Airport Operations Research Articles

Determination of Limited Security Area at the Indonesian Flight Academy, Banyuwangi: A Case Study at Banyuwangi Airport

The Security Restricted Area at airports plays a crucial role in preventing unauthorized access and criminal activities around the airport. This research aims to evaluate the design of the Security Restricted Area and access control at Banyuwangi Airport, operated by the Indonesian Civil Pilot Academy Banyuwangi. The research adopts a qualitative approach with data collection techniques such as participant observation, interviews with relevant stakeholders, and analysis of documents related to airport security regulations and standards. The findings reveal that the Airport Business Entity (BUBU) or airport operator is responsible for security in the airside area, but through a Memorandum of Understanding (MoU), this responsibility is delegated to the Indonesian Civil Pilot Academy Banyuwangi. Weaknesses in access control and security measures were identified in the airside area operated by the academy, including inadequate guarding at certain access points and the absence of mapping for the Security Restricted Area. The research provides recommendations to enhance access control and security at Banyuwangi Airport, aiming to improve operational safety and the airport's reputation.

Modeling Circle Runway to Increase Runway Capacity

Runway is a runway for airplanes to land (landing) or to fly (takeoff). Runway is a major component in an airport, it is necessary to plan a good runway. The runway at Juanda Airport uses a conventional system where the runway is rectangular. In this final project the author plans a runway with a circular runway model. The circular runway is a radical new runway design with a circular shape. With a circular runway, airport operators can operate the runway regardless of the wind direction and for all types of aircraft. Airports with circular runways have a smaller footprint than airports with conventional runways. With the existence of a circular runway, it is expected to increase runway capacity compared to conventional runway capacity. Circular runways can also allow airports to continue operating without interference from crosswinds. From the calculation results, it is found that the runway has a circumference of 9864 m. The ARFL length obtained for a circular runway with a Boeing 747-400 aircraft as a reference is 3795 m. The width of the circular runway is determined to be 140 m wide. The slope of the runway starts at an angle of 0° and then increases gradually to 20°. While the force felt by the aircraft when landing on a circular runway is 0.43 g. Juanda's conventional runway capacity is 32 operations per hour. Where the circular runway capacity is 64 operations per hour, this capacity may increase depending on the type of aircraft served.

Prediction of Hourly Airport Operational Throughput with a Multi-Branch Convolutional Neural Network

Extensive research in predicting annual passenger throughput has been conducted, aiming at providing decision support for airport construction, aircraft procurement, resource management, flight scheduling, etc. However, how airport operational throughput is affected by convective weather in the vicinity of the airport and how to predict short-term airport operational throughput have not been well studied. Convective weather near the airport could make arrivals miss their positions in the arrival stream and reduce airfield efficiency in terms of the utilization of runway capacities. This research leverages the learning-based method (MB-ResNet model) to predict airport hourly throughput and takes Hartsfield–Jackson Atlanta International Airport (ATL) as the case study to demonstrate the developed method. To indicate convective weather, this research uses Rapid Refresh model (RAP) data from the National Oceanic and Atmospheric Administration (NOAA). Although it is a comprehensive and powerful weather data product, RAP has not been widely used in aviation research. This study demonstrated that RAP data, after being carefully decoded, cleaned, and pre-processed, can play a significant role in explaining airfield efficiency variation. Applying machine learning/deep learning in air traffic management is an area worthy of the attention of aviation researchers. Such advanced artificial intelligence techniques can make use of big data from the aviation sector and improve the predictability of the national airspace system and, consequently, operational efficiency. The short-term airport operational throughput predicted in this study can be used by air traffic controllers and airport managers for the allocations of resources at airports to improve airport operations.

