Airport System Research Articles

Multi-Airport System Development Model: Case Study of Airports in Indonesia

Indonesia's air transportation business has grown substantially to suit the community's transportation needs. An increasing number of people travel by airline each year. By way of secondary and tertiary multiplier effects, the intensifying competition between airport services provided in neighboring regions is likely to have a multiplier influence on a territory. Simultaneously, airport services that are more competitive are focused on areas with rising economic growth in sectors like tourism. MAS is an airport system consisting of at least two airports within a metropolitan area that support civil aviation. MAS includes both big and small airports. MAS is the development of an air transportation system to suit the growing demand for air transportation services. As an example of an integrated multi-model airport design in Indonesia, this research will examine Juanda International Airport, Surabaya, as the major airport and Abdul Rachman Saleh Airport as the secondary airport. In order to establish an integrated multi-modal airport in Indonesia, it is necessary to adopt a multi-airport system. This study's airport location is in East Java Province and includes two airports: Juanda International Airport and Abdul Rachman Saleh Airport. The Juanda International Airport is situated in Sedati, Sidoarjo, whilst the Abdul Rachman Saleh Airport is in Pakis, Malang Regency. Using modelling findings and final passenger statistics, airport capacity in 2045 is determined. The results demonstrated the necessity for more comprehensive points in the MADAM simulation used in this research study, which can estimate a number of crucial parameters. Doi: 10.28991/CEJ-SP2021-07-013 Full Text: PDF

The Evolution of Canada’s Airports and Airport Policy: A Review

Canada’s airports are unique in the world as a system of private, no-share capital, not-for-profit organizations. This paper reviews the evolution Canada’s airport system and airport policy over the last 30 years and provides an overview of airport performance including an assessment of the likely proceeds should the Canadian government decide to sell its eight largest airports to private investors. The review reveals an airport system with a heavy “user pay” orientation that has become reliant on “airport improvement fees” charged to passengers, over and above regular aeronautical charges, in order to finance the substantial investments in infrastructure made by airport authorities. The paper highlights criticisms of the current airport system that have endured for over 20 years and shows how recent recommendations to sell our airports to private investors reveals an underlying tension regarding whether airports should be regarded as “spark plugs” that create wider economic benefits or “toll booths” that generate government revenues. The paper argues that a viable alternative to selling off airports to private investors is to reintroduce legislation first introduced in 2003 and again in 2006, which, despite broad political support, never became law.

Looking into the Crystal Ball—How Automated Fast-Time Simulation Can Support Probabilistic Airport Management Decisions

Airport management plays a key role in the air traffic system. Introducing resources at the right time can minimize the effects of disruptions, reduce delays, and save costs as well as optimize the carbon footprint of the airport. Efficient decision-making is a challenge due to the uncertainty of the upcoming events and the results of the applied countermeasures. So-called ‘what-if’ systems are under research to support the decision-makers. These systems consist of a user interface, a case management system, and a prediction engine. Within this paper, we evaluate different types of prediction engines (flow, event, and motion models) that can be used for airport management what-if systems by comparing them in terms of accuracy and calculation speed. Hence, two different operational situations are examined to evaluate the performance of the prediction engines. The comparison shows that accuracy and calculation speed are opposed. The flow model has the lowest accuracy but the shortest calculation time and the motion model has the highest accuracy but the longest calculation time. The event model lies between the other two models. The acceptable accuracy of a prediction tool is strongly dependent on the respective airport, whereas the calculation time is strongly dependent on the available decision time. Regarding airport management, this means that the selection of a prediction engine has to be made in dependence of the airport and the decision processes. The results show the advantages and disadvantages of each prediction engine and provide a first quantification by which a selection for what-if systems can happen.

What Determines the Behavior of a System and How to Design a Satisfactory System for an Expected Behavior

Systems are everywhere around us, such as products, production lines, the Internet, companies, schools, hospitals, airports, communities, cities, countries, governments, and military forces. System researchers and engineers always strive to achieve their desired system behaviors. Thus, this paper aims to solve two fundamental problems of systems engineering: what determines the behavior of a system and how to design a satisfactory system for the expected behavior. First, we determine the dimensions of a relationship flow, such as information flow, material flow, and capital flow. Second, we develop new theorems and propositions to solve the first problem. For example, they show that, for a given behavior of a system, if the dominant subsystem of the behavior has the basic level for the behavior, the behavior is only determined by its input flow and relationship flows at or above the basic level, all of which are collectively referred to as total relationship flow (TRF). Third, we develop a relationship flow diagram which is of great significance to system design, just as a circuit diagram to circuit design, and a TRF-oriented system design framework to solve the second problem. In order to show how the framework works, we apply it step by step to the schematic design of an airport system for the required passenger departure procedure service behavior, and get a system example; using this framework to design a system will greatly simplify the complexity of development and improve the maintainability of the system. Therefore, our findings provide a new theory for systems engineering and improve its methods and tools systematically.

