Optimal Scheduling of Multiple Rail Cranes in Rail Stations with Interference Crane Areas

In this paper,we consider a multi-crane scheduling problem in rail stations because their operations directly influence the throughput of the rail stations.In particular,the job is not only assigned to cranes but also the job sequencing is implemented for each crane to minimize the makespan of cranes.A dual cycle of cranes is used to minimize the number of working cycles of cranes.The rail crane scheduling problems in this study are based on the movement of containers.We consider not only the gantry moves,but also the trolley moves as well as the rehandle cases are also included.A mathematical model of multi-crane scheduling is developed.The traditional and parallel simulated annealing(SA)are adapted to determine the optimal scheduling solutions.Numerical examples are conducted to evaluate the applicability of the proposed algorithms.Verification of the proposed parallel SA is done by comparing it to existing previous works.Results of numerical computation highlighted that the parallel SA algorithm outperformed the SA and gave better solutions than other considered algorithms.

Strategic Placement of Charging Stations for Enhanced Electric Vehicle Adoption in San Diego, California

California mandated that 100% of vehicles sold must be electric by 2035. As electric vehicles (EVs) reach a higher penetration of the car sector, cities will need to provide publicly accessible charging stations to meet the charging demand of people who do not have access to a private charging spot like a personal garage. We have chosen to limit our scope to San Diego County due to its non-trivial size, well-defined shape, and dependence on personal vehicles;this project models 100% of current vehicles as electric, roughly 2.5 million. By planning for the future, our model becomes more useful as well as more equitable. We anticipate that our model will find locations that can service multiple population centers, while also maximizing distance to other stations. Sensitivity analysis and testing of our algorithms are conducted for Coronado Island, an island with 24,697 residents. Our formulation is then scaled to set the parameters for the whole county.

Estimation of Daily Global Solar Radiation with Different Sunshine-Based Models for Some Burundian Stations

Sunshine duration (S) based empirical equations have been employed in this study to estimate the daily global solar radiation on a horizontal surface (G) for six meteorological stations in Burundi. Those equations include the Ångström-Prescott linear model and four amongst its derivatives, i.e. logarithmic, exponential, power and quadratic functions. Monthly mean values of daily global solar radiation and sunshine duration data for a period of 20 to 23 years, from the Geographical Institute of Burundi (IGEBU), have been used. For any of the six stations, ten single or double linear regressions have been developed from the above-said five functions, to relate in terms of monthly mean values, the daily clearness index () to each of the next two kinds of relative sunshine duration (RSD): and . In those ratios, G0, S0 and stand for the extraterrestrial daily solar radiation on a horizontal surface, the day length and the modified day length taking into account the natural site’s horizon, respectively. According to the calculated mean values of the clearness index and the RSD, each station experiences a high number of fairly clear (or partially cloudy) days. Estimated values of the dependent variable (y) in each developed linear regression, have been compared to measured values in terms of the coefficients of correlation (R) and of determination (R2), the mean bias error (MBE), the root mean square error (RMSE) and the t-statistics. Mean values of these statistical indicators have been used to rank, according to decreasing performance level, firstly the ten developed equations per station on account of the overall six stations, secondly the six stations on account of the overall ten equations. Nevertheless, the obtained values of those indicators lay in the next ranges for all the developed sixty equations:;;;, with . These results lead to assert that any of the sixty developed linear regressions (and thus equations in terms of and ), fits very adequately measured data, and should be used to estimate monthly average daily global solar radiation with sunshine duration for the relevant station. It is also found that using as RSD, is slightly more advantageous than using for estimating the monthly average daily clearness index, . Moreover, values of statistical indicators of this study match adequately data from other works on the same kinds of empirical equations.