Factors Influencing Airport Technology Development: Customer Convenience, Aviation Security, and Environmental Issues

Technology development had introduced automation techniques in the airport operation and service system. Passengers also feel more comfortable choosing an airport which has equipped with technology. Therefore, many airports are becoming more enthusiastic about implementing new technologies because they can increase efficiency, reliability, and sustainability within their operations. This article then tried to explain several factors which are significantly influencing airport technology development. The method used by the authors was a qualitative method focusing on the literature review. The research result showed that there are three prominent factors influencing airport technology development. First, the customer convenience factor encourages airports to apply self-service technologies that are more flexible and efficient. Second, the aviation security factor creates body scanner technology to automatically scan the passengers and the liquid explosives detection system. Third, environmental issues can be looked at from the airport’s efforts to implement various energy-saving behaviors and utilize renewable energy sources. Moreover, there are also other factors influencing the airport technology development, namely price, rapidness, customer experience, customer value, risk minimization, and communication enhancem.

Introducing the novel concept of cumulative concentration roses for studying the transport of ultrafine particles from an airport to adjacent residential areas

Abstract. Airports are often surrounded by urban residential areas, which is both a motivation and challenge for studying their potential impact on local air quality. Airports are a relevant source of ultrafine particles (UFPs), which can pose a risk to human health due to their small size (particle diameter Dp≤100 nm). However, in urban environments, UFPs originate from a multitude of biogenic and anthropogenic sources. Here, we investigate UFPs in close proximity to an airport to disentangle their impact on local air quality from other urban sources. We present observations and analyses of airborne UFP concentrations and size distributions determined at two sites in close proximity to Munich Airport. Therefore, two novel measurement stations were established north and south of the airport but were neither situated on the axis of prevailing wind directions nor impacted by fly overs. This set-up allowed us to explore a mainly advection-driven distribution of UFPs into the most populated adjacent residential areas. The observation period covered a full year from August 2021 to July 2022. We analysed the data set in three steps. (1) First, we derived UFP concentration roses using the wind data as reported at 10 m height at the airport to represent the local wind field. An increase in particle number concentrations and a shift of the modal maximum towards smaller mobility diameters became evident for wind directions, including those approaching from the airport. During the airport's operation hours during the daytime, median particle number concentrations were 2.2- and 1.6-fold compared to nighttime at the northern station and the southern station. However, our data had a high variability, and the direction-based analysis was uncertain due to other potential UFP sources in the surroundings and the assumption of a homogeneous, local wind field. (2) Next, we derived concentration roses employing the airflow observations from the two measuring stations at 5.3 m height. While the annual concentration rose in principle yielded the same conclusions as the first analysis step, a significant seasonal and diurnal variability of UFPs and wind became evident. The influencing factors were likely other urban local UFP sources, an increased surface roughness due to green vegetation, and the atmospheric boundary layer development. (3) In order to assess the possible advection of UFPs from the direction of Munich Airport relative to all other directions over the course of the year, we calculated cumulative concentration roses with both local- and site-scale wind data. Under the assumption of a homogeneous local wind field, the fraction of all UFPs sampled in airflows approaching from the airport's direction was 21 % (N322) and 40 % (S229). Considering a local background, the range of UFP advection from Munich Airport to the adjacent residential areas was up to 10 % in the north and 14 % in the south. It has to be noted that these values highlight the relative magnitude of the maximum impact of the airport on local air quality as they do not distinguish between UFP sources from the airport and other measuring sites. Additionally, they integrate over a time period during which the airport did not reach its full capacity compared to pre-COVID-19 times.

The impact of COVID-19 related flight reductions on bird prevalence and behaviour at Manchester Airport, UK, and the implications for airport management

Airport management is a complex and multifarious activity, involving many operators including airlines, retailers and ground handlers, and processes. The presence of wildlife at airports poses a safety risk to aircraft operations and as such managing wildlife hazards is a mandatory legal responsibility. This is important not only from a safety perspective but also from the fact that safety incidents can impact the operational efficiency and the reputation of an airport. Airport operators are required to devise and enact site-specific Wildlife Hazard Management Plans (WHMP) to reduce the risk of aircraft-wildlife interaction under normal airport operating conditions. The COVID-19 pandemic, however, led to an unprecedented reduction in commercial air traffic and the partial or total suspension of flights at some airports. The aim of this paper is to examine the impact of COVID-19 related flight reductions on bird prevalence and behaviour and the potential implications for airport management. Drawing on an empirical dataset of wildlife observations at Manchester Airport, UK, in 2019 and 2020, this paper details the airfield ornithology before and during the pandemic and examines the impact of COVID-19 related flight reductions on bird prevalence and behaviour. The findings reveal variations in the frequency and apparency of individual species as well as changes in the spatial location of bird sightings on the airfield. The paper concludes by discussing the implications of these findings for post-pandemic operations and for the formulation of future airport wildlife hazard management policies.

