Full Load Rate Research Articles

Optimization of smart bus scheduling based on dynamic speed limit of load rate

Aiming at the problem that fixed speed limit and static regular scheduling of single-type bus cannot meet the actual passenger flow demand with uneven distribution of time and space. By designing a dynamic speed limit rule of full load rate, based on the integrated scheduling of multiple types of bus models, taking the total passenger cost and bus scheduling cost as the overall optimization objective, and considering various constraints comprehensively, OBLESGA (Opposition-based learning elite strategy genetic algorithm) was designed to solve the problem, and the data of Beijing 563 route downlink was taken as an example for simulation experiment. The results show that OBLESGA can improve the convergence rate and solution accuracy of GA. At the same time, the optimized scheduling can reduce the cost of passenger congestion by 86.61 percent and the cost of passenger waiting times by 40.65 percent compared to traditional scheduling, while only increasing operating costs by 26.57 percent.

Study on the Operation and Optimization of Holiday Passenger Flow of Shenyang Metro on the Basis of Queuing Theory

By studying the passenger flow data in and out of the station of Shenyang Metro, the changes of holiday and daily passenger flow are obtained. Determine whether and how to optimize the running interval according to the load factor and the average waiting time of passengers, and provide reference for optimizing the running interval. The selection of holiday passenger flow data is explained, the proportion of the average inbound passenger flow is used as the basis for dividing the inbound passenger flow of different lines at the transfer station. The time series stationarity test is carried out and the passenger flow attraction factor of the subway station is given in order to calculate the full load rate. By using the Random number Generator in MATLAB to generate the time interval between incoming passengers, it is checked that the incoming data of subway obeys Poisson distribution, the full-load ratio of subway and the average waiting time of passengers are calculated. During the Spring Festival, Qingming Festival, Labor Day, Dragon Boat Festival and Mid-Autumn Festival, the driving interval is set by weighing the full load rate and the service time. Finally, the method of this paper is summarized and explained, the method proposed in this paper has certain reference value for subway operation optimization.

Assessment of Carbon Emissions at the Logistics and Transportation Stage of Prefabricated Buildings

As regards the carbon emission levels of the logistics stage of prefabricated buildings, this study aims to fill the gap in scientific and unified carbon emission calculation models and standards. Thus, the calculation boundary for carbon emissions was first defined in this study. Secondly, various carbon emission factors related to China’s energy consumption characteristics were summarized. Subsequently, a carbon emission calculation model for the logistics stage was established, based on the carbon emission factor method. Finally, taking a project as an example, the carbon emission level at the transportation stage was calculated using the proposed model. The effect of full-load rates on the carbon emission levels of prefabricated components was also evaluated. The results demonstrate that the full-load rate has a significant effect on carbon emissions during the transportation stage (54.32% reduction in carbon emissions at 100% full load). Therefore, increasing the full-load rate can reduce carbon emissions from transportation, as long as the loading requirements are met.

Deep Reinforcement Learning based dynamic optimization of bus timetable

Bus timetable optimization is a key issue to reduce operational cost of bus company and improve the transit service quality. Existing methods optimize the timetable offline. However, in practice, the short-term passenger flow may change dramatically from time to time. Timetables generated offline cannot be adjusted in real time to handle the changed passenger flow. In this paper, we propose a Deep Reinforcement Learning based bus Timetable dynamic Optimization method (DRL-TO). In DRL-TO, the problem of bus timetable optimization is formulated as a Markov Decision Process (MDP). A Deep Q-Network (DQN) is applied as the agent to decide whether a bus departs at each minute during the service period. Therefore, departure intervals of bus services are determined in real time in accordance with passenger demand. We identify several new and useful state features for the DQN agent, including the load factor, the carrying capacity utilization rate, passengers’ waiting time and the number of stranded passengers. Considering the interests of both the bus company and passengers, a reward function is designed, which includes metrics of full load rate, empty load rate, passengers’ waiting time, and the number of stranded passengers. Experiments demonstrate that, in comparison to the timetable generated by offline optimization approaches and the manual method, DRL-TO can dynamically determine the departure intervals based on the real-time passenger flow, and generate a timetable with less departure time points (i.e., operational cost) and shorter passengers’ waiting time (i.e., higher quality of service).

