Large Airports Research Articles

Research and Analysis of Civil Airport Asphalt Concrete Pavement Damage Cause Evaluation and Countermeasure

Asphalt concrete pavement is characterized by convenient construction and maintenance, ride comfort, low noise, and strong adaptation and coordination deformation. Therefore, it has been gradually used in civil aviation transport airport runway, especially in recent years, the proportion of runways used in large hub airports has increased. However, asphalt concrete pavement also has many issues that is not conducive to the security of airport operation and management under the influence of traffic load, natural environment, and material performance. This paper analyzes and studies the causes and countermeasures of the damages through the investigation of several cases of asphalt concrete pavement damages in China, so as to provide reference for the extensive application and maintenance management of asphalt concrete pavement in airports in the future.

Characterization of delay propagation in the air traffic network

We build a delay propagation network based on Bayesian Network approach to study the complex phenomenon of delay propagation within a large network consisting of the 100 busiest airports in the United States. Through topological analysis and probability analysis, we investigate the characterization of delay propagation among airports and the impact of different types of airports on delay propagation. Results indicate that the cumulative degree distribution of the delay propagation network follows an exponential function and flight delays take at most one transhipment to go from each airport to any other airports on average. For each individual airport, the effects of delay propagation are associated with airports size (traffic flow), small airports are easily affected by other airports while large airports are more affecting downstream airports but fewer affected by upstream airports. Finally, we show how the number of affected airports changes as a function of the delayed airports based on different simulation strategies.

Long-Distance Airport Substitution and Air Market Leakage: Empirical Investigations in the U.S. Midwest

Following airline mergers and network reorganizations aimed at reducing operational costs, consolidated air services at large hub airports have encouraged air travelers to forego use of their smaller local airports to access large hub airports offering superior air services farther away. This study investigates airport leakage in areas of Wisconsin and Michigan served by small airports, where air travelers may leak to neighboring large hubs. Using a proximity-based service area definition, three airports experiencing leakage are identified, and a hierarchical logit airport choice model is applied that accounts for air service characteristics and access distance for travelers coming from these airports’ service areas. Results show that a similar mean number of flight legs at both the local and substitute (large hub) airports will encourage leakage at Dane County Regional and Gerald R. Ford International airports, indicating that adding direct flights alone will not be sufficient to combat leakage. Comparable access distances to local and substitute airports have opposite effects on the local markets of Gerald R. Ford International and Milwaukee Mitchell International airports—promoting leakage at the former but discouraging it at the latter. Furthermore, proportional increases in airfares at local airports lead to uneven losses of markets in investigated service areas. Overall, the study provides empirical evidence of long-distance airport leakage in parts of the U.S. Midwest, and how its implications can be used by small airports seeking to further understand and respond to travelers’ airport choices within their local markets.

Influence of Passenger Comfort Requirements on the Interior Layout of Long-Haul Aircraft

The plane has become a convenient method of transportation. The main idea of aviation in the 21st century is the safety of passengers and crew, but the human is always inclined towards comfort. The structural and parametric analysis of the long-haul aircraft development made it possible to form the concept of the fuselage layout with capsule accommodation of passengers. By adding the third axis to the dimension of the aircraft expressed in take-off mass, it clearly showed the ultimate dimension of the aircraft, expressed by modern infrastructural constraints. The histogram of the distribution of flights between the largest airports in the world that can operate with long-haul aircraft was showed. The distribution of large airports was characterised by the demographic factor. The proposed variant of the capsule accommodation, designed for the Boeing 777-200LR, can be installed in other passenger airliners with a ceiling height of at least 2.1 m. Analysis of alternative options for the layout of the passenger compartment allows us to state: with a flight range of more than 8 hours, the flight is comfortable only in business or first classes. The proposed two-story capsule placement allows providing the layout with first-class seats in a given cabin.

Surveillance of SARS-CoV-2 in Frankfurt am Main from October to December 2020 Reveals High Viral Diversity Including Spike Mutation N501Y in B.1.1.70 and B.1.1.7.

