Terminal Gate Research Articles

Minimizing renewable hydrogen costs at producer's terminal gate with alkaline electrolyser, proton exchange membrane, and their co-installment: A regional case study in China

China leads in deploying large-scale alkaline (ALK) and proton exchange membrane (PEM) electrolysers for renewable hydrogen production. However, they are often overbuilt to handle intermittent renewable electricity (RE), leading to frequent system shutdowns, wasted capacity, or extensive investment. In this work, we propose a co-optimization solution in which ALK and PEM are collocated alongside hybrid RE supply from solar and wind energies. Implementing such a strategy could achieve the lowest hydrogen costs at producer's terminal gate, with production levelized costs of hydrogen (PLCOHs) down to 5.05, 4.13, 3.89, and 5.97 USD per kg respectively in south, north, west, and east regions of China. The co-optimization strategy, harnessing the combined strengths of ALK and PEM systems, efficiently minimizes hydrogen production costs while also presenting opportunities for the integration of advanced technologies into existing facilities.

Analisis Masalah Dalam Kegiatan Proses Receiving Unit CBU Di Terminal Internasional PT. Indonesia Kendaraan Terminal

Indonesia Kendaraan Terminal which is a company in the field of special terminal services for vehicle stacking. This research aims to find out what are the factors that affect the process of receiving activities of international terminal vehicles. In operational activities at the international terminal at PT Indonesia Kendaraan Terminal, there are several obstacles that can affect receiving activities. In the process of receiving vehicles at the international terminal gate, there are several factors that can hinder the receiving process and loading and unloading planning. This factor will certainly hinder the Receiving Process and Planning of Loading and Unloading so that it is inefficient and slows down the Receiving Process time at the gate and Load Planning activities in the international terminal field.

Aircraft Ground Support Equipment: A Framework for Maintenance Strategies

The airline industry encompasses a wide range of businesses, called airlines, which offer air transport services for paying customers or business partners. Airline industry can be classed as just one sector of the wider aviation industry. There are a number of services that may be done on a plane when it is parked at an airport terminal gate, and they are known as "aircraft ground handling. The number of passengers using airports continues to rise, pushing such facilities to their maximum capacity. Without the substantial services provided by the Ground Handlers, these brick and mortar infrastructures would not be able to continue to exist. Ground Support Equipment (GSE) is an industry term that refers to support equipment typically found at an airport that is used to service the aircraft between flights. The primary goal of GSE maintenance is to deliver the holder or user with safe and operable equipment that is also presentable, while incurring as little expenses as possible and experiencing as little downtime as possible. The laws that oversee airport operations must be complied with by any maintenance programs that are begun on GSE. Introduced equipment standardization, processes standardization, parts standardization, inventory management, asset management, maintenance KPIS, life of equipment and impacts on performance and reliability. Too little maintenance may lead to expensive breakdowns, poor system performance, and reduced dependability. Regular maintenance improves dependability but raises costs.

Analyzing different types of asymmetric responses in terminal gate prices of petrol and diesel across major Australian seaports: Implications for fuel price monitoring strategies

This paper examines the sign and size-dependent asymmetry in wholesale petrol and diesel prices in the long and short run across seven major distribution centres in Australia using daily data from 1 January 2004 to 18 November 2022. This study adopts a composite threshold mean model that is augmented with an asymmetric power autoregressive conditional heteroskedasticity (APARCH) model or an exponential general autoregressive conditional heteroskedastic (EGARCH) model to capture volatility clustering in high-frequency data. Inter alia, the results reveal that the long-run (adjustment) asymmetry is more widespread for unleaded petrol prices than diesel prices. Melbourne and Perth are the only two outport terminals that do not exhibit short- or long-run asymmetry for both diesel and petrol. In terms of the adjustment asymmetry, terminal gate prices for petrol in Darwin, Hobart, and Sydney are the least competitive, whereas the opposite is true for Adelaide, Brisbane, and Perth.

