Airport Operations Research Articles

STUDY OF GROUND FAULT PROTECTION SYSTEM IN THE MEDIUM VOLTAGE PANEL OF THE MAIN POWERHOUSE AT THE AIRPORT

The protection system is a system for securing electrical equipment caused by abnormal conditions such as short circuits (phase contact with the ground), human error, and others and detecting disturbances that occur and overcoming these disturbances in a short time. The ground fault protection system has not been activated at Juanda Airport Surabaya. This research aims to avoid problems that cause ground faults that spread throughout the MV. The Medium Voltage (MV) panel ground fault protection system used by MPH, namely MPH M-03, for voltage distribution to Air Field Lighting (AFL) substation and Airport Operation Building (AOB) substation, and Pump House 4 (PH 4) has not been activated. This study assesses the impact of activating the ground fault protection system for the MV MPH M-03 panel using the SEPAM protection relay. The research method is an exploratory study of the ground fault protection system in the M-03 main powerhouse medium voltage panel. The results showed that using a ground fault protection system for the MV MPH M-03 panel using the SEPAM protection relay is safer due to the ground fault indicator on the equipment. The Ground Fault panel helps protect electrical equipment and supplies from damage caused by ground faults. Quickly shutting off power in the event of a fault prevents excessive current flow that can damage or destroy sensitive equipment. This benefit is significant in industrial environments or areas with valuable equipment where downtime and repairs can be costly. The conclusion is that these systems should be used for safety in voltage transmission and distribution operations. Activating the ground fault protection system, operational safety at Juanda Airport Surabaya will be guaranteed, and it will be safer for the MV panel equipment and safety for the technicians working.

ESG and airports: The benefits and risks of ESG reporting for US airports

The subject of ESG — environmental, social and governance — disclosure and how airports are responding to the issues presented by these factors has become of great interest in the last few years. This paper will help familiarise airport managers and others with the concepts behind ESG and what these factors mean at an airport; discuss the reasons why an airport might want to provide ESG guidance to a wider audience; and review the potential risks and liabilities associated with ESG reporting, including a review of the application of US securities laws to disclosure regarding ESG, either formally through an official statement in connection with an issuance of bonds or less formally through an ESG report or by other means. ESG reporting has been driven, in large part, by the growth of funds and other investors who are seeking to invest primarily in securities issued to finance sustainable infrastructure and/or in entities that are working to achieve socially driven goals. It provides a very different scope of review of an airport's operations, focusing primarily on the external impacts of those operations on the environment, on affected communities and on how the entity operates within its regulated environment.

An empirical analysis of airport capacity evaluation: insights regarding air traffic design hours

An important and challenging question for air transportation regulators and airport operators is the definition and specification of airport capacity. Airport capacity is rather difficult to describe due to its multi-faceted and dynamic nature, and it depends both on the available infrastructure, on external factors and on operating procedures. Moreover, annual capacity is used for long term planning purposes as a degree of available service volume, but it poses several inefficiencies when measuring the true throughput of the system because of seasonal and daily variations of traffic. Instead, airport throughput is calculated or estimated for a short period of time, usually one hour. This brings about a mismatch: air traffic forecasts typically yield annual volumes, whereas capacity is measured on hourly figures. To manage the right balance between airport capacity and demand, annual traffic volumes must be converted into design hour volumes so that they can be compared with the true throughput of the system. This comparison is a cornerstone in planning new airport infrastructures, as design-period parameters are important for airport planners in anticipating where and when congestion occurs. Although the design hour for airport traffic has historically had a number of definitions, it is necessary to improve the way air traffic design hours are selected. By reviewing the relationships between hourly and annual air traffic volumes at 50 European airports during the period 2004-2021, this paper discusses the problem of defining a suitable peak hour for capacity evaluation purposes. Additionally, we appraise different daily traffic distribution patterns and their variation by hour of the day. The clustering of airports with respect to their capacity, operational, and traffic characteristics allows us to discover functional relationships between design hours and annual volumes. These relationships help us to propose empirical methods to derive expected traffic in design hours from annual volumes. This could be used to properly assess airport expansion projects or to optimise resource allocation tasks. Finally, we provide new evidence on the nature of airport capacity and the dynamics of air traffic design hours.