Estimation of Atmospheric Gusts Using Integrated On-Board Systems of a Jet Transport Airplane—Flight Simulations

Currently, quite accurate measurements of atmospheric gusts are carried out by airport systems only in the vicinity of the runways. There is a still open issue of availability of information about real wind gusts at cruising altitudes and during approach at a considerable distance from the airfield. Standard on-board systems of a jet transport airplane provide some information which is desirable to have knowledge of how flight parameters reflect real gust parameters and their impact on the aircraft dynamics. The paper proposes an algorithm for headwind gust magnitude estimation in relation to aircraft response. The analysed estimation algorithms assume the use of data available from the existing on-board systems only without the employment of any extra sensors or ground and satellite systems. In this way, many problems caused by different structures, configurations, and ways of installation of additional sensors and structural changes are rejected. The algorithms use the classical method for estimation of wind parameters as well as a linear longitudinal model of aircraft dynamics, taking into account the influence of wind gusts. Data fusion was realised with the use of three filtration methods. Results were evaluated to select the most accurate method of the estimation. Test data were obtained from advanced flight simulation. The experimental scenario considered a flight of a passenger twin-engine jet airplane through a layer of programmed gusts. The results of the flight simulations allowed us to determine the accuracy of the proposed gust estimation algorithms in reference to the ideal wind-speed data analysis obtained directly from the simulation environment (with the accuracy of the simulation process). The use of the proposed gust estimation algorithms may provide more accurate signal for integrated on-board systems, especially for wind shear detection and sped-up response time of flight control systems, protecting aircrafts against the adverse impact of encountered wind shear or gusts, e.g., auto-thrust or auto-throttle systems. The dedicated algorithm presented in the paper may increase the safety level of take-off and approach phases in gusty conditions and also during significant changes in wind speed at cruising altitudes in the case of crossing the area of jet stream occurrence.

Developing a Cost-Effective Assessment Method for Noise Impacts at Non-Towered Airports: A Case Study at Purdue University

Aircraft noise is considered as one of the environmental impacts that most adversely affects airport development. Aircraft noise estimation tools such as the Aviation Environmental Design Tool (AEDT) are widely used by airports to mitigate local concerns for airport development. Aircraft operations and fleet mix information play important roles in aircraft performance modeling for noise prediction. However, such information is difficult to obtain at almost 85% of the 3,348 National Plan of Integrated Airport Systems (NPIAS) airports, which lack full-time air traffic control facilities and personnel. Given the increasing percentage of equipped automatic dependent surveillance-broadcast (ADS-B) aircraft in the U.S. national airspace, this paper presents a cost-effective noise estimation approach for non-towered general aviation (GA) airports. Instead of deploying physical sound meters or relying on the local air traffic control facilities, the authors collected aircraft positional data and fleet mix information based on ADS-B broadcasts. Advanced aircraft performance model parameters are constructed using four-dimensional aircraft position and a kinematic point-mass model. Aircraft-specific noise levels are interpolated based on the EUROCONTROL Aircraft Noise and Performance (ANP) database. To obtain the final noise level, two adjustments are applied to the interpolated noise values. The test results show the proposed approach can help non-towered airports predict the noise impact on any selected locations near the airport cost-effectively. Recommendations and opportunities for future investigation are also included.

Things-Net

The Internet of things aims to create a continuity between real and digital worlds, by integrating physical objects into the digital universe. This will increase the number of connected machines and generate new applications. When combined according to an appropriate logic, IoT objects can produce value-added services that a single object cannot provide. In order to avoid costly errors, this execution logic has to be modeled and validated, using a formal model, before its effective deployment. To address the lack of special-purpose modeling languages for IoT applications, the authors propose the Things-Net model, designed specifically to meet the needs of IoT-based systems. It allows an easy modeling and verification of IoT time-dependent platforms, to ensure that the designed IoT solution fulfills the application's requirements. In order to illustrate the approach, authors apply the modeling and verification techniques to a prototype of an airport management system based on IoT.

Adaptive information management system of dynamic monitoring of actual water content in jet fuel in technological processes of aviation fuel supply