Research on Optimization of container Delivery Truck Appointment Considering No-showing and Carbon Emission

The truck appointment system is to set the share of truck appointment according to service capacity of the terminal gate and yard bridge, so that the facilities and equipment of container terminal can be reasonably used; On this basis, considering the situation that there are no-shows in container truck delivery process, and analyzing the impact of different types of no-shows on the appointment system. With the goal of minimizing the system cost of container terminal losses, an overbooking appointment model based on the optimization of container truck appointment is constructed by queuing theory, and the no-show probability is considered to optimize the original appointment share. Then designing an adaptive genetic algorithm to solve the model and search for the optimal overbooking scheme. Finally, an actual data example is used to verify the validity of the model and algorithm, which proves that the overbooking appointment model of the truck can more effectively improve the utilization rate of the terminal's equipment resources, reduce the terminal's meaningless carbon emissions, and restrict the irregular arrival of truck.

Examining the Effect of Airport Environment on Perceived Image, Memorable Experiences and Passenger Relational Behaviours

This study aims to explore air passengers’ relational behaviours in terms of advocacy and openness by considering the overall airport environment, perceived image, and memorable experience in the context of international airports. The data was gathered from 879 respondents who are experienced airport users. This study employs partial least squares structural equation modelling (PLS-SEM) to verify the validity and accuracy of the research model. The overall airport environment was established with the second-order formative construct of six dimensions, namely, information and layout, terminal ambience, security, passenger facilities, gate area, and leisure and entertainment. Findings enhance knowledge of the formation process of airport image and memorable travel experience and provide insights into tourism and airport literature, particularly from the perspectives of air passengers. This study also discusses practical implications.

Container terminal daily gate in and gate out forecasting using machine learning methods

Container throughput is an essential indicator for measuring the container terminal’s efficiency. Gate in and gate out containers are the containers that are transported to and transported out of the terminal respectively. Containers are stacked in the container yard before they leave the terminal. Handling of these containers accounts for a major workload at the terminal. Therefore, accurate short-term forecasting of the daily gate in and gate out containers at a container terminal is critical for operational planning. While most forecasts are made for the strategical level of the overall container throughput, this paper focuses on the daily gate in and gate out container quantities with a case study of Ningbo Zhoushan Port Beilun Second Container Terminal. Traditional approaches are mainly time series prediction algorithms that purely rely on the previously observed values. This paper proposes a novel decomposition-ensemble methodology framework which first divides the daily forecasting into a group of forecasting on a set of vessels which arrive in a certain time range around the predicted day. A novel machine learning method, “Extreme Gradient Boost (XGBoost)”, is used for the vessel level of forecasting, where some temporal-related features of vessels are considered in the model. We then ensemble the predicated value of all vessels in the set as the total gate in/out amount for a day. Experimental results demonstrate that our proposed method achieves notable performance gains compared to the time series-based method ARIMA. In addition, the results of this new technology can be fed into the terminal operating system (ToS) in the Ningbo Beilun container terminal for better management. Specifically, the prediction results facilitate effective real-time decision-making for operational management and policy drafting, such as workload planning, equipment scheduling, yard planning, etc.

Collaborative Optimization of Yard Crane Deployment and Inbound Truck Arrivals with Vessel-Dependent Time Windows

Due to mega-ships, increasing container throughput, and nonuniform truck arrivals, many container terminals face challenges of unbalanced workloads of yard equipment, shortage of equipment resources in peak hours, and congestion problem. To solve such issues, we propose a mixed-integer bilevel programming model to optimize the vessel-dependent time windows for inbound trucks and yard crane deployment simultaneously. In the proposed bilevel model, the upper level aims to minimize the total truck waiting time at the container terminal gate and yard, while the lower level is formulated to minimize the total workload overflow to next shift in the whole container yard. The optimal yard crane deployment obtained in the lower level will transfer to the upper level problem to determine the waiting time of trucks in the yard and then affect the truck arrivals pattern. To solve the model, a hybrid algorithm—called hybrid genetic algorithm, based on collective decision optimization—is put forward by combining the genetic algorithm and the collective decision optimization algorithm. Numerical experiments are conducted to validate the proposed approach is effective to simultaneously flatten truck arrivals and improve the efficiency of yard cranes. The proposed approach can significantly reduce container terminals’ truck waiting time.

Filter-free color pixel sensor using gated PIN photodiodes and machine learning techniques

This work addresses the possibility of light wavelength discrimination, using a specially designed Lateral PIN Gated Photodiode and Machine Learning signal processing techniques. The devices were designed at FEI University using IBM BiCMOS 8HP 0.13 μm technology. The terminal gate of the lateral PIN photodiode controls the vertical depletion layer, in order to modulate the capture of the electron-hole pairs generated by different wavelengths along the intrinsic region. The collected data were organized in optical power classes with the corresponding cathode currents. The experimental characterization shows that the terminal gate voltage can be used to discriminate different incident colors. The simulation results allowed the acquisition of a complete dataset to apply machine learning techniques and classify the photodetector captured color. This technique can be extended to photosensors arrays and eliminate the organic color filters. The best result was obtained using the “Linear and Quadratic Discriminant” algorithms, with the average accuracy of 92.46% and 96.82%, respectively.

