyzed the influencing factors of proper supplement of parking space in High-Speed Railway Stations with analogy and parking turnover method, and taking East Ji'nan High-Speed Railway Station as an example to give recommended values.

The seasonal production of fruit and seeds resembles opening a feeding station, such as a restaurant agents/ customers will arrive at a certain rate and pick fruit (get served) at a certain rate following some appropriate processes. Therefore, dispersion follows the resource process. Modelling this process results in a search/optimisation algorithm that used dispersion as an exploration tool that, if well captured, will find the optimum of a function over a given search space. This paper presents such an algorithm and tests it on non-trivial problems., http://repository.essex.ac.uk/9973/

Un modèle structurel est fourni afin d'appréhender les phénomènes de capacité dans un modèle d'affectation de flux de voyageurs sur un réseau de transport collectifs. Cela a été fondé sur une représentation du réseau de transports collectifs en deux couches : sur la couche inférieure, le modèle traite séparément chaque sous système du réseau (ligne, station et rabattement) en fonction des effets de capacité spécifiques ; sur la couche supérieure, le choix d'itinéraire d'un voyageur individuel est adressée par une représentation du réseau en leg (ou segment de ligne) en utilisant le coût et les caractéristiques opérationnelles des sous-systèmes respectifs. On établit une cadre novateur pour modéliser les effets de capacité et on développe le modèle CapTA (pour Capacitated Transit Assignment). Il s'agit d'un modèle d'affectation de flux systémique et modulaire. Il adresse les phénomènes de capacité ci dessous : La qualité du service en véhicule est liée au confort de voyageurs à bord. L'occupation d'états de confort hétérogènes (places assises, strapontins et debout à de densités de voyageurs variables) influence la pénibilité perçu du voyage ; La capacité du véhicule à la montée impacte le temps d'attente de voyageurs et leur distribution aux missions disponibles ; La capacité de l'infrastructure de la ligne établit une relation entre le temps de stationnement des véhicules (and par extension les flux de voyageurs en montée et en descente) et la performance des missions et leur fréquence de service. Ces phénomènes sont traités par ligne d'exploitation sur la base d'un ensemble des modèles locaux qui rendent de flux et de coût spécifiques. Par conséquent, ils modifient les conditions locales d'un trajet en transports collectifs pour chaque voyageur individuel. Cependant, ils doivent être adressés dans le cadre d'un réseau de transports collectifs afin de recueillir leur effet sur les choix d'itinéraire sur le réseau ; essentiellement sur les arbitrages économiques qui impactent le choix entre itinéraires alternatifs. Leur traitement sur la couche réseau garantir la cohérence du choix d'itinéraire. Le modèle de station traite de contraintes de capacité spécifiques et évalue les conditions locales de marche, qui est sensible aux interactions des voyageurs à l'intérieur de la station : le goulot instantané à l'entrée d'un élément de circulation retard l'évacuation de la plateforme ; la densité de voyageurs et l'hétérogénéité des leur flux ralenti les voyageurs qui circulent dans une station ; la présence de l'information en temps réel influence le processus de décision des voyageurs. Ces effets n'ont pas seulement un impact sur le choix d'itinéraire à l'intérieure de la station, mais notamment ils modifient les choix de service sur le niveau du réseau. La Région Ile-de-France fournit un champ d'application idéal pour un modèle d'affectation de flux de voyageurs en transport collectifs sous contraintes de congestion. Plus précisément, il est utilisé dans le cadre du modèle CapTA pour illustrer les capacités de simulation et la finesse de l'approche de modélisation adoptée. Le réseau de transports collectifs contient 1 500 missions de cars et autocars, tout comme 260 missions ferroviaires et inclut 14 lignes de métro et 4 lignes de tramway. L'affectation de trafic à l'heure de pointe du matin est caractérisée d'une charge importante en voyageurs sur les sections centrales de lignes ferroviaires qui traversent la ville. Un temps de stationnement élevé, en raison de flux de montée et descente, et la réduction de la fréquence de service impactent la capacité des missions et des lignes. Le temps généralisé d'un trajet est impacté notamment de sa composante de confort à bord. De résultats détaillés sont présentés sur le RER A, la ligne la plus chargée du réseau ferroviaire régional. A structural model is provided to capture capacity phenomena in passenger traffic assignment to a transit network. That has been founded on a bi-layer representation of the transit network : on the lower layer the model addresses each network sub-system (line, station and access-egress) separately, on the basis of specific capacity effects ; on the upper layer a leg-based representation is used with respect to the sub-systems' costs and operating characteristics to address the trip maker's path choices. We establish a novel framework for modelling capacity effects and develop the CapTA network model (for Capacitated Transit Assignment). It is systemic and modular and addresses in particular the following capacity phenomena, the in-vehicle quality of service is linked to the comfort of the passengers on-board. The occupation of heterogeneous comfort states (seats, folding seats and standing at different passenger densities) influences the perceived arduousness of the travel ; the vehicle capacity at boarding influences the waiting time of the passengers and their distribution to the transit services ; the track infrastructure capacity relates the dwelling time of the vehicles (and by extent the alighting and boarding flows) with the performance of the transit services and their service frequency. These phenomena are dealt with by line of operations on the basis of a set of local models yielding specific flows and costs. Accordingly, they modify the local conditions of a transit trip for each individual passenger. However, these should be addressed within the transit network in order to capture their effect on the network path choices; essentially the economic trade-offs that influence the choice between different network itineraries. Their treatment in a network level assures the coherence of the path choice. Equivalently, a station sub-model addresses specific capacity constraints and yields the local walking conditions, sensible to the interaction of the passengers in the interior of a station : the instant bottleneck created at the entry of the circulation elements delays the evacuation of the station platforms; the passenger density and presence of heterogeneous passenger flows slows down the passengers who circulate in the station; and the presence of real-time information influences the decision making process of the transit users exposed to. These effects do not only impact locally the in-station path choice, but most notably they modify the choices of transit routes and itineraries on a network level. The Paris Metropolitan Region provides an ideal application field of the capacity constrained transit assignment model. It is mainly used as a showcase of the simulation capabilities and of the finesse of the modelling approach. The transit network involves 1 500 bus routes together with 260 trains routes that include 14 metro lines and 4 light rail lines. Traffic assignment at the morning peak hour is characterized by heavy passenger loads along the central parts of the railway lines. Increased train dwelling, due to boarding and alighting flows, and reduction in the service frequency impact the route and the line capacity. The generalized time of a transit trip is impacted mainly though its in-vehicle comfort component. Detailed results have been provided for the RER A, the busiest commuter rail line in the transit network.