Socialization Related to the Dangers of Kites, Laser Beams, Hot Air Balloons, and Drones Around Silampari Lubuklinggau Airport

The implementation of socialization in the Tridharma of Higher Education framework is by conducting research and compiling Scientific Journals within the Palembang Aviation Polytechnic, South Sumatra. In addition, this activity aims to increase the knowledge and awareness of the general public around the Silampari – Lubuklinggau Class III Airport Operator Unit. This activity also informs about the dangers of kites, laser beams, hot air balloons, and drones around the air space in Silampari – Lubuklinggau as well as the safe distance of building construction, especially in the Flight Operation Safety Area, especially people who live close to the Flight Operation Safety Area (KKOP). The method used for socialization is a participatory Focus Group Discussion (FGD) by resource persons and discussions with communities living around the Silampari – Lubuklinggau Class III Airport Operator Unit that the results are expected so that participants know the results of socialization related to activities that can endanger flights. Then, the results of the socialization were published on the social media of the Palembang Poltekbang.

Reliable and robust scheduling of airport operation resources by simulation optimization feedback and conflict resolution

Reliable and robust airport flight ground service resources collaborative scheduling has emerged as an issue of major concern at congested airports, which has great significance on airport service quality and operation efficiency. Due to the uncertainty of the service process of multiple vehicles in airport ground operations, the combination of simulation and optimization (sim-opt) techniques has been proven to be an effective means to solve the collaborative scheduling problem. However, existing models still have limitations on the reliability of feasible solutions and the robustness of evaluations. In this work, we developed a conflict resolution based sim-opt framework that combines the search capability of mathematical optimization models with the ability of simulation models to describe uncertainty. The dynamic window is introduced to divide the flight zone into multiple sub-intervals, which allows for iterative search and evaluation of the optimal schedule solution while reducing model calculation time. Additionally, a matching algorithm based on slack and tight constraints is proposed to optimize the possible resource requirements of each vehicle, thereby improving the initial schedule solution’s search depth and reliability. Furthermore, a conflict resolution feedback mechanism between adjacent windows is constructed to optimize the scheduling plan, reducing misjudgment and omission of the optimal solution and enhancing the sim-opt framework’s robustness. Finally, experiments on real airport datasets of three different scales demonstrate that our proposed method efficiently allocates resources with a smaller flight delay time as well as reducing total vehicle cost time during the flight ground service process.

УДОСКОНАЛЕННЯ ІСНУЮЧИХ МЕТОДІВ ОЦІНЮВАННЯ ФУНКЦІОНУВАННЯ АЕРОПОРТІВ ПРИ МІЖНАРОДНІЙ ІНТЕГРАЦІЇ

The article is devoted to the study of methods for assessing the operation of airports under international integration and their improvement. The recent scientific studies on assessing the operation of international airports were analyzed and it was found that the most actively used methods are the initial data envelopment analysis (DEA) and various variants of quantile regression, Tobit regression, assurance region methods, SBI and DMU, Malmquist index, classification and regression tree, bootstrapping tool and other tools. It was confirmed that the existing methods for assessing the airports’ operation have a significant number of indicators for calculations based on the evaluation of economic, technical or overall efficiency. The parametric methods for assessing the operation of airports, their advantages and disadvantages were characterized. The methodology of stochastic frontier analysis (SFA), the use of a non-parametric approach to evaluate airport performance, and the evaluation of the overall efficiency of two-stage DMUs with shared resources were described. The methodical approaches based on the use of the spatial regression model, the AAG model and the stochastic frontier model were characterized. The methodology for determining the target function Effi to assess the efficiency of each airport DMUi was described. The scheme for assessing the airports’ operation by input and output indicators was proposed, which includes a three-module assessment system for the passenger, cargo and joint modules. The cargo module is the authors’ own development and its creation is justified by the fact that a significant number of air cargo flows are served by passenger aircraft. The group of input indicators of the cargo module includes the length of the loading and unloading work front, the number of cargo receiving points, the working area of rack and stack storage, the number of electric forklifts and lift trucks, as well as the number of cargo warehouses, and the number of general and special categories of cargo are defined as output indicators.