Research on Short-Term Load Forecasting of Distribution Stations Based on the Clustering Improvement Fuzzy Time Series Algorithm

An improved fuzzy time series algorithmbased on clustering is designed in this paper.The algorithm is successfully applied to short-term load forecasting in the distribution stations.Firstly,the K-means clustering method is used to cluster the data,and the midpoint of two adjacent clustering centers is taken as the dividing point of domain division.On this basis,the data is fuzzed to form a fuzzy time series.Secondly,a high-order fuzzy relation with multiple antecedents is established according to the main measurement indexes of power load,which is used to predict the short-term trend change of load in the distribution stations.Matlab/Simulink simulation results show that the load forecasting errors of the typical fuzzy time series on the time scale of one day and one week are[−50,20]and[−50,30],while the load forecasting errors of the improved fuzzy time series on the time scale of one day and one week are[−20,15]and[−20,25].It shows that the fuzzy time series algorithm improved by clustering improves the prediction accuracy and can effectively predict the short-term load trend of distribution stations.

Energy Management of Networked Smart Railway Stations Considering Regenerative Braking, Energy Storage System, and Photovoltaic Units

The networking of microgrids has received significant attention in the form of a smart grid.In this paper,a set of smart railway stations,which is assumed as microgrids,is connected together.It has been tried to manage the energy exchanged between the networked microgrids to reduce received energy from the utility grid.Also,the operational costs of stations under various conditions decrease by applying the proposed method.The smart railway stations are studied in the presence of photovoltaic(PV)units,energy storage systems(ESSs),and regenerative braking strategies.Studying regenerative braking is one of the essential contributions.Moreover,the stochastic behaviors of the ESS’s initial state of energy and the uncertainty of PV power generation are taken into account through a scenario-based method.The networked microgrid scheme of railway stations(based on coordinated operation and scheduling)and independent operation of railway stations are studied.The proposed method is applied to realistic case studies,including three stations of Line 3 of Tehran Urban and Suburban Railway Operation Company(TUSROC).The rolling stock is simulated in the MATLAB environment.Thus,the coordinated operation of networked microgrids and independent operation of railway stations are optimized in the GAMS environment utilizing mixed-integer linear programming(MILP).

Quantum Atmospheric Biophysics: A Comparison of Four Weather Stations in India on Average Monthly Temperatures Since 1892 and Forecasts to 2150

The identification method revealed asymmetric wavelets of dynamics, as fractal quanta of the behavior of the surface air layer at a height of 2 m, according to the average monthly temperature at four weather stations in India (Srinagar, Jolhpur, New Delhi and Guvahati). For Srinagar station, the maximum for all years is observed in July, for Jolhpur and New Delhi stations it shifts to June, and for Guvahati it shifts to August. With a high correlation coefficient of 0.9659, 0.8640 and 0.8687, a three-factor model of the form was obtained. The altitude, longitude and latitude of the station are given sequentially. The hottest month for Srinagar over a period of 130 years is in July. At the same time, the temperature increased from 23.4 °C to 24.2 °C (by 3.31%). A noticeable decrease in the intensity of heat flows in June occurred at Jolhpur (over 125 years, a decrease from 36.2 °C to 33.3 °C, or by 8.71%) and New Delhi (over 90 years, a decrease from 35.1 °C to 32.4 °C, or by 7.69%). For almost 120 years, Guvahati has experienced complex climate changes: In 1902, the hottest month was July, but in 2021 it has shifted to August. The increase in temperature at various stations is considered. At Srinagar station in 2021, compared to 1892, temperatures increased in June, September and October. Guvahati has a 120-year increase in December, January, March and April. Temperatures have risen in February, March and April at Jolhpur in 125 years, but have risen in February and March at New Delhi Station in 90 years. Despite the presence of tropical evergreen forests, the area around Guvahati Station is expected to experience strong warming.