Background: International travel is a major driver of the introduction and spread of SARS-CoV-2. Aim: To investigate SARS-CoV-2 genetic diversity in the region of a major transport hub in Germany, we characterized the viral sequence diversity of the SARS-CoV-2 variants circulating in Frankfurt am Main, the city with the largest airport in Germany, from the end of October to the end of December 2020. Methods: In total, we recovered 136 SARS-CoV-2 genomes from nasopharyngeal swab samples. We isolated 104 isolates that were grown in cell culture and RNA from the recovered viruses and subjected them to full-genome sequence analysis. In addition, 32 nasopharyngeal swab samples were directly sequenced. Results and conclusion: We found 28 different lineages of SARS-CoV-2 circulating during the study period, including the variant of concern B.1.1.7 (Δ69/70, N501Y). Six of the lineages had not previously been observed in Germany. We detected the spike protein (S) deletion Δ69/Δ70 in 15% of all sequences, a four base pair (bp) deletion (in 2.9% of sequences) and a single bp deletion (in 0.7% of sequences) in ORF3a, leading to ORF3a truncations. In four sequences (2.9%), an amino acid deletion at position 210 in S was identified. In a single sample (0.7%), both a 9 bp deletion in ORF1ab and a 7 bp deletion in ORF7a were identified. One sequence in lineage B.1.1.70 had an N501Y substitution while lacking the Δ69/70 in S. The high diversity of sequences observed over two months in Frankfurt am Main highlights the persisting need for continuous SARS-CoV-2 surveillance using full-genome sequencing, particularly in cities with international airport connections.

Traffic congestion mechanism in mega-airport surface

In this paper, guided by macroscopic cell transmission models, a cell transmission model of aircraft traffic flow on runways, taxiways and aprons was established to deduce and analyze the evolution rules of an airport surface traffic. The model was simulated by adopting data from a large domestic airport in China. The relationship between three parameters of traffic flow on taxiways was evaluated, and the airport surface traffic flow characteristics were analyzed. Moreover, this paper macroscopically analyzed the characteristics of spatial–temporal distribution of airport surface recurrent and non-recurrent traffic congestion. Simulation results showed that arrival rates and pushback rates had significant influence on the formation and dissipation of recurrent traffic congestion in different phases of the surface aircraft traffic flow. When the arrival rate was 0.3 aircraft/minute and the pushback rate was 0.23 aircraft/minute, the speed of aircraft on taxiways was high, the density and flow were large, and the aircraft had a high degree of obstacle-free taxiing. At this time, the airport ran smoothly and the surface network operation efficiency was high. Compared with the arrival rate, the outward expansion trend of each parameter was more obvious when the pushback rate changed. Parallel taxiways are less robust than apron taxiways and connect taxiways.

Private Markets, Infrastructure and Venture Capital in the Post-COVID Era: The Pension Perspective

This second of a series of seven papers co-authored by M. Nicolas J. Firzli and David Weeks looks at the notions of private markets – PE, VC, private debt and infrastructure – and the "quest for yields" in a low interest rates environment, which where discussed at two recent global conferences organised by the G7 Pensions Summit (G7 P7) and the Singapore Economic Forum (SEF). ESG, impact investing, renewable energy and the notion of green growth are also discussed by the co-authors and other experts, including the Hon. Nick Sherry, fmr. AUS minister of Superannuation & Corporate Law, Nick Silver, chairman, Climate Bonds Initiative (CBI), Michael Dennis, Head, APAC, Alternatives & Cap. Markets, BlackRock, Dr Guan Seng Khoo, Singapore Management University (SMU) and Ingrid Edmund, Columbia Threadneedle Investments (CTI)The notion of financial long-term-ism is considered from the perspective of institutional asset owners, notably in the US, Britain and the European Union (EU), where "pension fund regulation and the structure of the industry [often] puts a premium on liquidity and causes short-termism, at the expense of long-term investment and patient capital.”Australia has seen much interest in privatisation of public functions/assets. This has increased opportunities for private investment in infrastructure. It has, however, raised political discussion about the correct pricing of “monopoly assets”, such as large regional airports and water utilities.The authors also look at some of the recent developments in Canada, China, India and various ASEAN jurisdictions, including Singapore and assess the role played by the city-state in a complex period: "the COVID crisis has accelerated the mutually reinforcing effects of the Age of Empowerment (ESG, Equity and Entrepreneurship/the Venture Capitalist Ethos), the Age of Geoeconomics (intensifying Sino-American coopetition) and Datafied World Economy (Digitalization, Ai, Cybernetics), and Singapore is positioned precisely at the crossroads where these three powerful currents meet.”Some of the financial and geo-economic aspects of the "Post Brexit" era are also analysed. The authors note that HM Government has invited four key maritime powers to join the 47th G7 summit held in Carbis Bay, Cornwall later in the year: Australia, South Korea, India and South Africa, thus "bringing the blue economy to the fore of the global policy agenda".