The flow field and the train wind reduction effect in the subway station are experimentally examined for three kinds of station model with staircases and tunnels. As the results, prototype model consisting of station and shortened tunnels with orifices can clarify the overall flow characteristics. However, this model is not able to reproduce the time history of the wind velocity at the tunnels and the staircase parts in the real subway. One-station model having the same reduced stale ratio for the tunnels and the station is generally useful to evaluate the wind velocity and the air quantity. Two-stations model connecting two one-station models is most effective to evaluate the transient flow characteristics with high accuracy. In the next place, three train wind reduction methods are tested. The one blower control method which is the tunnel ventilation in accordance with the train wind can reduce the wind velocity at a staircase about 0.5 m/s. Furthermore, two blowers control method can reduce it about 1 m/s. In the case of natural draft method, the wind reduction value is 0.7-1.1 m/s and this reduction effect becomes 1.8 times for the usual staircase with small cross section.

The Train Control Language (TCL) is a domain-specific language that allows automation of the production of interlocking source code. From a graphical editor a model of a train station is created. This model can then be transformed to other representations, e.g. an interlocking table and functional blocks, keeping the representations internally consistent. Formal methods are mathematical techniques for precisely expressing a system, contributing to the reliability and robustness of the system through analysis. Traditionally, applying formal methods involves a high cost. This paper presents a formalization of TCL, including its behavior expressed in the constraint solving language Alloy. We show how analysis of station models can be performed automatically. Analysis, such as simulation of a station, searching for dangerous train movements and deadlocks, is used to illustrate the approach.

Orbiting very long baseline interferometry based on radio transmission of a reference signal from an Earth-bound oscillator is considered. This method provides the possibility of forming a connected-element interferometer between the spacecraft and an Earth radio telescope co-located with the reference oscillator. The reference signal from the spacecraft to the Earth is retransmitted and the round-trip time is continuously measured by assuming reciprocity of the path; the time at the spacecraft is always known relative to a clock on the Earth. The author is concerned with the design of such a round-trip reference system and its accuracy limitations. Spacecraft and Earth station models, continuous contact and simple-frequency timing, ambiguity-free timing link design, and the onboard synthesizers are discussed. A design example is presented. >

A typical hydrogen refueling station was designed based on DOE targets and existing gasoline filling station operations. The purpose of this design was to determine typical heat loads, how these heat loads will be handled, and approximate equipment sizes. For the station model, two DOE targets that had the most impact on the design were vehicle driving range and refueling time. The target that hydrogen fueled vehicles should have the equivalent driving range as present automobiles, requires 5 kg hydrogen storage. Assuming refueling occurs when the tank is 80% empty yields a refueling quantity of 4 kg. The DOE target for 2010 of a refueling time of 3 minutes was used in this design. There is additional time needed for payment of the fuel, and connecting and disconnecting hoses and grounds. It was assumed that this could be accomplished in 5 minutes. Using 8 minutes for each vehicle refueling gives a maximum hourly refueling rate of 7.5 cars per hour per fueling point.

