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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.

In the last couple of decades, there has been a growing concern in what effects fossil fuels are having on the environment, resulting in governments and governing organizations issuing stringent emission standards in an effort to curve their environmental damage. To meet these new standards, the transportation industry has been conducting research into alternative fuels, such as hydrogen, but one critical problem utilizing hydrogen is that there is almost no infrastructure. A network of hydrogen refueling stations similar to modern gasoline stations will be required to be constructed to meet future demand. The hydrogen refueling station model was created to aid in designing hydrogen facilities, thus accelerating their development while reducing design cost. A model was created using Simulink consisting of an electrolyzer that generates hydrogen, a compressor, numerous storage tanks, a dispensing unit that transfers hydrogen, and a vehicle component that consumes hydrogen fuel. The model was validated using data from existing hydrogen refueling stations, and the data obtained from testing the previous version of the hydrogen refueling station model to determine model accuracy and if the model has improved. The model has demonstrated that it can produce reasonable results for a station's performance and has improved compared to the previous version.

The future success of fuel cell electric vehicles requires a corresponding infrastructure. In this study, two different refueling station concepts for fuel cell passenger cars with 70 MPa technology were evaluated energetically. In the first option, the input of the refueling station is gaseous hydrogen which is compressed to final pressure, remaining in gaseous state. In the second option, the input is liquid hydrogen which is cryo-compressed directly from the liquid phase to the target pressure. In the first case, the target temperature of −33 °C to −40 °C [1] is achieved by cooling down. In the second option, gaseous deep-cold hydrogen coming from the pump is heated up to target temperature. A dynamic simulation model considering real gas behavior to evaluate both types of fueling stations from an energetic perspective was created. The dynamic model allows the simulation of boil-off losses (liquid stations) and standby energy losses caused by the precooling system (gaseous station) dependent on fueling profiles. The functionality of the model was demonstrated with a sequence of three refueling processes within a short time period (high station utilization). The liquid station consumed 0.37 kWh/kg compared to 2.43 kWh/kg of the gaseous station. Rough estimations indicated that the energy consumption of the entire pathway is higher for liquid hydrogen. The analysis showed the high influence of the high-pressure storage system design on the energy consumption of the station. For future research work the refueling station model can be applied to analyze the energy consumption dependent on factors like utilization, component sizing and ambient temperature.

In order to solve the problem that the subway attracts less passenger flow, there are too many overlapping lines between the bus and the subway, resulting in traffic congestion of other conventional bus lines along the subway. For this reason, we take Xiamen as the sample point, and consider the number of subway stations and the length of subway bus configuration. The mathematical model of matching bus line density and traffic line length is referred. Based on the accessibility analysis, a new bus connecting station model with more than five stations on the same line is designed. We propose two models for the alignment adjustment of the number of common stations of subway and public transport. It is shown that the average connecting time from bus to subway is reduced by 15.58 minutes, and the passenger flow attracted by subway is increased by 2.15%-19.99%, compared with the unadjusted road network layout.

With the development and popularization of electric vehicles, the charging demand for large-scale electric vehicles is an increasing challenge for the electric grid. Based on the existing electric vehicle charging data, this paper establishes a model for the calculation of electric vehicle charging demand and estimates the influence of vehicle charging on the electric grid. First, we established an electric vehicle model and expanded it into a charging station model. The station model is used to calculate the charging power of a single charging station within 24 hours and the charging demand ratio of electric vehicles. Since that the vehicles equipped with charging piles do not strongly depend on the charging station, we use the SVM algorithm to recognize these vehicles and exclude them from the data to increase the estimation accuracy of station-based charging demand. The K-means algorithm is used to estimate the coordinates of the charging stations. We finally calculate the impact of charging peaks caused by increasing the number of electric vehicles and charging power on the public grid.

Computing triangular meshes with constrained edges requires both advanced mathematics and thoughtful logic of the implemented algorithm. Our approach to this is modifying an already created triangulation (e.g., Delaunay triangulation), which can be constructed by a simple algorithm. By swapping edges between triangles and splitting them in needed scenarios, we achieve a mathematically simple algorithm, that supports the construction of wanted edges. This algorithm has been tested in a scenario where it was used to automatically generate terrain based on an infrastructure of a railway station model.