Study on the optimization of urban emergency supplies distribution paths for epidemic outbreaks

The humanitarian logistics vehicle routing problem (VRP) of urban emergency supplies in response to epidemic outbreaks is studied in this work to address the adverse effects of epidemic outbreaks on human society. Under the premise that the greater the urgency of the demand for various emergency supplies by the hospitals in the city’s jurisdiction, the higher the priority of distribution, the fitness function of the highest vehicle utilization rate and the lowest transportation cost is established. The aim of the research is to construct a multi-objective mathematical model of emergency supplies distribution for large cities in case of an epidemic outbreak. Based on the multi-verse optimization algorithm and the differential evolution algorithm, a hybrid multi-verse optimizer algorithm based on differential evolution (DE-IMOV) is proposed. A simulation experiment is then carried out to verify the model. The calculation results show that the developed algorithm can effectively reduce the distribution cost and improve the full load rate of vehicles on the basis of considering the urgency of emergency supplies demand, which provides a solution for the optimization of heterogeneous vehicle distribution paths for urban emergency supplies in response to epidemic outbreaks.

Managing Peak-Hour Congestion in Urban Rail Transit with the Sub-Train Price Adjustment Strategy

In urban rail transit, adjusting fares to satisfy passenger flow requirements is a new method to relieve urban congestion. A bilevel model is proposed herein to solve the congestion problem for an urban rail line. The upper level of the model determines the discount factor to minimize the total number of passengers exceeding the full-load rate, and the lower level of the model determines the distribution of passengers on the line, in which the cost-minimizing behavior of each passenger is considered using the allocation method based on the probability of selection. To achieve a more realistic model, the range of acceptable train numbers for each passenger is considered. A simulated annealing algorithm is introduced to solve the bilevel model. Based on an example, we obtain the specific fare and passenger flow distribution of each train after fare adjustment. The results show that the objective function is reduced by 17.5%, the congested section is reduced by 9.1% when the full-load rate is 90% of the train loading capacity, and the passenger flow shifts to both ends of the peak period. Finally, relevant parameters are discussed.

Research on Coordinated Passenger Inflow Control for the Urban Rail Transit Network Based on the Station-to-Line Spatial-Temporal Relationship

This study proposes a coordinated inflow control organization for the urban rail transit network to improve train capacity utilization and reduce inbound delay rate, considering existing operational requirements and station-to-line spatial-temporal relationship of passenger flow. The coordinated passenger flow control model is proposed with the objective to maximize the inbound flow rate and the train full load rate. A station-to-line spatial-temporal correlation formula is constructed to characterize the relationship between station inbound passenger volume and section passenger volume. A two-stage approach is employed to solve this passenger flow control problem. The proposed model and solution strategy are evaluated on a well-known Beijing network with 10 operating lines. The refined inflow control scheme is displayed with the accurate inbound volume at each station during each time period. The comparison between the proposed control strategy and the current control strategy shows that the former can effectively improve the service level and capacity utilization.

Baseline testing of a variable-speed water-cooling Chiller according AHRI standard 550/590

A new experimental test facility was designed to test vapor compression chillers of up to 145.9 refrigeration tons (approximately 513 kW). To implement such a large-capacity test facility in a university laboratory research environment, the system design is based on regenerative shell and tube heat exchangers. The capacity load on the chiller can be controlled via a bypass valve that allows a flow change over the internal heat exchangers. In addition to the internal sensors of the chiller, a variety of sensors in the system ensures a detailed recording of data as well as an automation of the test procedure.The test facility is constructed and commissioned to execute the performance according the AHRI Standard 550/590. The chiller has been tested in full load and part load rating conditions to achieve a characteristic performance line of the machine. Recorded data is averaged and evaluated according to the requirements of the AHRI standard. The results of the baseline testing and the data processing are presented in this paper. A detailed analysis of the outcomes allows a comparison with the manufacturer rated efficiency values.Finally, the potential instabilities of the test systems that caused problems during the test runs and their reasons are discussed, as well as possibilities to overcome them. The given ability of the test facility for a rapid change between different load conditions allows the arrangement of test cycles to investigate the performance degradation of the twin-screw chiller over time.