Functioning of an adaptive automated system of operational management of the locomotive park should be based on an accurate operational forecast of the rail direction train operation. For this purpose it is necessary to create a forecast model of the rail direction train operation, the main task of which is the calculation of the readiness moments of trains’ various categories for departure at the technical stations, as well as the calculation of the readiness moments of locomotives and crews for departure with trains. The forecast model of the rail direction train operation includes block forming input information (forming information about the train, locomotive, crew), the trains’ arrival forecasting module (calculation of the forecast time of trains’ arrival), the modules forecasting work of the locomotives (calculation of the forecast time of locomotives’ readiness) and the crews (calculation of the forecast time of locomotive crews’ readiness) and the station functional model (calculation of the forecast time of trains’ readiness for departure) and the locomotive depot model (calculation of the forecast time of locomotives’ and crews’ readiness for departure with trains). The development of the work plan of the locomotives and crews using adaptive model can be considered as an optimization problem solution of binding locomotives and crews to the trains. As an optimality criterion is most advisable to choose the total operational costs associated with downtime of wagons (wagon-hours), locomotives (locomotive-hours) and locomotive crews (crew-hours) at the technical stations while expecting the departure. The optimal variant of the operational work plan of the locomotive park at the railway direction is determined by the minimum of the operational costs associated with unproductive downtime at the technical stations.

Sump model testing is mainly used to check flow conditions around the intake structure. In present paper, numerical simulation with SST turbulence model for a scaled sump model was carried out with air entrainment and two phases for prediction of locations of vortex generation. The sump model used for the CFD and experimental analysis was scaled down by a ratio of 1:10. The experiment was performed in Korea Maritime and Ocean University (KMOU) and the flow conditions around pump's intake structure were investigated. In this study, uniformity of flow distribution in the pump intake channel was examined to find out the specific causes of vortex occurrence. Furthermore, the effectiveness of an Anti Vortex Device (AVD) to suppress the vortex occurrence in a single intake pump sump model was examined. CFD and experimental analysis carried out with and without AVDs produced very similar results. Without the AVDs, the maximum swirl angle obtained for experimental and CFD analysis were 10.9 and 11.3 degree respectively. Similarly, with AVDs, the maximum swirl angle obtained for experimental and CFD analysis was 2.7 and 0.2 degree respectively. So, with reference to the ANSI/HI 98 standard that permits a maximum swirl angle of 5 degree, the use of AVDs in experimental and CFD analysis produced very desirable results which is well within the limit.

Concerns over global warming and high oil prices are expected to lead to a continuous increase in electricity generated by distributed renewable energy sources and small-scale embedded generators (SSEGs). This increase in SSEG will pose numerous technical challenges for distribution network operators. The small-scale energy zone (SSEZ) concept seeks to overcome these challenges using appropriate coordinated control. An SSEZ is defined as a section of low voltage network with a high penetration of SSEGs, controllable loads and energy storage units. This paper puts forward the concept of the virtual power station (VPS), consisting of a number of aggregated SSEZs, which has the potential to offer significant improvements in the commercial value and environmental impact of the installed SSEGs by enabling provision of ancillary services. In order to evaluate the effectiveness of this concept, a dynamic power system model of a VPS has been developed.

The object of study in this paper is a Brownian model of a multiclass service station. Such Brownian models arise as heavy traffic limits of conventional queueing models in which several different types or classes of customers are processed through a common service facility. Assuming that the Brownian service station is initialized with its stationary distribution, four different model characteristics are shown to be equivalent, and the station is said to be quasireversible if these equivalent conditions pertain. Three of the four conditions characterize the vector departure process from the Brownian service station, and our definition of quasireversibility parallels that proposed by F. P. Kelly for conventional queueing models. The last of our four conditions is expressed directly in terms of primitive model parameters, so one may easily determine from basic data whether or not a Brownian station model is quasireversible. Rather than characterizing the complete vector of departure processes from a Brownian service station, we prove a more general theorem expressed in terms of arbitrary linear combinations of the departure processes; this yields a generalized notion of quasireversibility that will play an important role in future work. To be more specific, in a future paper on multiclass Brownian network models, it will be shown that there is an intimate relationship between product form stationary distributions and the generalized notion of quasireversibility developed here.

Archived hourly output from the National Meteorological Center (NMC) prediction models has provided the basis for advanced graphic diagnostic and forecast tools. The high-frequency data are available on a regional selected station network. Each point in the network consists of the basic state variables at each sigma layer and a variety of surface quantities. Five graphics products have been developed at NMC to display the hourly forecast data. They are thermo-dynamic diagrams, standard format meteograms, extended format meteograms, station model plots, and contoured analyses. Graphics workstation animation capabilities enhance the products’ value. Dissemination of a portion of the raw data by the Automation of Field Operations and Services (AFOS) is underway.

The major functions, inputs, and outputs of the seven computer models developed during the Automated Guideway Transit (AGT) System Operations Studies (SOS) project are described. The models were designed to provide tools to enable the transportation community to analyze the operation of AGT systems in the complete spectrum of deployments. Three analytic models are described: the feeder system model, which determines the cost and service characteristics of the non-AGT components of the door-to-door trip; the system cost model, which calculates annual and life cycle costs and environmental impacts; and the system availability model, which calculates the impact of failures and recovery times on passenger and vehicle delays in the network. Four simulation models are described: the discrete event simulation model, which models individual trips and vehicles on AGT networks for a wide range of management algorithms, service policies, and network configurations; the system planning model, which models vehicle and passenger flows on AGT networks; the detailed station model, which models individual vehicle and passenger movement in a station; and the detailed operational control model, which is a time step simulation that models individual or strings of vehicles on links, merges, or intersections.