Fast response flight multi-service nodes prediction based on one hidden layer neural network

Airport scene multi-service process(ASMP) state prediction is one of the important links to optimize airport ground resource allocation, improve collaborative release scheduling, and improve airport operation efficiency. In order to solve the problem of the slow response of existing prediction models, a Gaussian kernel probability density model of multi-service nodes in airport scenes is established. Then the one hidden layer neural network(OHLNN) is used to predict the nodes of ASMP. A study on the data of more than 20,000 flights at a large airport in China shows that: The mean absolute error (MAE) of the mixed flight prediction result is only 2.62911min, the mean root mean square error (RMSE) is only 3.24564min, and the response speed of the prediction model in the verification set is about 0.48s. When the results of MAE and RMSE are good, the response speed of the prediction model is greatly improved.

A Three-Stage Hybrid SEM-BN-ANN Approach for Analyzing Airport Service Quality

The novel coronavirus (COVID-19) outbreak has impacted the aviation industry worldwide. Several restrictions and regulations have been implemented to prevent the virus’s spread and maintain airport operations. To recover the trustworthiness of air travelers in the new normality, improving airport service quality (ASQ) is necessary, ultimately increasing passenger satisfaction in airports. This research focuses on the relationship between passenger satisfaction and the ASQ dimensions of airports in Thailand. A three-stage analysis model was conducted by integrating structural equation modeling, Bayesian networks, and artificial neural networks to identify critical ASQ dimensions that highly impact overall satisfaction. The findings reveal that airport facilities, wayfinding, and security are three dominant dimensions influencing overall passenger satisfaction. This insight could help airport managers and operators recover passenger satisfaction, increase trustworthiness, and maintain the efficiency of the airports in not only this severe crisis but also in the new normality.

The Impact of Airport Facilities on Non-Aeronautical Revenue Through Airport Traffic And Aeronautical Revenue As Mediating Variables

Airport revenue, which consists of aeronautical and non-aeronautical revenue, is very important for airport operations and expansions. Once built, an airport must earn sufficient revenue to cover operating expenses and pay back infrastructure development capital from both public and private sources. Airport facilities and airport traffic determine revenue. The study aimed to analyze the impact of airport facilities on non-aeronautical revenue with airport traffic and aeronautical revenue as mediating variables. The research used a quantitative approach, where the population was Indonesian airports and the samples taken were from 27 Indonesian international airports and 8 Indonesian domestic airports in 2020. The result of this study discovered that non-aeronautical revenue at Indonesian airports can be affected directly and indirectly by airport facilities, airport traffic and aeronautical revenue. Airport facilities had a positive and significant direct effect on airport traffic. Airport traffic had a positive and significant direct effect on aeronautical revenue. Aeronautical revenue had a positive and significant direct effect to the Non-Aeronautical Revenue. However, only airport traffic had an indirect and significant effect on non-aeronautical revenue with aeronautical revenue as the mediating variable.
 Keywords: Airport Facilities, Airport Traffic, Airport Revenues, Aeronautical Revenue, Non-Aeronautical Revenue

A multi-stage multi-criteria data analytics approach to rank commercial service airports

The continuous performance evaluation of commercial service airports is an important part of airport operations. Despite its significance, the existing airport ranking approaches by various aviation organizations and agencies does not provide a comprehensive methodology to rank the airports based on multiple criteria. This paper proposes a comprehensive multi-stage multi-criteria data analytics approach that combines data envelopment analysis, best-worst method, and multi-attributive border approximation area comparison method to provide a robust ranking framework. The ranking procedure is based on seven criteria, i.e. passenger throughput, number of direct routes, number of check-in counters, terminal area, number of gates, number of flights, and number of runways. The proposed method ranks the shortlisted airports from the best to the worst and evaluates the strengths and weaknesses of each of the candidate airports. A real-world example involving the ranking of the efficient major commercial service airports in China is demonstrated to validate the applicability of the proposed approach. The insights generated have implications for the benchmarking of airports.