Перспективы развития международного аэропорта имени Нурсултана Назарбаева (г. Нур-Султан, Республика Казахстан) в качестве пассажирского транзитного хаба авиакомпании «Air Astana»

Цель: целью проводимого исследования является представление модели развития аэропорта имени Нурсултана Назарбаева (г. Нур- Султан, Республика Казахстан) в качестве пассажирского транзитного хаба авиакомпании «Air Astana». Обсуждение: на основании данных пассажиропотока аэропорта г. Нур–Султан за период с 2004 по 2019 г. было установлено, что пассажиропоток вырос более чем в 10 раз (с 500 тыс. до 5 млн пассажиров), в то время как крупнейший аэропорт Республики Казахстан, аэропорт г. Алматы продемонстрировал рост пассажиропотока более чем в 4 раза за аналогичный период (с 1,5 млн до 6,4 млн пассажиров). В период с 2014 по 2016 г. была проведена комплексная модернизация аэропорта имени Нурсултана Назарбаева, допустимая пропускная способность аэропорта возросла до 8,2 млн пассажиров в год. Аэропорт расширяет сотрудничество с национальными и зарубежными авиакомпаниями, открывая новые внутренние и международные направления. Рынок авиаперевозок Республики Казахстан демонстрирует высокие показатели роста. Результаты: результатом проводимого исследования является построение модели развития направлений маршрутной сети авиакомпании «Air Astana» на базе аэропорта имени Нурсултана Назарбаева. На основании анализа действующей внутренней и международной маршрутной сети национальных и зарубежных авиакомпаний была представлена модель перспективного развития международных направлений. Авиакомпания «Air Astana» осуществляет расширение и обновление парка воздушных судов, приобретая узко- и широкофюзеляжные лайнеры, способные выполнять перелеты на расстоянии от 6000 до 12000 км. Построение пассажирского транзитного хаба на базе аэропорта имени Нурсултана Назарбаева позволит авиакомпании «Air Astana» увеличить пассажиропоток и стать ведущей авиакомпанией региона, выполняющей регулярные авиарейсы по европейским и азиатским направлениям.

Post and Cargo Monopoly Practices by Airport Management (Case Study of Hasanudin Airport dan Kualanamu Airport)

The continued development of the world economy with increasing competition in various businesses including the aviation business. Indonesia's own aviation business where management is centralized which is given to PT Angkasa Pura I and II as companies that manage large airports throughout Indonesia. The airport management rights were later misused by PT Angkasa Pura I and II to conduct monopolistic practices. Based on the decisions of the Commission, both companies should be excluded from the application of the Competition Law, proved to have committed abuse of monopoly power by creating barriers to entry for other business actors. And the activities carried out by the airport management in the process of cargo and mail at airports not included exceptions contained in the Act. No. 5 of 1999 regarding monopolistic practices and unfair business competition because of what was done by the airport management have broad impact to the national economy due pentetapan too high a rate which causes the price of goods that dikirimakan through cargo and mail also increased, as well as their indekasi monopolistic practices such as other businesses can not carry on business without government approval of airport and PT. Angkasa Pura I and II

A Simulation Platform for Airport Runway Collision Warning System

The increasing passenger throughput makes the large-scale aviation hub being unable to bear the burden gradually. Flight delays caused by cannot fly through the ATC tower in time are becoming more and more common, which makes airlines have to face the problem of passenger loss. Meanwhile, runway intrusion incidents caused by the high load operation of the airport also occur frequently. Once there is a collision, airlines will suffer huge economic losses. In order to avoid runway intrusion, improve air transport efficiency and reduce airline losses, runway collision avoidance system emerges as the times require. Based on the real airport map geographic coordinate data, this paper draws the airport dynamic map in the on-board moving map for the pilot, defines several kinds of runway intrusion scenarios, and introduces 3D real-time visual display into the platform in order to build a complete set of simulation verification platform for airport runway collision avoidance system. The research results of this paper can be used to verify the optimization algorithm of runway collision avoidance system and the test of airport dynamic map in the future, which is of great significance to improve the traffic condition of large airports in the future.