Under the general development trend of the power Internet of Things, multi-station integration with high computing efficiency and local load consumption will become the main form of the future energy system. However, with the large number of renewable energy stations and charging stations connected into multi-station integration systems, the uncertainties and volatilities of new energy output and charging time of charging stations adversely affect the economic, efficient, and stable operation of the system. To achieve the economic, efficient, and stable operation of multi-station integration energy system, this paper establishes an integration station model with five stations in one: substation, charging station, energy storage station, data center station and renewable energy station. This paper adopts Monte Carlo simulation method to obtain renewable energy station output scenarios and K-means algorithm to perform scenario reduction. Probability density function is used to describe the uncertainty of random charging at charging station. Considering time-of-use price, a multi-objective optimization model is established with respect to costs and risks. NSGA-II and multi-attribute decision method are combined to find the optimal solution. The simulation results show that the proposed method significantly reduces the total operating cost and risk of the system, indicating that the proposed model and method are feasible.

With the development of smart grid, the power data resources increase rapidly, and the potential value of data is gradually explored. This paper based on clustering algorithms, clustering massive amounts of low-voltage station users' electricity data, and analysing each user group by clustered electricity consumption behaviour. Classify the low-voltage station according to the electricity consumption behaviour and extract the characteristic parameters of the low-voltage station. Then comprehensively considering the users' electricity consumption behaviour, and characteristic parameters of the typical low-voltage station, the support vector regression (SVR) is used to construct the typical low-voltage station model. The improved particle swarm optimization is used to optimize the SVR parameters. Finally, different low-voltage stations in Tianjin are selected to verify the effectiveness of the proposed model.

To improve the running efficiency of automated warehouse, numerous enter prices adopts the warehouse layout model which uses double-stackers on monorail with two I/O station. For the problem of double-stackers scheduling, the anti-collision principle is taken as the basic principle and the required operating time of two stackers as the evaluation criteria to present a new scheduling model based on mixed command sequence by analyzing the operating modes of double-stackers in different tasks. On this basis, improved Chemical Reaction Optimization (ICRO) is used to optimize the scheduling path of double-stackers. According to the analysis of simulation, the proposed stacker scheduling model could adapt to the warehouse operating condition and avoid the collision. Meanwhile the optimization algorithm could improve the storage efficiency for double-stackers on monorail with two I/O station model.

The integration of Distributed Generation (DG) can affect the distribution network in many aspects, such as power flow, short-circuit current, distribution grid protection, etc. In this paper the influence of a MW photovoltaic (PV) station to a distribution network is mainly studied. The mathematical model and equivalent circuit of a photovoltaic cell are presented in the first part of this paper. Then a 1.6MW PV station model is established in the software of DIgSILENT PowerFactory. This model is not a precise one, but it is more convenient for the research of PV station’s affection to a power grid. In the last part of this paper, various simulations are performed to investigate the influence of the PV station to a distribution network. The result shows that the model is capable for our investigation and the influence varies with different operating modes of the PV station.

The paper outlines various factors affecting the solar module efficiency. The authors consider the dependence of the solar module operation on insolation and temperature. The temperature increases the degradation of the solar modules during the operation time, determines technical characteristics and the efficiency of the modules, which decreases as the temperature increases. Using the Matlab Simulink program the authors have developed a model of an autonomous solar power plant. The model considers the relationship between the heating temperature of solar modules and their efficiency during operation. The model provides an option of selecting solar module makes, the number of modules and their connection circuits. Depending on a solar module make the corresponding current and voltage parameters are automatically set. When the model operates, the batteries connected to the solar modules are charged and the inverter converts DC into AC.

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.

Parameter extraction of solar photovoltaic (PV) models is a typical complex nonlinear multivariable strongly coupled optimization problem. In this paper, an improved whale optimization algorithm (WOA), referred to as IWOA, is proposed to accurately extract the parameters of different PV models. The original WOA has good local exploitation ability, but it is likely to stagnate and suffer from premature convergence when dealing with complex multimodal problems. To conquer this concerning shortcoming, IWOA develops two prey searching strategies to effectively balance the local exploitation and global exploration, and thereby enhance the performance of WOA. Three benchmark test PV models including single diode, double diode and PV module models, and two practical PV power station models with more modules in the Guizhou Power Grid of China are employed to verify the performance of IWOA. The experimental and comparison results comprehensively demonstrate that IWOA is significantly better than the original WOA and three advanced variants of WOA, and is also highly competitive with the reported results of some recently-developed parameter extraction methods.

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.