Public Norms in the Operation Scheme of Urban Rail Transit Express Trains: The Case of the Beijing Changping Line

The development of urban rail transit is of great significance to the sustainable development of cities. However, the formulation of public norms of the urban rail transit train operation scheme lacks the corresponding theoretical support, rationality and scientificity. Therefore, based on the research on passenger flow conditions, this paper establishes an optimization model of express train operation and uses a heuristic genetic algorithm to solve it. In addition, this paper takes the Beijing Changping Line as an example to conduct empirical research. Results show that the optimization model established reduces the operation cost of operating enterprises, improves the capacity of urban rail transit, reduces travel time and maintains the full load rate of trains at a more comfortable level. This will improve the attractiveness of urban rail transit and promote benign interaction between operators and passengers. It will also provide a theoretical basis for formulating public norms of transit train operation, make it more scientific and reasonable and promote the development of urban rail transit.

Research on Distribution Path of Single-center Medical Rescue Materials

Reasonably planning the vehicle’s distribution path can effectively improve the distribution efficiency of the distribution center. This article takes the distribution of medical rescue materials as an example. Under the conditions of meeting the needs of hospital and the loading capacity of the vehicle, with the goal of the shortest distribution route, an optimization model is established and the model is solved with the help of MATLAB to obtain an optimized distribution route plan. The two schemes are compared and analyzed before and after the optimization. The results show that the optimized scheme can effectively shorten the distribution path and increase the full load rate of the vehicle.

Research on digital flow control model of urban rail transit under the situation of epidemic prevention and control

Purpose Beijing rail transit can actively control the density of rail transit passenger flow, ensure travel facilities and provide a safe and comfortable riding atmosphere for rail transit passengers during the epidemic. The purpose of this paper is to efficiently monitor the flow of rail passengers, the first method is to regulate the flow of passengers by means of a coordinated connection between the stations of the railway line; the second method is to objectively distribute the inbound traffic quotas between stations to achieve the aim of accurate and reasonable control according to the actual number of people entering the station. Design/methodology/approach This paper analyzes the rules of rail transit passenger flow and updates the passenger flow prediction model in time according to the characteristics of passenger flow during the epidemic to solve the above-mentioned problems. Big data system analysis restores and refines the time and space distribution of the finely expected passenger flow and the train service plan of each route. Get information on the passenger travel chain from arriving, boarding, transferring, getting off and leaving, as well as the full load rate of each train. Findings A series of digital flow control models, based on the time and space composition of passengers on trains with congested sections, has been designed and developed to scientifically calculate the number of passengers entering the station and provide an operational basis for operating companies to accurately control flow. Originality/value This study can analyze the section where the highest full load occurs, the composition of passengers in this section and when and where passengers board the train, based on the measured train full load rate data. Then, this paper combines the full load rate control index to perform reverse deduction to calculate the inbound volume time-sharing indicators of each station and redistribute the time-sharing indicators for each station according to the actual situation of the inbound volume of each line during the epidemic. Finally, form the specified full load rate index digital time-sharing passenger flow control scheme.

Development and application of a life cycle energy consumption and CO2 emissions analysis model for high-speed railway transport in China

China's high-speed railway (HSR) is booming recently, the HSR's performance of energy conservation and carbon reduction has attracted much attention. This study developed a new life cycle model of energy consumption and greenhouse gas (GHG) emissions on China's HSR by life cycle analysis (LCA), covering the stages of infrastructure, HSR train, and operation, based on the TLCAM (Tsinghua-LCA Model). A case of the Beijing–Shanghai HSR has been studied to show that the full life cycle energy consumption and GHG emissions of HSR transportation are 0.4 MJ km−1 per capita and 0.04 kg CO2e km−1 per capita, respectively, which are far less than aviation, gasoline vehicles, diesel vehicles, electric vehicles and public vehicles. With the cleaner power structure and the progress of HSR train technology, the energy consumption and carbon emissions of HSR in 2020 could be reduced by 20% compared to 2015. This study indicates that electricity generation mix structure and full load rate are important factors influencing the life-cycle energy consumption and GHG emissions of HSR transportation. It is recommended to improve the coverage of HSR network, accelerate train upgrades, improve the full load rate of HSR trains, and promote the low-carbon development of electricity supply to strengthen and realize the low-carbon advantage of HSR transport mode in China. HSR transportation can be used to achieve the low carbon transformation of China's transportation sector and improve oil supply safety situation.