OPTIMALISASI PELAYANAN UNIT PENYELENGGARA BANDARA UDARA PADA SAAT PENDEMI COVID 19 DI BANDAR UDARA KOMODO LABUAN BAJO

Komodo Labuan bajo Airport is one of the companies that offers services in the field of aviation that will use air transportation services,.Before boarding the avsec officer will check the completeness of the trip before entering the area within the airport (check in ).in handling the avsec officer,of course there are several things which is an advantage for the company and Avsec officers,such as in terms of service,for service users so that the output obtained by the company will also be better.knowing the obstacles faced in the service of the airport operator unit during the pandemic.
 The study use a qualitative method.the data sources used are primary data and secondary data.the method or documentation technique used in this study is to obtain interview and observation data based on the results of research that has been carried out.The results of the study show that (1) the optimization of the Airport Operator unit service includes ensuring that passengers meet flight requirements during the covid 19 pandemic.(2) The problem is that many Avsec officers do not comply with health protocols such as crowding,not wearing masks,not keeping their distance,even playing with cellphones while checking passengers,and it happened that one of the passenggers did not meet one flight requirement.however,it is allowed to enter or travel.

Exploring Delay Propagation Causality in Various Airport Networks with Attention-Weighted Recurrent Graph Convolution Method

Exploring the delay causality between airports and comparing the delay propagation patterns across different airport networks is critical to better understand delay propagation mechanisms and provide effective delay mitigation strategies. A novel attention-based recurrent graph convolutional neural network is proposed to identify the hidden delay causality relationship among airports in three different airport networks of China. The selected three airport networks show great heterogeneities in topological characteristics, such as average intensity, modularity and eigenvector centrality. The modeling results indicate that the identified delay causality networks of three airport networks are greatly varied in terms of complexity, delay propagation distance and efficiency. Moreover, the delay state of each airport is categorized into three levels, and the delay state transition of the three networks is explored. The results indicate that delay state transition in the North China Control Area exhibits an obvious bidirectional transition form that mainly propagates between the large-degree airports and small-degree airports, while severe delays of some hub airports account for a relatively large proportion in the other two networks. The results of this study could better reveal the delay propagation mechanism among airports and help airport operators develop effective strategies to alleviate flight delays and improve airport operation efficiency.

ANALISIS UPAYA PEMULIHAN DAN PENINGKATAN KEGIATAN OPERASIONAL BANDARA H. HASAN AROEBOESMAN ENDE PASCA PANDEMI COVID-19

Since early March 2020, the Covid 19 pandemic has hit Indonesia and brought a major disaster to the world of aviation. This is evidenced by the drastic decrease in the number of passengers and aircraft at Ende Airport. Travel requirements and PSBB policies discourage people from traveling by air. Ende Airport's operational activities have decreased drastically due to the Covid 19 pandemic. This study aims to find out what efforts have been made to recover and increase operational activities after the Covid 19 pandemic and what obstacles have become obstacles in efforts to implement recovery and increase operational activities at H. Hasan Aroeboesman Ende after Covid-19.pandemic.
 The research was conducted qualitatively using primary and secondary data. Efforts to restore and increase Ende Airport operational activities after the Covid-19 pandemic are efforts originating from Ende Airport to improve and restore its airport operations after the Covid-19 pandemic. This study uses qualitative methods, obtained from primary and secondary data. Primary data is done by data, observation, interviews, and secondary data is done by documentation and literature study. This research was carried out at Ende Airport in August and September 2022.
 The results of this research are Ende Airport's efforts to improve and restore its post-pandemic airport operations, including: carrying out promotions, trying to create new flight routes, preparing places for rapid tests and coordinating with the local health office to administer vaccines. The obstacles that hinder this effort are the high ticket prices, the views of the public who are still worried about using air transportation services due to the Covid 19 pandemic and a lack of understanding about the requirements for people's travel by air transportation.

Analisis Operasional Bandar Udara Ngloram sebagai Satuan Pelayanan Bandar Udara di Kabupaten Blora


 Airport Service Unit, hereinafter abbreviated as SATPEL BU, is an airport service implementation unit that is under and responsible to the Head of Airport Operations Unit Office. In this study the Ngloram Airport Service Unit is under and responsible to the Head of the Dewadaru Airport Implementation Unit Office. This study is intended to find out how the Ngloram Airport Implementation Unit operates. Operations focus on policies, structure and work assignments, as well as technical standards and operations that exist in SATPEL BU Ngloram. This research was conducted using a descriptive qualitative approach and data collection techniques through observation, interviews, documents, literature study. This study uses primary and secondary data sources. Primary data sources were obtained from civil servants and honorary staff who served in SATPEL BU, while secondary data were in the form of statutory documents, books, journals and articles related to research topics. Based on the conclusions, the results show that the operations of SATPEL BU Ngloram have been running as they should according to the regulations in charge. It's just that there is a slight inequality in terms of division of work units. According to the researcher's analysis, if the restructuring process is carried out optimally, Ngloram Airport will experience an increase in classification from SATPEL BU to become Airport Operations Unit.
 Keywords: Airport Service Unit (SATPEL BU), operations, policies, structure and work assignments, technical standards and operations.