Functional Characteristics of Beijing Subway Stations Based on POI Data:Taking Beijing Metro Line 6 as An Example

Urban subway station is a key node related to urban social,political,economic and cultural activities.There are some differences in the location,function orientation,land use and flow characteristics of different types of stations in the city.This paper mainly used Tyson’s edge,kernel density analysis,chart analysis and other methods to classify the functional types of 412,393 POI data of 26 stations along Metro he results showed that the spatial distribution of Beijing Metro Line 6 was mainly divided into 3 categories,subway stations were divided into 4 categories.Among them,type A sites were divided into composite and single types,and the distribution characteristics of the 6 types of sites were quite different.Based on the qualitative and quantitative analysis of POI point data,this method can quickly classify and analyze the characteristics of stations along Line 6 in Beijing,which also has theoretical and practical value for the planning of urban subway lines.

Space physics and astronomy research from Chinese polar stations: current and future directions

Space weather has a remarkable effect on modern human activities,e.g.,communication,navigation,space exploration etc.Space physics study from polar stations is as an important part of the entire solar-terrestrial space,and conducts quantitative research from the perspective of overall space plasma behavior.One of the most important issues is to identify the dominant processes that transfer plasma and momentum from the solar wind to Earth’s magnetosphere.Thus,it is necessary to carry out research for combination the observations from polar ground stations and spacecraft observations in the space.Observations at polar regions can be as a window to the space for satellite traffic controls.The operation of the observation chain―Zhongshan-Taishan-Kunlun Station could monitor polar space debris in a large area with high temporal and spatial resolution.Also,night-time measurements of astronomical seeing at Dome A in Antarctica make it less challenging to locate a telescope above it,thereby giving greater access to the free atmosphere because of a thinner boundary layer.

A practical framework for performance-based reliability analysis of subway stations based on a faultestructure combined system

It is necessary to pay particular attention to the uncertainties that exist in an engineering problem to reduce the risk of seismic damage of infrastructures against natural hazards.Moreover,certain structural performance levels should be satisfied during strong earthquakes.However,these performance levels have been only well described for aboveground structures.This study investigates the main uncertainties involved in the performance-based seismic analysis of a multi-story subway station.More than 100 pulse-like and no pulse-like ground motions have been selected.In this regard,an effective framework is presented,based on a set of nonlinear static and dynamic analyses performed by OpenSees code.The probabilistic seismic demand models for computing the free-field shear strain of soil and racking ratio of structure are proposed.These models result in less variability compared with existing relations,and make it possible to evaluate a wider range of uncertainties through reliability analysis in Rtx software using the Monte Carlo sampling method.This work is performed for three different structural performance levels(denoted as PL1ePL3).It is demonstrated that the error terms related to the magnitude and location of earthquake excitations and also the corresponding attenuation relationships have been the most important parameters.Therefore,using a faultestructure model would be inevitable for the reliability analysis of subway stations.It is found that the higher performance level(i.e.PL3)has more sensitivity to random variables than the others.In this condition,the pulse-like ground motions have a major contribution to the vulnerability of subway stations.

Prototyping low-cost automatic weather stations for natural disaster monitoring

Weather events put human lives at risk mostly when people might occupy areas susceptible to natural disasters.Deploying Professional Weather Stations(PWS)in vulnerable areas is key for monitoring weather with reliable measurements.However,such professional instrumentation is notably expensive while remote sensing from a number of stations is paramount.This imposes challenges on the large-scale weather station deployment for broad monitoring from large observation networks such as in Cemaden—The Brazilian National Center for Monitoring and Early Warning of Natural Disasters.In this context,in this paper,we propose a Low-Cost Automatic Weather Station(LCAWS)system developed from Commercial Off-The-Shelf(COTS)and open-source Internet of Things(IoT)technologies,which provides measurements as reliable as a reference PWS for natural disaster monitoring.When being automatic,LCAWS is a stand-alone photovoltaic system connected wirelessly to the Internet in order to provide real-time reliable end-to-end weather measurements.To achieve data reliability,we propose an intelligent sensor calibration method to correct measures.From a 30-day uninterrupted observation with sampling in minute resolution,we show that the calibrated LCAWS sensors have no statistically significant differences from the PWS measurements.As such,LCAWS has opened opportunities for reducing maintenance costs in Cemaden's observational network.