A State-Dependent Approximation Method for Estimating Truck Queue Length at Marine Terminals

As international trade and freight volumes increase, there is a growing port congestion problem, leading to the long truck queues at US marine terminal gates. To address this problem, some countermeasures have been proposed and implemented for reducing truck queue length at marine terminals. To assess the effectiveness of these countermeasures, a method for accurately estimating terminal gate truck queue length is needed. This study developed a new method, named the state-dependent approximation method, for estimating the truck queue length at marine terminals. Based on the simulation of the truck queuing system, it was found that it takes several hours for the truck queue length to reach its steady state, and neglecting the queue formation (queue dispersion) processes will cause overestimation (underestimation) of truck queue length. The developed model can take into account the queue formation and dispersion processes, and it can be used to estimate the truck queue length caused by short-term oversaturation at marine terminals. For model evaluation, a simulation-based case study was conducted to evaluate the prediction accuracy of the developed model by comparing its results with the simulated queue lengths and the results of other four existing methods, including the fluid flow model, the M/M/S queuing model, and a simulation-based regression model developed a previous study. The evaluation results indicate that the developed model outperformed the other four modeling methods for different states of queue formation and dispersion processes. In addition, this new method can accurately estimate the truck queue length caused by the short-term system oversaturation during peak hours. Therefore, it will be useful for assessing the effectiveness of the countermeasures that are targeted at reducing the peak-hour congestion at marine terminals.

Impact of service policies on terminal gate efficiency: a simulation approach

Congestion at terminal gates is a significant issue that many ports are dealing with. The port of Songkhla, which serves as the main seaport in southern Thailand, has been confronted with this issu...

The Microsimulation Model for Assessing the Impact of Inbound Traffic Flows for Container Terminals Located near City Centers

The growth of container transport places increasing demand on traffic, especially in situations where container terminals are located near the city centers. The main problem is traffic congestion on networks caused by the integration of Heavy-Duty Vehicles and urban traffic flows. The main objective is to identify the critical traffic parameters which cause negative organizational and environmental impacts on the existing and future traffic demand. A micro-level traffic simulation model was implemented for the testing of the proposed framework-based supply, demand, and control layers. The model was generated and calibrated based on the example of a mid-size Container Terminal “Brajdica” and the City of Rijeka, Croatia. The results indicate that the critical parameters are Queue Length on the approach road to the Container Terminal and the Stop Delay on the main city corridor. High values of these parameters cause negative effects on the environment because of increased fuel consumption and the generation of extra pollution. Due to this problem, a sensitivity analysis of the traffic system performance has been conducted, with a decrement of Terminal Gate Time distribution by 10%. After re-running simulations, the results indicate the impact of subsequent variation in Terminal Gate Time on the decrease of critical parameters, fuel consumption, and vehicle pollution.

Measurement and Analysis of the Operations of Drayage Trucks in the Houston Area in Terms of Activities and Exhaust Emissions.

The effects of exhaust emissions on public welfare have prompted the US Environmental Protection Agency to take various actions toward understanding, modeling, and reducing air pollution from vehicles. This study was performed to better understand exhaust emissions of heavy-duty diesel-powered tractor-trailer trucks that operate in drayage service, which involves the moving of shipping containers to or from port terminals. The study involved the use of portable emissions measurement systems (PEMS) to measure both gaseous and particulate matter (PM) mass emission rates and record various vehicle and engine parameters from the test trucks as they performed their normal drayage service. These measurements were supplemented with port terminal gate entry/exit logs for all drayage trucks entering the two Port of Houston Authority container terminals. The datasets were combined to analyze model year characteristics of drayage trucks over time, evaluate port visit frequencies and durations, assess geographic distributions of trucks that perform port service, and estimate the pollutant emissions related to drayage operations. When compared to certification results, measured pollutant emissions generally exceeded certification standards in terms of nitrogen oxides and PM, although this difference may be partly because these vehicles were not tested on certification cycles but rather actual in-use operation. The findings of this work indicate that less than 3.5 percent of gaseous drayage truck emissions are released during operation within port terminals, as drayage trucks operate at higher engine loads during their extensive travels throughout the region around the port.