Hub location problem with balanced round-trip flows on hub links

This paper addresses the classical single and multiple allocation hub location problems with fully interconnected hubs, in which the balanced round-trip flows on hub links are considered in the strategic decision making process. The use of balanced round-trip flows on hub links is motivated by the need to decrease the empty-trip rate of vehicles and increase the full-load rate of vehicles. Mixed-integer programming models are presented for single and multiple allocation versions of the problems. Numerical experiments with the CAB and AP datasets are performed to analyse the impacts of balanced flows on the network configurations and the utilisation of service resources. Experimental results show that the number of located hubs tends to decrease with a decrease in the allowable unbalanced round-trip degree of the hub link flows. The utilisation rate of transportation resources can be significantly improved with a small increase in the traditional operating cost. Moreover, a better modelling of economies of scale can be achieved when considering balanced flows. [Received: 22 September 2019; Accepted: 15 March 2020]

The Split Delivery Vehicle Routing Problem with Three-Dimensional Loading and Time Windows Constraints

Besides routing and packing plans, synthetically considering the requirements of customers about service time is absolutely necessary. An order split delivery plan can not only better satisfy the service time requirements, but also improve the full-load rate of vehicles. The split delivery vehicle routing problem with three-dimensional loading constraints (3L-SDVRP) combines vehicle routing and three-dimensional loading with additional packing constraints. In the 3L-SDVRP splitting deliveries of customers is basically possible, i.e., a customer can be visited in two or more tours. The vehicle routing problem with three-dimensional loading constraints that are based on the time window and considering split delivery of orders (3L-CVRPTWSDO) and its optimization algorithm are studied in this paper. We established mathematical model of the problem and designed the tabu search algorithm. Based on the examples used in Gendreau et al. (2006), examples was constructed to test our algorithm. The experimental results have expressed that, in the 3L-CVRP problem, the results of split delivery is better than those of non-split delivery, and it is easier to satisfy the time window constraints. The algorithm in this paper generates high quality solutions, it provides a effective method to solve the 3L-CVRPTWSDO problems.

Hub location problem with balanced round-trip flows on hub links

This paper addresses the classical single and multiple allocation hub location problems with fully interconnected hubs, in which the balanced round-trip flows on hub links are considered in the strategic decision making process. The use of balanced round-trip flows on hub links is motivated by the need to decrease the empty-trip rate of vehicles and increase the full-load rate of vehicles. Mixed-integer programming models are presented for single and multiple allocation versions of the problems. Numerical experiments with the CAB and AP datasets are performed to analyse the impacts of balanced flows on the network configurations and the utilisation of service resources. Experimental results show that the number of located hubs tends to decrease with a decrease in the allowable unbalanced round-trip degree of the hub link flows. The utilisation rate of transportation resources can be significantly improved with a small increase in the traditional operating cost. Moreover, a better modelling of economies of scale can be achieved when considering balanced flows. [Received: 22 September 2019; Accepted: 15 March 2020]

Study of operational strategies for a hybrid solar-geothermal heat pump system

This research aims to improve the performance of an office building based on a new operation strategy for an evacuated tube solar collector-U-tube ground heat exchanger system. The main problem with the traditional operation strategy is the mismatch between the chiller capacity and the real cooling demand, which leads to operation of the air-conditioner units under low load rates and causes low system efficiency. In order to solve the above problem, we propose a new operation strategy, which controls the unit based on the load distribution of the building. Under this operation mode, the unit operates at full load rate during most operating times. Therefore, it can solve the mismatch between selection and operation and improve energy efficiency. We introduce the traditional operating strategy and design an experiment to evaluate the system performance for a solar thermal collector and geothermal heat exchanger system. We investigate the traditional operation strategy in detail, adopting the TRNSYS (Transient System Simulation) tool to develop a detailed simulation model that considers the seasonal system performance. The simulation results are validated by experiments. The simulation and experimental results show good agreement. Over 80% of the absolute relative errors have a magnitude falling within ±10%. As a result, compared with the traditional strategy, the proposed operation strategy can reduce the ground thermal imbalance in cold regions. The system coefficient of performance can be improved from 3.7 to 3.92, and the total electricity consumption is decreased by 6.4%.