Analysis to energy consumption characteristics and influencing factors of terminal building based on airport operating data

Airport terminals have much higher average energy consumptions than normal public buildings. This is caused by their complicated space features and operation characteristics. In China, large modern airports were built from around 2004, which means our understanding to the real energy performance of these buildings lag behind the design practice and with feedback from operation experience, both design or operation of modern airports shall be improved in terms of energy efficiency. Nanning Airport provided an excellent example for that purpose, with comprehensive operation data collected during 2016–2019. The data were firstly presented in this paper, followed by clustering and correlation analysis to establish the correlation among potential factors. From the analysis, the major factors influencing energy consumption were identified as passenger flow, meteorological parameters and supply fan frequency. Regression analysis was performed based on monthly data and equations were provided for the calculation of the terminal total energy consumption and its three sub components according to the input parameters of passenger flow data and meteorological data. These equations provide guidance on energy supply for the operation of this airport and more importantly can be used as valuable reference when designing airports in similar conditions.

Modeling airport congestion contagion by heterogeneous SIS epidemic spreading on airline networks.

In this work, we explore the possibility of using a heterogeneous Susceptible- Infected-Susceptible SIS spreading process on an airline network to model airport congestion contagion with the objective to reproduce airport vulnerability. We derive the vulnerability of each airport from the US Airport Network data as the congestion probability of each airport. In order to capture diverse flight features between airports, e.g. frequency and duration, we construct three types of airline networks. The infection rate of each link in the SIS spreading process is proportional to its corresponding weight in the underlying airline network constructed. The recovery rate of each node is also heterogeneous, dependent on its node strength in the underlying airline network, which is the total weight of the links incident to the node. Such heterogeneous recovery rate is motivated by the fact that large airports may recover fast from congestion due to their well-equipped infrastructures. The nodal infection probability in the meta-stable state is used as a prediction of the vulnerability of the corresponding airport. We illustrate that our model could reproduce the distribution of nodal vulnerability and rank the airports in vulnerability evidently better than the SIS model whose recovery rate is homogeneous. The vulnerability is the largest at airports whose strength in the airline network is neither too large nor too small. This phenomenon can be captured by our heterogeneous model, but not the homogeneous model where a node with a larger strength has a higher infection probability. This explains partially the out-performance of the heterogeneous model. This proposed congestion contagion model may shed lights on the development of strategies to identify vulnerable airports and to mitigate global congestion by e.g. congestion reduction at selected airports.

Reduced Order Modeling Methods for Aviation Noise Estimation

A key enabler for sustainable growth of aviation is the mitigation of adverse environmental effects. One area of concern is community noise exposure at large hub airports serving growing population centers. Traditionally, community noise exposure is computed using noise contours around airports, which requires knowledge of a large dataset pertaining to the air traffic operations at the airport of interest. Due to the underlying variability in real-world aircraft operations, numerous assumptions need to be made which adversely affect the accuracy of the model. Reduced-Order Modeling (ROM) methods provide a new framework for the retention of a large number of these parameters, thus improving model speed and accuracy. In this work, a proper orthogonal decomposition in conjunction with a response surface methodology-based surrogate model is used to create a rapid noise assessment model. Validation is performed against results obtained from the aviation environmental design tool with quantitative error metrics and visual contour comparisons. Obtained results are encouraging and motivate further work in this area with other ROM methods. ROM based models for noise assessment expand the solution space for noise mitigation strategies which can be evaluated, and therefore can lead to novel solutions which cannot be found with traditional modeling methods.