Primena veštačke inteligencije u uslugama aviprevoza, GEP studija zadovoljstva korisnika na aerodromima u Srbiji

AI technologies have significantly transformed various sectors, including travel and airport operations. This research aims to investigate the implications of implementing artificial intelligence (AI) in airport services on passenger satisfaction and overall travel experiences, as well as how AI technology shapes the way airports support passengers throughout their journey. The study conducted empirical research at Serbian airports with a sample size of 668 passengers. Participants provided their attitudes and satisfaction ratings on 10 statements regarding the impact of AI technology implementation in airport services. The findings from regression analysis reveal a high level of AI implementation in airport services, particularly concerning passenger experience and security. However, passengers express less satisfaction with the implementation of chatbots and virtual assistants, AI algorithms, and certain AI tools that do not meet their expectations. Specifically, passengers feel they do not always receive sufficient instant responses, real-time flight information in the case of delays, or effective issue resolution at the analyzed airports. These results contribute valuable insights to the AI literature and offer implications for future implementations of these technologies in industry, marketing, and technology development. Moreover, they can guide managerial practices and investments in future digital technologies aimed at enhancing passenger experience.

Digital Twin Based Resource Optimization and Dynamic Decision Making in Air Terminal Yards

Abstract With the growth of globalized trade, the efficient operation of airports is crucial. In this paper, we study the use of digital twin technology to optimize the yard resources of airports, which can improve their operational efficiency and decision-making quality. The study first constructs a digital twin framework for intelligent yard scheduling, which contains physical and virtual space and the connection between them. Data is collected through the physical perception module, while the virtual space is used for real-time simulation and optimized decision-making. The research methodology includes mixed integer programming and adaptive immune cloning algorithms for optimizing yard resource allocation and box space allocation. The experimental results show that the method can effectively reduce the total transportation distance in the air terminal yard operation and improve operation efficiency. The experiments demonstrate an average improvement in operational efficiency of around 20% and a cost reduction of around 15%. It is concluded that digital twin technology has apparent advantages in allocating resources in air terminal yards, which can achieve efficient utilization of resources and dynamic optimization of decision-making.

Preliminary Exploration of Rational Settings for Sponge Airport Indicators in the Context of Low Carbon -- Taking Baiyun Airport as an Example

Sponge city is an important means of urban stormwater management, and it is also the core concept of green and low-carbon ecological landscape construction.Currently, the rainfall and flooding problems of airports are becoming more and more obvious, and the construction of "sponge airports" is getting more and more attention. However, considering the operational needs of airports, the existing conventional sponge construction ideas cannot be directly applied to airport construction. How to set up a set of reasonable indicators that not only guarantee the safe operation of airports but also meet the requirements of the existing sponge city construction is one of the problems that need to be solved in the process of airport sponge city construction. Taking the third phase expansion project of Guangzhou Baiyun Airport as an example, the design principles of focusing on safety, adapting measures to local conditions, and meeting the overall standards, from the overall consideration of the airport, combined with the land use of each functional zone of the airport, reasonably set the sponge index, so as to provide a reference for the construction of "sponge airport", in order to promote the sustainable development of green and low-carbon construction.

Prediction of Off-Block Time Distribution for Departure Metering

The uncertainties related to target off-block time (TOBT), the pushback-ready time predicted by aircraft operators, affect greatly airport operations. The accuracy of TOBT is, in general, difficult to be improved, because there are many uncertain factors in the departure process, e.g., delays in the passengers’ boarding. A better understanding of TOBT uncertainties, however, may help to improve airport surface operations. Currently, TOBT is estimated as a single point in time and updated as necessary by aircraft operators. Instead, the author proposes that TOBT is estimated as a distribution with a Johnson-SU distribution. The distribution parameters are estimated with time by neural networks using the history of TOBT updates. The main benefit of the proposed method is found in assigning the better pushback approval time of each departure aircraft for more efficient surface operations, which is demonstrated clearly by the simulation results. Using the proposed method, the aircraft operators can save fuel from improved ground operations via a probabilistic approach at the cost of reporting TOBT as a single point.