Transformer Fuse Sizing—The NEC is not the Last Word

It is widely accepted that transformer primary side fuses should be appropriately sized to protect load side transformers. Proper sizing involves consideration of fault and overload conditions. The basis for such sizing is commonly derived from National Electrical Code (NEC) limits. The NEC imposed limits are the legal limits, but direct application of the NEC maximum values to size transformer primary side fuses is ill advised. The primary side fuse for medium voltage (MV) applications greater than 1000 V, as with most MV protective devices, is not intended to provide overload protection for the transformer, that is achieved by design (considering the intended loading on the transformer). The NEC recognizes this by permitting the fuse to be sized up to 300% of the transformer full-load ampere rating. It is clearly not a good idea to apply the maximum limits of the NEC as an absolute standard for fuse sizing to protect transformers in the absence of the application of other techniques (such as plotting the ANSI/IEEE thermal-mechanical damage characteristic for transformers on a time current curve along with the primary side (MV) fuse time current curve characteristic). These considerations are discussed in the course of this paper. The focus here is on dry type, low voltage transformers, although the content can be easily extended to liquid-filled transformers by using the equations from the appropriate standard.

Energy analysis and optimization of main hydraulic system in 10,000 kN fine blanking press with simulation and experimental methods

In this paper, a low-high pressure double oil hydraulic system with accumulators was presented with the features of high working efficiency, high control precision and large working capacity. To analyze the hydraulic system energy characteristic, a novel analytical approach, based on the mathematical energy dissipation model of hydraulic components, was proposed to calculate the system energy dissipation by establishing high accuracy simulation model. A test rig with a 10,000 kN hydraulic fine blanking press was built up and used to validate the proposed system and the energy analytical approach. Finally, the system energy dissipation of the 10,000 kN hydraulic fine blanking press was analyzed and the pump output pressure was optimized to minimize the energy dissipation with the genetic algorithm. Results indicate that the energy efficiency of the hydraulic fine blanking press hydraulic system is low, and especially under low-load conditions it is (0–50% full load rate) less than 15%. About 50% of the total input energy is consumed in the form of valve dissipation resulted from the imbalance of installed and demanded energy. After optimization, the total input energy decreases by nearly 50% and the energy efficiency increases by 10%, especially under low-load conditions.

Effects of exhaust gas recirculation temperature on diesel engine combustion and emissions

When hot exhaust gas is mixed with inlet air, the charge to a diesel engine is modified in three ways: the charge temperature increases, the total charge mass is reduced and the charge composition changes. This paper is concerned with the effects on combustion and pollutant emissions of only the first two items. The last item has been investigated by the authors previously and reported in references [1-4]. The investigation was conducted on a high-speed direct-injection diesel engine at about 40 per cent of full load, 2000 r/min and constant fuelling rate. The investigation included in-cylinder heat release and exhaust gas analysis. It was found that increasing inlet charge temperature, at constant inlet charge mass and composition, increased oxides of nitrogen (NO x) and particulate exhaust emissions but reduced unburnt hydrocarbon (UHC) emissions. When the inlet charge mass was reduced at constant inlet temperature, the exhaust particulates and UHC emissions increased substantially, principally because the oxygen available for combustion was reduced. In contrast, NO x emissions increased only slightly, probably because the effects on NO x of a higher combustion peak temperature tended to be offset by substantially lower oxygen availability.

Performance characteristics and optimum utilization of a cage machine as capacitance excited induction generator

The performance characteristics of a cage induction machine operating as a self-excited induction generator (SEIG) in stand-alone mode are presented. A static capacitor bank is considered to self-excite the machine and to maintain its terminal voltage constant. The lagging reactive power requirement of self-excited induction generator is obtained for different load values. The effect of speed on the excitation requirement of the cage machine has also been studied. An algorithm is developed to achieve these characteristics using the Newton-Raphson method and a steady-state equivalent circuit of the machine. The developed analytical technique is extended to evaluate the number of steps of switching capacitors for loading the machine up to its full load rating while maintaining the terminal voltage within desired limits. The selection of an optimum terminal voltage corresponding to the maximum output of the machine for its optimum utilization is also made using single-variable optimization.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>