Optimal Configuration Method for the Installed Capacity of the Solar-Thermal Power Stations

Because of the randomness of wind power and photovoltaic(PV)output of new energy bases,the problem of peak regulation capability and voltage stability of ultra-high voltage direct current(UHVDC)transmission lines,we proposed an optimum allocation method of installed capacity of the solar-thermal power station based on chance constrained programming in this work.Firstly,we established the uncertainty model of wind power and PV based on the chance constrained planning theory.Then we used the K-medoids clusteringmethod to cluster the scenarios considering the actual operation scenarios throughout the year.Secondly,we established the optimal configuration model based on the objective function of the strongest transient voltage stability and the lowest overall cost of operation.Finally,by quantitative analysis of actual wind power and photovoltaic new energy base,this work verified the feasibility of the proposed method.As a result of the simulations,we found that using the optimal configuration method of solar-thermal power stations could ensure an accurate allocation of installed capacity.When the installed capacity of the solar-thermal power station is 1×106 kW,the transient voltage recovery index(TVRI)is 0.359,which has a strong voltage support capacity for the system.Based on the results of this work,the optimal configuration of the installed capacity of the solar-thermal power plant can improve peak shaving performance,transient voltage support capability,and new energy consumption while satisfying the Direct Current(DC)outgoing transmission premise.

Analysis and Treatment of Faults in the Operation of Rainfall Sensors in Automatic Weather Stations

Based on the structure and working principle of rain sensors in new automatic weather stations,according to the abnormal precipitation records found in the observation business,the possible faults of rain sensors were analyzed,and treatment methods were discussed. Daily maintenance and management measures were put forward to ensure the normal operation of rain sensors and improve the quality of surface meteorological observation business.

Passengers gathering-scattering analysis at the corners of subway stations

During both daily operation and emergency evacuation,the corners of walking facilities in subway stations play an important role in efficient circulation.However,the effectiveness of the corner is difficult to assess.In this paper,a method of passenger gathering and scattering analysis based on queueing models was proposed to investigate the corner performance in subway stations.Firstly,we constructed a set of state spaces of passenger flow according to passenger density and proposed the state transition model of passenger flow.Moreover,the model of passenger flow blocking and unblocking probability were also presented.Then,to illustrate the validity of the method and model,several passenger gathering-scattering scenarios and were simulated to verify the influence of passenger distribution and facility width on passenger walking,and the blocking probability,throughput,and expected time were also analyzed under various widths of the target corridor and arrival rates.Results showed that the proposed model can reproduce the trend of walking parameters changing and the self-organizing phenomenon of'faster is lower'.With the increase of arrival rates of passengers,walking speeds of passengers decrease and the expected walking time is prolonged,and the blocking probability sharply increased when the arrival rate exceeded 7 peds/s.In addition,with change of width of the target facility,efficiency of capacity of walking circulation facility fluctuated.With the width of the target corridor enlarged by 10%,the steady state of passenger flow was less crowded.Therefore,corridor width is critical to the circulation efficiency of passengers in subway stations.The conclusions will help to develop reasonable passenger flow control plans to ease the jam and keep passengers walking safely.

Service Functions of Private Community Health Stations in China: A Comparison Analysis with Government-sponsored Community Health Stations