Comparison of logistic regression and artificial neural network model for apron allocation assignment

Management of the parking apron is one of the most essential airport ground service operations for flight operations to run smoothly. Effective airport ground service management will have a direct effect on the cost and duration of flights. Therefore, in this paper, we address the issue of using machine learning techniques, such as logistic regression analysis and artificial neural network (ANNs) models, for classified targets of stand locations assignment of an arriving flight. Also, this could assist ground controllers to assign apron allocation and improve the efficiency and predictability of airport operations which reduce the time required for airport ground processing to increase flight capacity. In order to evaluate the performance of the proposed method, simulation results reveal that ANN has the lowest error rate and the highest accuracy. Therefore, ANN is the effective classification technique for this data set.

POLYVINYLIDENE FLUORIDE MEMBRANES WITH TIN (IV) DIOXIDE (SNO2) ADDITIVES: ENHANCING WATER TREATMENT FOR AIRPORT ECO GREEN

Water treatment is a major process of realizing Eco Airport in airport development that does not cause environmental damage, protects the environment, and seeks to minimize the impact of environmental pollution due to airport operations. The growth and development of the global economy make a significant contribution resulting in increasingly uncontrolled disposal of wastewater, resulting in a series of environmental problems related to the provision of clean water at airports. This study discusses water filtration using membrane technology with Polyvinylidene Fluoride (PVDF) polymer mixed with Tin (IV) Dioxide (SnO2). This study aims to analyze the microstructure formed through Scanning Electron Microscopy (SEM) testing and determine the mechanical properties and performance in water treatment of mixed PVDF and Tin (IV) Dioxide (SnO2) membranes. This research is a new method in water treatment. The research method used was quantitative with initial membrane specimen formation, membrane preparation, flat sheet method, and testing methods (tensile testing, Scanning Electron Microscopy (SEM) observations, and Clean Water Permeability (CWP) testing. The results of this study, namely the formation of mixed membranes, showed the corresponding results as an alternative to water filter membranes. PVDF and SnO2 mixed membranes subjected to tensile tests using ASTM D638 standards, the surface structure of mixed membranes using SEM showed significant differences at each concentration, and the performance of water treatment performed with CWP showed an increase with increasing PVDF concentration and SnO2 for the airport. The conclusion is that water treatment performance using Clean Water Permeability (CWP) increases with increasing concentrations of PVDF and SnO2, which are suitable for airports.

Cost–Benefit Analysis of Investments in Air Traffic Management Infrastructures: A Behavioral Economics Approach

An important and challenging question for airport operators is the management of airport capacity and demand. Airport capacity depends on the available infrastructure, external factors, and operating procedures. Investments in Air Traffic Management (ATM) infrastructures mainly affect airside operations and include operational enhancements to improve the efficiency, reliability, and sustainability of airport operations. Therefore, they help increase capacity while limiting the impact on the airport infrastructure itself. By reviewing the neoclassical valuation principles for Cost–Benefit Analysis (CBA), we find that it does not consider relevant behavioral economic challenges to conventional analysis, particularly: failure of the expected utility hypotheses, dependence of valuations on reference points, and time inconsistency. These challenges are then incorporated through practical guidelines into the traditional welfare model to achieve a new methodology. We propose a novel CBA behavioral framework for investments in ATM infrastructures to help policy makers and airport operators when faced with a capacity development decision. This is complemented with a practical example to illustrate and test the applicability of the proposed model. The case study evaluates the deployment of Automatic Dependent Surveillance–Broadcast (ADS–B) as an investment aimed at improving ATM operational procedures in the airport environment by providing advanced ground surveillance data. This allows airport operators to discover the causes of taxi congestion and safety hotspots on the airport airside. The benefits of ADS–B are related to enhanced flight efficiency, reduced environmental impact, increased airport throughput, and improved operational predictability and flexibility, thus reducing waiting times. At the airport level, reducing the waiting times of aircraft on the ground would lead to a capacity release and a reduction in delays. The results show that, following a traditional CBA, the investment is clearly viable, with a strong economic return. Including behavioral notions allows us to propose a new evaluation framework that complements this conclusion with a model that also considers inconsistencies in time and risk perception. A positive Net Present Value can turn into a negative prospect valuation, if diminishing sensitivity and loss aversion are considered. This explains the reticent behavior of decision makers toward projects that require robust investments in the short-term, yet are slow to generate positive cash flows. Finally, we draw conclusions to inform policy makers about the effects of adopting a behavioral approach when evaluating ATM investments.