The atrium-style station is one of the favourite choices in underground railway systems, as it can provide a larger and clearer space for passengers and commercial clients at the hall level of the station. With such style, as hall slabs are replaced with flat-beams, the station's capabilities to withstand lateral action like seismic action become one of the main concerns. Shaking table tests were conducted to investigate the dynamic response of soil-structure interaction of atrium-style station model under harmonic excitations covering the full frequency range, with comparison to free-field tests. The experimental results confirm that the influence of the structure on the dynamic response of the ground surface begins when the frequency of input motions is greater than 10 Hz. The predominant frequencies of the ground corresponding to the second and third modes both show an increase of 10% from the FF model to the SS model due to the presence of an atrium-style metro station. For atrium-style station: (i) the discontinuous structural elements such as beams and columns are more severely strained than the continuous ones like slabs and side walls, (ii) the peak dynamic soil normal stresses along the side wall follow an approximate L-shaped distribution and the maximum stress occurs at the side wall bottom, and (iii) the spectral characteristics of both dynamic structural strain and dynamic soil normal stress reflect the amplification function of the ground.

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.

There is a severe contradiction between the heating supply of central heating systems and the utilization of wind power in wind integration areas. Combined heat and power dispatch can alleviate the wind curtailment problem through the utilization of heat storage property of central heating systems. Existing studies mainly focus on the dispatch of heat sources in central heating systems but do not consider the schedule of heat exchange stations. In this paper, a start-stop schedule model of heat exchange stations is established. Combining the quasi-dynamic pipeline thermal model, a combined heat and power dispatch model is addressed. A transformation on the heat exchange station model is proposed to transform non-convex constraints into tractable mixed integer linear constraints. Numerical tests demonstrate the necessity of introducing the schedule of heat exchange stations into combined heat and power dispatch and the economic advantages of the proposed method in reducing wind curtailment.

Previous study had not yet constructed an effective system assisting players in training free kicks. We present a Simulation and Modeling of Station and Shooting Model of Free Kicks. In order to investigate the two opposite aspects of offense and defense, the station model is established after building a football field model. Then through considering the distance from corner of the goal and the speed of the ball, the best way to shoot football is solved by small steps. Finally, we simulate the station and shooting model to verify the accuracy of our model. The results showed that the proposed model is effective in football games.

Nowadays the world demands trains that go with a very high speed. To achieve this, a concept of a railway modeling using software applications is proposed for the purpose of increasing the resilience of railway traffic. Software applications need models that can describe their structure, reaction to internal and external events concerning cooperation and task migration. The behavior of the system which contains these types of trains can be conceived using OETPN (Object Enhanced Time Petri Nets). In this model, the tokens are active or passive objects. The active objects are sub OETPN that are executed by another thread of execution. In this model, the OETPNs are capable of communicating with each other via communication channels, they can send passive and active objects (i.e. task migration). Concurrency, reaction to internal or external events, synchronization and temporal behavior with fix and dynamic delays could be easily modeled using OETPN. A model for the railway system is proposed in this paper, the station, the controller and the software train are modeled using OETPN. The software train is an active object (a task, or an agent) that is moved inside the station model, meanwhile the physical train is moved on the physical infrastructure. The experiments of OETPN models successfully show that they can be used to solve the railway traffic problems due to their capabilities to adapt to the changing environment.

This paper presents a control design for the irrigation station by sprinkling. The proposed method is applied in order to solve the problem of managing water sources and distributions systems. The main contribution is focused primarily on conceiving T-S fuzzy model for the irrigation station. In formalism of the fuzzy-coalescence algorithm, we derive sufficient conditions to determine the model parameters. Meanwhile, additional effort is developed to achieve PI control for the irrigation station model.

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.

Among other flood forecasting tools, fuzzy logic is one of a simple and flexible approach which can be implemented in river basins where adequate hydrologic data is available and not good enough to use in a more sophisticated model. This paper assesses the potential of fuzzy logic approach for real time flood forecasting using the minimum implication function type Mamdani fuzzy inference system by applying the model to the Kelantan River basin in Malaysia. The developed models were tested for forecasting the downstream water levels of Guilemard and Kuala Krai stations using upstream hourly telemetric water levels of Dabong and Tualang stations. The membership functions (MFs) of triangular shapes with several fuzzy rule sets were utilized to check the efficiency of the fuzzy logic approach for the Kelantan River flood forecasting. For the Guilemard station, models of 8, 10 and 15 rules' sets were tested. In the calibration and validation events, the Guilemard station models' achieved MAE, ranges 0.35–0.45 m, N–S coefficient, ranges 0.87 – 0.89 and Coefficient of Determination ranges, R 2 ranges 0.91–0.95. The water level prediction model developed for the Kuala Krai station consisted of 19 rules with triangular shape MFs. It shows the ranges for MAE: 0.26–0.76 m, N–S coefficient: 0.78–0.93 and R 2 : 0.91–0.96 in calibration and validation periods. The efficiencies of the developed models show acceptable levels according to the tested performance indicators implying the potential of establishing a flood forecasting system by using the fuzzy logic approach in the Kelantan River basin, Malaysia.