Aircraft turnaround time dynamic prediction based on Time Transition Petri Net.

Accurate aircraft turnaround time prediction is an important way to coordinate the operation time of airport ground service and improve the efficiency of airport operation. In this paper, by analyzing the aircraft turnaround operation process, a description model based on Time Transition Petri Net is proposed. The model describes the flight turnaround operation process and the logical relationship of the operation. According to the model, a dynamic prediction method of turnaround time based on Bayesian theorem is designed. According to the actual landing time of the flight, the aircraft turnaround time is predicted. The specific method is to obtain the prior probability distribution and joint distribution law of each operation link according to the flight history data, and use Shapiro-Wilke to test the prior probability distribution of each link. Based on the analysis and comparison between the actual turnaround data of a large airport in China and the forecast data proposed in this paper, the root-mean-square error 3.75 minutes and the mean absolute error 3.40 minutes can be calculated. This paper contributes to the improvement of flight punctuality rate and airport clearance level.

Visual Research on Airport Operational Efficiency in China over the Past Decade Based on CiteSpace

Visual Research on Airport Operational Efficiency in China over the Past Decade Based on CiteSpace

Comprehensive assessment of air pollutant and noise emissions at airports across different altitudes

<p>We utilized the International Civil Aviation Organization (ICAO) standard emission model, refined with adjustments for fuel flow, LTO cycle work mode time, and emission indices, to investigate the environmental footprint of airports at different altitudes. Airports categorized as high (above 5000 $ \mathrm{f}\mathrm{t} $), medium (1500–5000 $ \mathrm{f}\mathrm{t} $), and low (below 1500 $ \mathrm{f}\mathrm{t} $) altitudes were selected to provide a comprehensive representation of the altitude spectrum. The analysis was anchored over the period spanning 2016 to 2017. Emission inventories for air pollutants and noise were computed for these airports, focusing on the LTO (Landing and Take-Off) cycle. Our findings indicated that high altitude airports exhibit the highest $ {\mathrm{N}\mathrm{O}}_{\mathrm{x}} $ emissions, reaching 406.4 $ \mathrm{t} $, whereas low altitude airports record the highest noise levels at 73.1 $ \mathrm{d}\mathrm{B} $. Significant disparities in emission profiles were observed across different phases of the LTO cycle at airports of varying altitudes. Notably, during the climb phase, the types and proportion of $ {\mathrm{N}\mathrm{O}}_{\mathrm{x}} $ emissions at high altitude airports were as high as 71.8%, contrasting with the 45.6% at low altitude airports. Additionally, emissions of gaseous pollutants from major aircrafts, exemplified by the A320 model, escalated with altitude. Specifically, $ {\mathrm{N}\mathrm{O}}_{\mathrm{x}} $ emissions increased from 10.55 $ \mathrm{k}\mathrm{g}/\mathrm{c}\mathrm{y}\mathrm{c}\mathrm{l}\mathrm{e} $ at low altitude to 20.48 $ \mathrm{k}\mathrm{g}/\mathrm{c}\mathrm{y}\mathrm{c}\mathrm{l}\mathrm{e} $ at high altitude, and $ \mathrm{C}\mathrm{O} $ emissions from 10.88 $ \mathrm{k}\mathrm{g}/\mathrm{c}\mathrm{y}\mathrm{c}\mathrm{l}\mathrm{e} $ to 22.89 $ \mathrm{k}\mathrm{g}/\mathrm{c}\mathrm{y}\mathrm{c}\mathrm{l}\mathrm{e} $. A robust correlation between $ {\mathrm{N}\mathrm{O}}_{\mathrm{x}} $ emissions and $ {L}_{den} $ was identified among airports at different altitudes, with correlation coefficients of 0.96 for low altitude, 0.97 for medium altitude, and 0.93 for high altitude airports. This study delineates the distinct characteristics of air pollutant and noise emissions from airports across altitudes, offering novel insights for the environmental assessment of airport operations.</p>