In China, with the restructuring of health care system moving forward, private community health facilities have been playing a complementary but increasingly important role in providing public health and basic medical care services in urban areas. However, only limited evidence is available con-cerning the service functions of private community health facilities in China. The aim of this study was to explore the functions of private community health stations (PCHSs) to provide evidence-based rec-ommendations for policy-making and practice in the development of urban community health services systems. A total of 818 PCHSs and 4320 government-sponsored community health stations (GCHSs) located in 28 cities of China were investigated in 2008. The percentages of stations that provided health services and the annual workload per community health worker (CHW) were compared between the two types of institutions. The results showed that the percentages of PCHSs providing public health services were significantly higher than those of GCHSs (P<0.05); but no significant differences were found in the percentages of basic medical services providing between PCHSs and GCHSs (P>0.05). The annual workloads of all the public health services and basic medical services per CHW in PCHSs were lighter than those in GCHSs (P<0.05), except for resident health records establishment and health education materials distribution (P>0.05). At present, the GCHSs are still the mainstream in urban China, which will last for a long period in future. However, our findings showed that the annual workloads of CHWs in PCHSs were no heavier than those in GCHSs, and the PCHSs were willing to provide public health services. In view of current inadequacy of health resources in China, it is feasible to further develop PCHSs under the guidance of the government, given that PCHSs can perform the basic functions of community health services, which is useful for the formation of public-private partnerships (PPP) and the improvement of community health services.

Environmental monitoring and fuzzy synthetic evaluation of municipal solid waste transfer stations in Beijing in 2001-2006

Transfer station(TS)is an integral part of present-day municipal solid waste(MSW)management systems.To provide information for the incorporation of waste facilities within the current integrated waste management system,the authors measured the existing environmental quality at five MSW TSs.Discharged wastewater,air,and noise were monitored and assayed at the five TSs in Beijing in 2001-2006 during rainy seasons(RSs)and dry seasons(DSs).Except Ammonia(NH_3)and hydrogen sulfide(H_2S),the analytical results of...

Probe Selection for Over-the-Air Test in 5G Base Stations with Massive Multiple-Input Multiple-Output

In 5G systems, massive multiple-input multiple-output (MIMO) has been adopted in base stations (BSs) to improve spectral efficiency and coverage. The traditional conductive performance test techniques are challenging due to the unaffordable cost and high complexity when testing a large number of antennas. To solve this problem, the over-the-air (OTA) test has been presented, in which probe selection is the key to reduce the number of channel emulators and probes. In this paper, a novel artificial bee colony (ABC) algorithm is introduced to enhance the efficiency and accuracy of probe selection procedure. A sectoring- based multi-probe anechoic chamber (MPAC) is built to evaluate the throughput performance of massive MIMO equipped in 5G BS. In addition, link level simulation is carried out to evaluate the proposal’s performance gain under the commercial network assumptions, where the average throughput of three velocity is given with different SNR region. The results suggest that OTA chamber and multi-probe wall are available not only for 5G BSs, but also for user equipments (UEs) with end-to-end communication.

Elastic period of vibration calculated experimentally in buildings hosting permanent GPS stations

During the earthquake in Emilia（Italy） of 2012,ca.30 permanent GPS stations were in operation within a radius of about 100 km from the epicenter,each equipped with an antenna rigidly fixed to the host building and sampling the GPS signal at a high rate（〉 1 Hz）.From the recording of the GPS measurements,the instantaneous displacements s（t） in the NorthSouth and East-West directions of the phase centers of the single GPS antennas at each permanent station during the most important seismic sequences were calculated in kinematic mode.Subsequently,for each of the two displacements considered as two distinct external forces,the elastic response spectra of the building were determined and from them the two periods of vibration T along two orthogonal directions coinciding with the walls of the building were extracted.The experimentally obtained periods of vibration were compared with those inferable from the technical literature.In this way,a sufficiently large sample was obtained per building type,geometry（square,rectangular,regular or irregular planimetry）,height（from a minimum of 4 to a maximum of 20 m） and materials（masonry,reinforced concrete,etc.）.From the computational point of view,the study confirmed that GPS is an emerging tool for monitoring dynamic displacements and the experimentally estimated value of T is always lower than the one estimated with the formulae reported in the literature.The limitations of the study lie in the impossibility to choose a priori the geometry and/or structural type of the building hosting the GPS station.