Early warning of low visibility using the ensembling of machine learning approaches for aviation services at Jay Prakash Narayan International (JPNI) Airport Patna

Extremely low visibility affects aviation services. Aviation services need accurate fog and low-visibility predictions for airport operations. Fog and low-visibility forecasting are difficult even with modern numerical weather prediction models and guiding systems. Limitations in comprehending the micro-scale processes that lead to fog formation, intensification, onset, and dissipation complicate fog prediction. This article predicts low visibility for Jay Prakash Narayan International Airport (JPNI), Patna, India, using a historical synoptic dataset. The proposed machine learning (ML) approaches optimize three meta-algorithm approaches: boosting (which reduces variances), bagging (which reduces bias), and stacking (which improves predictive forces). The ML approaches optimize the best prediction algorithms (at level 0) for fog (surface visibility ≤ 1000 m) and dense fog (surface visibility ≤ 200 m), and the suggested ensemble models at level 1 (an ensemble of level 0 ML approaches) deliver the highest performance and stability in prediction output. All time series perform well with the specified model (6-h to 1-h lead time for any combination of observed historical datasets). Airport management, planning, and decision-making rely on high reliability. Because it works well and is reliable, the proposed approaches can be used at other airports in India's Indo-Gangetic Plain.

Passengers’ Knowledge and Attitudes toward Green Initiatives in Aviation

The aviation sector is one of the fastest-growing segments of the transportation industry responsible for a considerable share of greenhouse gas emissions. Therefore, sustainability has become one of the central issues for the aviation sector. International regulatory bodies, airlines, and airport operators, along with aircraft manufacturers and suppliers have put forward initiatives to make aviation green. However, before the wider implementation of new sustainable practices, it is important to look at the opinion of passengers, as customers, on these matters. For this reason, this study aims to explore the knowledge and attitudes of Slovak passengers about green initiatives in aviation. The information about passengers’ knowledge and attitudes was collected through an online questionnaire. The data obtained from 514 respondents were evaluated employing descriptive and inferential statistics. From the results, several conclusions are apparent. Slovak passengers have generally weak environmental knowledge; therefore, it is important to provide them with enough relevant information to make informed decisions. The passengers have generally neutral to positive attitudes towards green initiatives in aviation, with the exception when these initiatives endanger their comfort or finances. For the development of green aviation, it is essential to increase the number of passengers with overall positive attitudes.

Optimizing the Planning of Airport Airside Expansion Projects to Minimize Air Traffic Disruptions and Construction Cost

This paper presents the development of a novel multiobjective model for optimizing the planning of airport airside expansion projects that provides the capability of minimizing both airport operations disruption cost and total construction cost. The model computations are performed in four main modules: (1) a simulation module that calculates and quantifies the impact of airport construction activities on airport operations, (2) a multiobjective genetic algorithms optimization module that identifies an optimal schedule for airport airside expansion projects, (3) a scheduling module that calculates the start and finish times of each construction activity, and (4) a cost module that computes the total cost of construction-related disruptions in airport operations and the total construction cost. A real-life case study of an airport airside expansion project is analyzed to illustrate the use of the model and highlight its original contributions to the body of knowledge including its novel methodologies for (1) quantifying and minimizing the impact of construction activities on airport operations, (2) analyzing and minimizing the impact of air traffic data and airport operations on total construction cost, and (3) generating a set of optimal construction plans including optimal project start time, activities start time, and weekly and daily work plans for all activities. The results of the case study clearly illustrate the original contributions of the developed model and its novel capabilities that are expected to support airport and construction planners in their efforts to improve the cost-effectiveness and functional performance of airports during airside expansion projects.