A Novel Aircraft Refueling Behavior Detection Model based on Deep Learning

How to efficiently and accurately monitor the sparse aircraft Refueling behaviors from a large amount of video streams is of great significant for improving the level of management and refueling efficiency of aviation fuel stations. Due to the COVID-19 virus epidemic, the number of flights has dropped severely, the collection of image samples for refueling behaviors from large airport becomes difficult, which hinders the real-time detection of Refueling behaviors and reduces the efficiency of aviation fuel station. Therefore, automatically detecting the refueling behaviors of each station in time and accurately from a large number of aviation refuel stations still keeps challenging. To address this challenge, we propose a novel aircraft refueling behavior detection model based on deep learning, to quickly and accurately determine the refueling behaviors through analysing the video stream collected from the massive cameras deployed in the airport. Our proposed model adopts Inception v3 architecture of ImageNet to realize the model capability of transfer learning, the data augmentation to address the issue of overfitting, and the mAP (mean Average Precision) to test the performance. Our proposed model is also applied in the detection of refueling behaviors in China National Aviation Fuel Group, LTD (CNAF). The practical application results show better performance than other existing methods. Our work will promote the updating of related industry standard.

Position Report Enhancement Using Bayesian Estimator

In this article, a Bayesian estimator for a target position report is proposed. It is based on a maximum a priori algorithm, where the user's device knowledge about its location is used to deduce the prior probability density function. The algorithm does not require knowledge about the signal and noise levels, meaning, noninformative priors are used. It is well known that with a higher number of antenna elements in an array, narrower beams can be formed. In beamforming, task narrow beams are useful for serving many users simultaneously, whereas in direction-of-arrival (DOA) estimation, we are not interested in narrow beams as such; instead, estimation accuracy is important. So, reducing the number of antenna elements used for DOA estimation is beneficial from a system complexity point of view. In this article, signal source location report is used to enhance the estimated DOA, for the task, MAP estimator is developed. We will show that in the case of small array size and large array covariance matrix error values, the proposed estimator is the only one capable of improving the prior knowledge about the transmitter when comparing it with other popular algorithms, such as the maximum likelihood estimator and Root MUSIC. The algorithm could be used in a variety of different scenarios, but its advantages emerge in the case of complex signal propagation environments, such as urban canyons and large airports.

The Baggage Belt Assignment Problem

We consider the problem of assigning flights to baggage belts in the baggage reclaim area of an airport. The problem is originated by a real-life application in Copenhagen airport. The objective is to construct a robust schedule taking passenger and airline preferences into account. We consider a number of business and fairness constraints, avoiding congestion, and ensuring a good passenger flow. Robustness of the solutions is achieved by matching the delivery time with the expected arrival time of passengers, and by adding sufficient buffer time between two flights scheduled on the same belt. We denote this problem as the Baggage Belt Assignment Problem (BBAP). We first derive a general Integer Linear Programming (ILP) formulation for the problem. Then, we propose a Branch-and-Price (B&P) algorithm based on a reformulation of the ILP model tackled by Column Generation. Our approach relies on an effective dynamic programming algorithm for handling the pricing problems. We tested the proposed algorithm on a set of real-life data from Copenhagen airport as well as on a set of instances inspired by the real data. Our B&P scheme outperforms a commercial solver launched on the ILP formulation of the problem and is effective in delivering high quality solutions in limited computational times, making it possible to use the solution approach in daily operations in medium-sized and large airports. • We present a new formulation of the Baggage Belt Assignment Problem. • Model matches the arrival time of bags with the expected arrival time of passengers. • Exact solution algorithm is presented based on Branch-and-Price. • Pricing problem is solved efficiently by use of dynamic programming. • Computational results on real-life and synthetic data are presented.

Planepooling and Air Taxis for Post-COVID Aviation

For most of its history, commercial aviation has tended toward large airplanes, large airports, and rigidly scheduled flights. Now, however, two phenomena—technological innovation and long-term societal changes accelerated by the COVID-19 pandemic—are creating an environment in which many flight routes would be better served by “planepooling”: smaller planes, smaller airports, and, for some routes, ad hoc scheduling. We highlight social and technological changes—including COVID-19 prevention measures, electrification of aircraft, and autonomous planes and air taxis—that could make private regional aviation attractive and affordable for business travelers and the middle class. Making planepooling convenient and cost-effective will require some technological advances and some changes in public policy. We propose in particular that regulators consider more-flexible Essential Air Service grants to small airports and the development of a market for regional aviation aerial corridors.