Tunable graphene-based mid-infrared plasmonic multispectral and narrow band-stop filter

In this paper, we numerically investigate the band-stop properties of single- or few-layers doped graphene ribbon arrays operating in the mid-infrared region by finite-difference time-domain method (FDTD). A perfect band-stop filter with extinction ratio (ER) ∼17 dB, 3 dB bandwidth ∼200 nm and the resonance notch located at 6.64 μm can be achieved. And desired working regions can be obtained by tuning the Fermi level (Ef) of the graphene ribbons and the geometrical parameters of the structure. Besides, by tuning the Fermi level of odd or even graphene ribbons with terminal gate voltage, we can achieve a dual-circuit switch with four states combinations of on-to-off. Furthermore, the multiple filter notches can be achieved by stacking few-layers structure, and the filter dips can be dynamically tuned to achieve the tunability and selective characteristics by tuning the Fermi-level of the graphene ribbons in the system. We believe that our proposal has the potential applications in selective filters and active plasmonic switching in the mid-infrared region.

A Simheuristic Method for the Reversible Lanes Allocation and Scheduling Problem at Smart Container Terminal Gate

Under the constraints of limited spaces and imbalanced traffic volumes (for both in and out directions) of container gates, reversible lane layouts become an economical and practical way to improve the service level of container terminal systems and make the maximum use of the current terminal resources. Together with a consideration of minimized total costs (both construction and operating) of terminal gate system, this paper first developed an optimization model to decide the number and scheduling rules of the reversible lanes at a terminal gate. A metaheuristic algorithm was built to solve the optimal model. Meanwhile, to reflect the randomness and dynamics property of the terminal gate system in practice, parameters that cannot be calculated from conventional analytic methods are obtained through a simulation model. Finally, a hub container terminal in the northeast of China was employed to verify the effectiveness of the proposed method and provide a theoretical foundation for the construction and management of terminal gate systems.

Container – Terminal – Gate – System Optimization

The utility of the container terminal has become quite remarkable all over the world. It is vital to maximize the utility of the container yard and the terminal gate system. With the ever-increasing importance of containerization in the world, more than 60% of cargo is transported by containers, this ratio even reaches 100% in some highly economic developed and political stable places. It is estimated that, the total quantity of containerization in the world will increase by 10% every year before 2020. The aim of this work is to be used as a decision support system tool when designing and constructing container terminals. The article focuses on optimizing the staging of containers within a terminal gate system. A Port within the main Land China is being used as a test bed to demonstrate the Simulation Model based on Queuing Theory. The analysis considers both the facility and the setting of the terminal gate system by considering the Discrete Event System Theory and the terminal gate system in order to make the daily operation more suitable for the terminal. The research combines the computer simulation method and the actual complex discrete event system, and identifies the most suitable setting and the theoretical maximum capacity for the terminal. Normally, the usage ratio (the busy time) should be around 75%, the simulation findings, the channel performance measures indicators are the usage ratio and the average waiting time the proper number of channel is 3 for entrance channel, and 2 for exit channel with usage ratios of 74% and exit usage of 55%, allocating 3 Entrance Channel (gates) and 2 Exit Channels (gates). Both the entrance and exit saved 2 channels. Both the capacity and channel number calculation are treated as a reference for the future decision maker when it comes to the container terminal construction.

Investigation of gate leakage current mechanism in AlGaN/GaN high-electron-mobility transistors with sputtered TiN

The gate leakage current mechanism of AlGaN/GaN Schottky barrier diodes (SBDs) and high-electron-mobility transistors (HEMTs) with sputtered TiN is systematically investigated. The reverse leakage current (JR) of TiN SBDs increases exponentially with the increase of reverse voltage (VR) from 0 to −3.2 V (Reg. I). This conduction behavior is dominated by Poole-Frenkel emission from TiN through an interface state of 0.53 eV to the conductive dislocation-related continuum states. The obtained interface state of 0.53 eV may be due to the plasma damage to the surface of the AlGaN/GaN HEMT structure during the TiN sputtering. When the TiN SBDs are biased with −20 < VR < −3.2 V, JR saturated due to the depletion of the 2-dimensional electron gas (2DEG) channel (Reg. II). This conduction behavior is dominated by the trap-assisted tunneling through the interface state at ∼0.115 eV above the Fermi level. The three terminal OFF-state gate leakage current of AlGaN/GaN HEMTs exhibited an activation energy of 0.159 eV, which is in close agreement with the obtained interface state of ∼0.115 eV from saturated JR (Reg. II) of the SBDs. The observation of the negative temperature coefficient (−1.75 V/K) from the OFF-state breakdown voltage (at 1 μA/mm) of AlGaN/GaN HEMTs is due to the trap-assisted tunneling mechanism, which is also well correlated with the conduction mechanism realized from the reverse leakage current of the SBDs.