Railway liberalization, airport congestion toll, and infrastructure pricing: Modelling and numerical analysis for European and Chinese markets

Regulation on infrastructure pricing affects various aspects, including demand, social welfare, and investment in transport management, as well as intramodal and intermodal competition. This study develops a game theoretic model that derives the charges (set by the infrastructure operators) and fare prices (set by the transport operators) as well as the associated profit and welfare in equilibrium. Key analytical insights concern the joint effect of the product differentiation by the transport operators and profit/welfare orientation of the infrastructure operators. If the transport operator implements more differentiation between air and HSR, or the infrastructure operators are more profit-oriented, the transport mode becomes less sensitive to the access charge from the competing mode, but more sensitive to the access charge from the same mode. Furthermore, using publicly available data for European and Chinese markets, we investigate the effects of introducing HSR on-track competition and congested infrastructures through numerical studies. Key findings are that entry by an incumbent-owned compared to a privately-owned HSR generates more industry benefits but leads to a significant reduction in consumer surplus. A more profit-oriented airport operator leads to increased total welfare if congestion is sufficient high. Theoretical and policy insights are provided.

The competitiveness of global cargo airports employing the Best-Worst Method

PurposeThe global economy and air transport business have been negatively affected owing to the COVID-19 pandemic outbreak. As countries tighten restrictions on international movements, the growing emphasis on air cargo places pressure on airports to maintain and upgrade their cargo policies, facilities and operations. Hence, ensuring the competitiveness of cargo airports is pivotal for their survival under volatile global demand. This study aims to evaluate the importance of competitiveness factors for cargo airports and identify areas for further improvement.Design/methodology/approachThis study applies the Best-Worst Method (BWM) to assess the cargo airports' competitiveness factors.FindingsThe results identified “Transport Capacity” as the most significant competitiveness factor, implying that airport connectivity is crucial in promoting cargo transportation at hub airports. This result was followed by “Airport Operations' and Facilities' Capacity” and “Economic Growth.”. Additionally, the results identified Hong Kong International Airport as the best-performing cargo airport, followed by Aéroport de Paris-Charles de Gaulle and Incheon International Airport, respectively. Furthermore, both selected European airports are the most competitive airports in terms of “Financial Performance” and appear to be aware of the significance of their brand value.Originality/valueThis study forms a reference framework for evaluating cargo airports’ competitive positions, which may help identify airports’ relative strengths and weaknesses. Moreover, this framework can also serve as a tool to facilitate the strategic design of airports that can accommodate air cargo demand flexibly under demand uncertainty.

A Comparison of Airport Risks: Unmanned Aircraft Systems (UAS) Sightings, Wildlife Strikes, and Runway Incursions

To provide a context for the potential threat of unmanned aircraft systems (UAS) sightings on airport operations, this paper compares the characteristics of UAS sightings with two common airport threats: wildlife strikes and runway incursions. This study analyzed over 60,000 events in a three-year period (September 2016 to August 2019), including 6,551 UAS sightings from the Federal Aviation Administration (FAA) UAS Sightings Report database, 47,574 wildlife strikes from the FAA Wildlife Strike database, and 6,041 runway incursions from the FAA Runway Safety database. The results suggest both similarities and differences among the airport threats. Both UAS sightings and wildlife strikes vary by time of year and time of day. UAS sightings and wildlife strikes farther from the airport occur at higher altitudes than sightings and strikes occurring close to the airport. However, UAS sightings are reported at higher altitudes than wildlife strikes, and the distance of UAS sightings from the airport is farther than that of wildlife strikes, in general. The severities of UAS sightings and runway incursions are similar. Pilots take evasive actions in three percent of UAS sightings, and runway incursions of severity A and B are also rare. Pilots of general aviation (GA) aircraft reported the most UAS sightings, and GA operations are also involved in more runway incursions. Considering the kind of airport affected, UAS sightings and wildlife strikes are more common at primary airports, notably large and medium hub airports, whereas runway incursions are more common at reliever airports. Generally, UAS have had a minimal impact on airport operations despite their growing prevalence, which reflects the overall success of integrating this new airspace user into the national airspace system.