Tactical Runway Scheduling for Demand and Delay Management

Airports are limited in terms of capacity. Particularly, runways can only accommodate a certain number of movements (arrivals and departures) while ensuring safety and determined operational requirements. In such a constrained operating environment, any reduction in system capacity results in major delays with significant costs for airlines and passengers. Therefore, the efficient operation of airports is a critical cornerstone for demand and delay management of the whole air transportation system. Runway scheduling deals with the sequencing of arriving and departing aircraft at airports such that a predefined objective is optimized subject to several operational constraints, like the dependency of separation on the leading and trailing aircraft type or the runway occupancy time. Scheduling arrivals and departures at runways is a complex problem that needs to address diverse and often competing considerations among involved flights. In the context of the Airport Collaborative Decision Making (A-CDM) programme, airport operators and air navigation service providers require arrival and departure management tools that improve aircraft flows at airports. Airport runway optimization, as the main element that combines airside and groundside operations, is an ongoing challenge for air traffic management. By considering real airport performance data with scheduled and actual movements, as well as arrival/departure delays, we present a robust model together with an optimization algorithm, which incorporates the knowledge of uncertainty into the tactical operational step. Our model has been validated with real data from a large international European airport in different traffic scenarios. Results are compared to the actual sequencing of flights and show that the algorithm can significantly contribute to the reduction of delay, while adhering as much as possible to the operative procedures and constraints, and to the objectives of the airport stakeholders. Computational experiments performed on the case study illustrate the benefits of this arrival/departure integrated approach.

Sizing of a Photovoltaic Installation for the Needs of an International Airport: Case Study of GNASSINGBE EYADEMA International Airport (AIGE)

This paper presents the sizing of a photovoltaic (PV) system for the GNASSINGBE EYADEMA international airport. Technical and economic profitability studies were done in order to show the possibility and the relevance of using a PV installation to fully meet the energy needs of a large airport in a certain and profitable way, thus contributing to encourage airports to go for this form of energy in the perspective to reduce their environmental effects. In view of the load profile and because of operating constraints, it was proposed to design a grid-connected photovoltaic systems in self-consumption. Mathematical formulas and PVsyst software were used for the sizing. The results obtained showed that the sizing system has a peak power of 1 MWp. The total investment cost of the project was estimated at $2,100,000. To evaluate the profitability of the project, the analysis was made according to two cases first if the project is financed with own funds and second if it is financed through a bank loan. It appeared that for funding own, the return on investment time is shorter, unlike when resorting to a bank. In addition, this PV power plant project would help to avoid 401.3 tonnes of CO₂/year.

Modeling and Simulation of Departure Passenger’s Behavior Based on an Improved Social Force Approach: A Case Study on an Airport Terminal in China

The unprecedented growth of passenger throughput in large airport terminals highlights the importance of analyzing passengers’ movement to achieve airport terminal’s elaborate management. Based on the theory of original social force model, video data from a departure hall of a large airport terminal in China were analyzed to summarize passengers’ path planning characteristics. Then, a double‐level model was established to describe passengers’ path planning behaviors. At the decision level of the proposed model, the avoiding force model including common avoiding force and additional horizontal avoiding force was established on the basis of setting time and space limitations for taking avoiding action and was used to describe passengers’ path planning in close‐range space. At the tactical level of the proposed model, the route and node choice models were established to describe passengers’ path planning in long‐range space. In the route choice model, a distribution of intermediate destination areas was proposed, with detouring distance, pedestrian density, speed difference, and pedestrian distribution considered in choosing an intermediate destination area. In the node choice model, the walking distance, the quantity of people waiting, and luggage were considered in choosing a check‐in counter or security check channel. The main parameters of the proposed model were confirmed according to video data. Simulation results show that the proposed model can simulate departure passengers’ path planning behaviors at an acceptable accuracy level.