Strategy Development for Improving Airport Efficiency of Landlocked Country using DEA Malmquist: Case of Mongolian Chinggis Khaan Airport

Improving the performance of landlocked countries’ airports significantly impacts the country’s economy. This study aims to evaluate the operations of well-known airports globally and identify innovative initiatives and improvements that can be implemented at Chinggis Khaan Airport. The paper analyzes the productivity of 50 airports using the DEA Malmquist index, collecting data from 2017-2022 to improve passenger flow and freight volume at Chinggis Khaan Airport. Despite the pandemic in the years 2020 and 2021, some airports showed promising results, and these are the airports we aim to emulate. The results provide comprehensive insights into the aviation industry’s criteria to aid decision-makers, emphasizing the need for greater attention to management activities

Analisa Kelayakan Finansial Proyek Automated People Mover System Bandar Udara Internasional Soekarno-Hatta

The growth in the number of passengers continues to increase every year, so increasing capacity is a challenge for airport operators, including by increasing the number of sub-terminals, namely: terminal 1, terminal 2 and terminal 3. being a passenger is a new problem that must be solved because the lockdown creates the potential for traffic jams and causes passengers to be late. To overcome these problems, Soekarno-Hatta International Airport has made modifications to carry out infrastructure development that can provide an integrated, dedicated transportation service system so that priority passenger mobility can be served properly. The operation of flying boats is a service system supporting intermodal and inter-sub-terminal connectivity, the cost of organizing flying boats requires quite large costs, namely investment costs and operational costs. / Passenger Service Fee (PSC), since the corona virus disease (covid 19) pandemic, this income has been decreasing. The research aims to financial analysis of the Automated People Mover System Project and perform calculations such as the Internal Return Rate, Net Present Value, Return On Investment, and Pay Back Period. The research results are declared not feasible because they are not providing benefit.

Econometric evidence on the profits and revenues of Indian regional airports

The low profitability of regional airports is a major impediment to the development of regional aviation. Without subsidies, regional airports struggle to subsist financially. This paper elucidates the various revenue and expenditure heads of Indian airports and discusses the financial status of regional airports. This study also uses panel data from 42 Indian regional airports from 2014–2015 to 2018–2019 to examine the effect of possible determinants on regional airport profits and revenue. Applying Hausman-Taylor regression, the findings indicate that regional airports can expand their profits and revenue primarily by increasing domestic and international passenger flow. Lower levels of seasonality contribute to the airport revenue. Airport capacity utilisation has a favourable and considerable impact on airport profits but not airport revenue. Civil enclaves were found to be profitable. Additionally, the research findings emphasise the unpredictable nature of low-cost carriers and provide managerial implications to policymakers and regional airport operators.

How can airports prepare for future public health disruptions? Experiences and lessons learned during the COVID-19 pandemic from a systemic perspective based on expert interviews

The COVID-19 pandemic proved to be an existential public health and economic crisis for the airport system. An interview study was conducted using Amsterdam Airport Schiphol as a use case to prepare for future public health disruptions. The study aimed to uncover key experiences and lessons learned by an airport system during the COVID-19 pandemic by interviewing 16 experts from airport operators, airlines, public health agencies, security services, and the government. After thematic analysis, four themes emerged. The first theme addressed the limited readiness of the airport system; the COVID-19 pandemic seemed unimaginable regardless of prior experiences with infectious diseases or weak signals. The second theme depicts an airport system running behind the facts, one that had difficulties implementing operational interventions and had to deal with extensive reorganisations. The third theme illustrated the complex relational dynamics within the airport system, such as the hesitancy of public health stakeholders towards aviation stakeholders and the government utilising a top-down approach. Finally, theme four provides lessons learned for the future whereby actively fostering a systemic approach, sensemaking capabilities, and informal relations are recommended. Current constructions like Crisis Management Teams and the Airport Operations Centre support these learnings. Further reflection and operationalisation of the study's findings are critical to proactively supporting the airport system's transition from a potential pandemic liability to a strategic asset in mitigating public health disruptions.