Diurnal Variation of Southwest Monsoon Rainfall at Indian Stations

The paper presents the patterns of rainfall behavior brought out by the diagrams depicting the diurnal variation of SW monsoon rainfall at selected indian stations. The stations in different geographical locations are found to exhibit different patterns of diurnal variation of rainfall. In general, coastal and island stations show enhanced rainfall from midnight to morning hours and below average rainfall during day time. Many inland stations show rainfall maximum towards afternoon/evening hours. Some hill stations show the same behavior as inland stations. However, at the heavy rainfall station of Cherrapunjee, the rainfall behavior is similar to that at the coastal stations. Possible physical mechanisms responsible for the diurnal variation of rainfall at stations under different categories, are briefly discussed. Harmonic analysis of hourly SW monsoon rainfall data of 33 stations show that for 19 stations, the first harmonic accounts for more than 50% of the variance of the rainfall series. These consist of (i) inland stations for which the maximum of the first harmonic is reached between 16 hours IST and midnight, and (n) coastal/island stations for which the maximum is seen between 03 and 07 hours IST. At most of the coastal and island stations, the first harmonic alone accounts for 75% orb more of the variance. For the heavy rainfall station of Cherrapunjee, the first harmonic which attains its maximum at 3.8 hours IST (-4.4 hours LT), is able to account for 96% of the variance of the rainfall series. It is hoped that the information contained in this paper about the pattern of diurnal modulation of monsoon rainfall may serve as background material to monsoon precipitation climatology.

Urban Spatial Risk Assessment of Fire from Fueling Stations on Buildings Case Study: Lubaga Division, Kampala City, Uganda

The discovery of oil and gas in Uganda has attracted many investors, leading to increase in fuel/gas distributing companies and fueling stations creating rapid demand for land to locate the stations compared to available open urban land. Because of the explosive and combustion characteristics of fuel stored and dispensed at stations, several studies have been conducted on different fires at fueling stations such as static fire, jet fire, vapor cloud explosions, open fires, etc. but there was need to assess spatially the risk of fire from stations, its consequences and sovereignty on buildings surrounding them. This was done basing on seven parameters—proximity of buildings to stations, building materials, distance between buildings, wind speed, temperature, slope and vegetation. Analytical hierarchy process and pairwise comparison were used to weight the parameters based on their relative importance. Weighted sum tool was applied to generate the fire risk maps for the quarters—December to February, March to May, June to August, and September to November from 2008 to 2013. The parameters were overlaid with the buildings in each risk zone for all the four quarters and their influences determined. The highest contributors were proximity of the buildings to stations, building materials and separation between buildings. Most of the affected buildings were made of rusted corrugated iron sheets and wood;the separation distance from one building to another ranged from 0 - 4 m. Most of buildings located within 100 m from stations were at moderate risk level and within 50 m were at highest risk level. The period of December to February and June to August had the highest risk. The findings can be used to guide planners and policy makers on building location vs. material vs. separation. It can also guide developers on where, when and how to carry out their developments.

Local vs. cross station simulation of suspended sediment load in successive hydrometric stations: heuristic modeling approach

The present paper aims at modeling suspended sediment load(SSL) using heuristic data driven methodologies, e.g. Gene Expression Programming(GEP) and Support Vector Machine(SVM) in three successive hydrometric stations of Housatonic River in U.S. The simulations were carried out through local and cross-station data management scenarios to investigate the interrelations between the SSL values of upstream/downstream stations. The available scenarios were applied to predict SSL values using GEP to obtain the best models. Then, the best models were predicted by SVM approach and the obtained results were compared with those of GEP. The comparison of the results revealed that the SVM technique is more capable than the GEP for modeling the SSL through the both local and cross-station data management strategies. Besides, local application seems to be better than cross-station application for modeling SSL. Nevertheless, the cross-station application demonstrated to be a valid methodology for simulating SSL, which would be of interest for the stations with lack of observational data. Also, the prediction capability of conventional Sediment Rating Curve(SRC) method was compared with those of GEPand SVM techniques. The obtained results revealed the superiority of GEP and SVM-based models over the traditional SRC technique in the studied stations.