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...

A new method of upgrading seismic performance for underground structures is proposed in this paper. Both single-story and double-story underground subway stations are studied. Using the famous single-story Daikai Station model, by which the reliability of the numerical model is verified, seismic efficiency of Shear Panel Damper (SPD) in underground structures is proven. Then, in order to design appropriate and efficient SPDs for underground structures, strength ratio, one of the design parameters, is employed to investigate the seismic performance of structures. The recommended optimum range of strength ratio is given. Afterwards, typical double-story three-span stations with different SPDs layout forms are analyzed to figure out the optimal placement of SPDs. And some interesting conclusions are obtained, which may provide a convenient way to design SPDs in multi-story underground structures.

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

High penetration of electric vehicles has brought huge impact on the safe and stable operation of power grid. How to effectively improve the comprehensive utilization rate of electric vehicle charging and discharging has become the most important problem for the grid operation. In this paper, we establish the centralized station model which takes the minimal real power loss as its objective and bring variance optimization function. Using IEEE 30-bus system as simulation system, this paper uses genetic algorithm to find the best solution of the above model. The result shows that reasonable arrangement of charge and discharge plans not only smoothes the load curve, but reduces real power loss.

As a reaserch and development model, IFS is fast and efficient for MIS sysment.At first, we introduced the IFS models (information models, station models and function models) ,and it is proposed that the management information system (MIS) is build base on IFS models data-driven technologies and four tiers soft development technologies. Finally, we described abstract of the station models (user interface) and mechanism about the station models to the user interface.

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.

The purpose of the current research effort is to develop a framework for a better understanding of commuter train users’ access mode and station choice behavior. Typically, access mode and station choice for commuter train users is modeled as a hierarchical choice with access mode being considered as the first choice in the sequence. The current study proposes a latent segmentation based approach to relax the hierarchy. In particular, this innovative approach simultaneously considers two segments of station and access mode choice behavior: Segment 1—station first and access mode second and Segment 2—access mode first and station second. The allocation to the two segments is achieved through a latent segmentation approach that determines the probability of assigning the individual to either of these segments as a function of socio-demographic variables, level of service (LOS) parameters, trip characteristics, land-use and built environment factors, and station characteristics. The proposed latent segment model is estimated using data from an on-board survey conducted by the Agence Metropolitaine de Transport for commuter train users in Montreal region. The model is employed to investigate the role of socio-demographic variables, LOS parameters, trip characteristics, land-use and built environment factors, and station characteristics on commuter train user behavior. The results indicate that as the distance from the station by active forms of transportation increases, individuals are more likely to select a station first. Young persons, females, car owners, and individuals leaving before 7:30 a.m. have an increased propensity to drive to the commuter train station. The station model indicates that travel time has a significant negative impact on station choice, whereas, presence of parking and increased train frequency encourages use of the stations.

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.

According to the independence of the base station, the basic characteristics of the base station are analyzed, and a heat transfer model of communication base station enclosing structure is constructed, and the change of the temperature data in the base station is simulated using computer, and also all program module design flows of computer simulation are provided. Through the comparison between the result of field test on a typical base station and the simulation data, it is learnt that the temperature data simulated in the heat transfer model of the base station enclosing structure is similar to the average temperature within the measured base station.

Robotics played a key role in the creation of the International Space Station during the assembly between 1998 and 2011. It continues to this day, thanks to the Space Station Robotic Manipulator System (SSRMS) that was delivered by STS-100 in April 2001. The apparent ease with which this was achieved was honed during several early Shuttle missions and by pioneering robotic arm operators who had to devise a different way of working several feet or meters away from where the workplace was situated, as pointed out above by Rhea Seddon. The development of the RMS and its operation first on the Shuttle and then aboard the ISS, was one of the unsung success stories of the series.1