A reward-based algorithm for the stacking of outbound containers

Abstract: As global trade increases, container transshipment activities increase rapidly. Therefore, high competition among container terminals has emerged. The decision for good stacking positions for containers plays a critical role on the performance of a container terminal, since it influences the productivity of the terminal in a strong sense. In this study, we focus on the minimization of the berthing time of vessels by improving the stacking operations through minimization of non-value-added handling operations of containers, which is called reshuffling, as well as the traveling time of the cranes operating at the storage yard. Most of the containers in the container terminal we focus are outbound, which are transported into the container terminal via external trucks and stored in the stacking yard until they are loaded onto vessels. We propose a reward-based algorithm for the stacking of outbound containers by taking the following four components into consideration; container's distance to the closest RTGC, RTGC's workload, the number of stacked containers at the neighborhood bays, and the current height of the stacks at the storage yard. The inputs of the algorithm include the relevant information of the container to be stacked that are just entered into the terminal gate, current usage information of the storage yard and the current positions of the yard cranes. The proposed stacking strategy is in implementation phase to one of the container terminals in Izmir. The results seem to be promising when compared to the current randomized stacking strategy in the container terminal.

The Future of Conventional Aircraft Ground Propulsion Systems in Relation to Fuel Consumption and CO2 Emission

Aircraft spends a minimum of 20 minutes using its main engine to taxi from the airport terminal gate to the runway, where the aircraft takes-off and similarly to the terminal gate after landing. During taxi operation, aircraft burns a lot of fuel, generates large quantity of emissions and the engine in the process of taxiing is exposed to damage due to Foreign Object Damage (FOD). This results in huge operational and maintenance cost as well as carbon emission tax which are all at the expense of the airline. EGTS is a recent technology designed to prevent aircraft from using its main engine for taxi operation and this in turn reduces the rate of fuel consumption, slashes carbon emissions and minimises operational and maintenance cost. This paper examines the viability of using EGTS in single engines for taxi operation rather than the aircraft engine. Block fuel savings was calculated for two engine, single engine and hybrid aircraft and it was observed that two engine aircraft using EGTS saved 110kg block fuel, single engine saved 74kg and for hybrid engine the block fuel savings was 50kg. Block fuel savings was calculated for aircraft such as airbus A320, airbus A380, Cessna 172 and A600ST and it was observed that EGTS is more compatible with airbus A320 but was not recommended for A600ST and A380 due to extra weight implication and for Cessna 172, EGTS was not necessary because the aircraft weight is low and consumes less fuel already. It was observed that the higher the aircraft weight including the extra weight of EGTS, the higher the fuel consumption emission as well as the torque required to overcome drag force when the aircraft operates in air. CO2 emission was also calculated for aircraft with EGTS and aircraft without installation, the result for aircraft with EGTS showed 797.56kg reduction of CO2 emission when compared to aircraft without EGTS. Comparably, EGTS was proven to be viable in terms of fuel savings, CO2 emissions, operational and maintenance cost than its contemporary Ground Propulsion Systems (GPS) for single aircraft engines and therefore, was recommended for aircraft in airbus A320 category to help minimise global warming which results from CO2 emission during taxing operations.

Optimal design of container terminal gate layout

Over the last 50 years, international trade of goods has grown significantly in the USA, and as a result, US ports have become bottlenecks in the freight supply chain and logistics. A particular issue that most US ports are contending with is gate congestion (i.e., queuing of trucks outside the container terminal gate). This research provides planners and engineers of container terminals a set of methodologies to design an optimal gate layout to reduce gate congestion. The use of the methodologies to determine the optimal number of service gates is illustrated considering various truck arrival rates, gate service rates, and waiting time thresholds.