Modern domestic and international standards, regulators of the aviation fuel industry, considering the negative impact of the presence of mechanical impurities and water in aviation fuel on the performance and life cycle of aircraft engines, fuel metering equipment, fuel systems of aircraft (A/C), as a threat factor for flight safety, impose high requirements for the purity of aviation fuel while operating aeronautical equipment. At the same time, the causes and sources of water content in jet fuel are a source of economic losses, the most important criterion for the success of the Aerodrome Fueling Complex business. The article considers the task of developing reliable and automated methods as well as technologies for controlling these contaminants, for example for determining water content in aviation fuel when refueling aircraft, and the necessity to minimize an effect of a human factor. The automation of aviation fuel quality monitoring processes, the transition from discrete control methods to continuous ones, from static control methods to dynamic ones (in-line), from indirect methods to direct ones are becoming relevant. The possibilities of end-to-end accounting and analysis of aviation fuel purity parameters at all stages of the aviation fuel life cycle are shown. The article considers the methods and conducts the analysis of known techniques and devices used to determine, measure and indicate actual water content, presence of dissolved, free and total water in jet fuel. The technical solution of continuous automated control of the actual water content level of the jet fuel flow in the processes of aviation fuel supply and aircraft refueling in an information system that provides on-line monitoring and dynamic measurement of the quantitative content of dissolved and free water in the jet fuel flow, is presented. The technical solution for the continuous determination of the quantitative water content in the jet fuel stream is proposed. At the same time, the solution of the problem of monitoring water content in jet fuel is combined with the technological process to control the purification of jet fuel from water. The paper represents an adaptive information management system for continuous monitoring of the water content level of the jet fuel flow, which will allow specialist to substantially increase a level of automatization of aircraft aviation fuel supply technological processes, decrease a negative impact of a human factor, increase economic effectiveness of the aviation fuel supply complex. The system is designed to carry out continuous, automated control (monitoring) of water content in the jet fuel flow at all the stages of the jet fuel movement: receiving, storing and delivering jet fuel and refueling aircraft, in particular fuel and lubricants warehouses (fuel and lubricants), refueling complexes and pre-apron filling points. It can also be used in the fuel system of the aircraft, as a system to prevent water content in the jet fuel. The integration of automation tools will enable us to improve the quality of management of aviation fuel supply and aircraft refueling to ensure timely operational decision based on real data in real time mode, provided the proposed system integration into the airport system for operational data exchange.

A Strategy-Based Formal Approach for Fog Systems Analysis

Fog systems are a new emergent technology having a wide range of architectures and pronounced needs making their design complex. Consequently, the design of fog systems is crucial, including service portability and interoperability between the various elements of a system being the most essential aspects of fog computing. This article presents a fog system cross-layer architecture as a first step of such a design to provide a graphical and conceptual description. Then, a BiAgents* (Bigraphical Agents) formal model is defined to provide a rigorous description of physical, virtual, and behavioural aspects of Fog systems. Besides, this formalisation is implemented and executed under a Maude strategy system. The proposed approach is illustrated through a case study: an airport terminal Luggage Inspection System (LIS) while checking the correctness of its relevant properties: the portability of data and their interoperability. The integration of the Maude strategies in the rewriting of Fog system states made it possible to guide the execution of the model and its analysis.

A novel design of a smart interactive guiding robot for busy airports

Abstract The COVID-19 pandemic has had a massive impact on the global aviation industry. As a result, the airline industry has been forced to embrace new technologies and procedures in order to provide a more secure and bio-safe travel. Currently, the role of smart technology in airport systems has expanded significantly as a result of the contemporary Industry 4.0 context. The article presents a novel construction of an intelligent mobile robot system to guide passengers to take the plane at the departure terminals at busy airports. The robot provides instructions to the customer through the interaction between the robot and the customer utilizing voice communications. The usage of the Google Cloud Speech-to-Text API combined with technical machine learning to analyze and understand the customer's requirements are deployed. In addition, we use a face detection technique based on Multi-task Cascaded Convolutional Networks (MTCNN) to predict the distance between the robot and passengers to perform the function. The robot can guide passengers to desired areas in the terminal. The results and evaluation of the implementation process are also mentioned in the article and show promise.

Air passenger demand forecast through the use of Artificial Neural Network algorithms

Airport planning depends to a large extent on the levels of activity that are anticipated. To plan the facilities and infrastructures of an airport system and to be able to satisfy future needs, it is essential to predict the level and distribution of demand. This document presents a short- and medium-term forecast of the demand for air passengers carried out through a specific case study (Colombia), in which the impact of the pandemic period due to COVID-19 on air traffic was taken into account. To make the forecast, an algorithm that implements techniques based on Artificial Neural Networks (ANN) (Machine Learning (ML)) was developed. In particular, for the analysis of the available time series, techniques of encoder-decoder networks of the type ConvLSTM2D have been applied. These architectures are a hybrid between Convolutional Neural Networks (CNN), very useful for the extraction of invariant patterns in their spatial position, and Recurrent Neural Networks (RNN), appropriate for the extraction of patterns within their temporal context (time series). The most relevant result of the present research is that the recovery in demand (volume and trend) to the levels reported before the pandemic is forecast for the period between the end of 2022 and the beginning of 2024 (depending on the type of traffic and scenario considered). Finally, the application of the forecasting model based on Machine Learning/Deep Learning (DL) presents, as a metric performance, a Mean Absolute Percentage Error (MAPE) value from 3% to 9% (depending on the scenario), which enables predictions of relative precision and introduces a new alternative technical approach to develop reliable air traffic forecasts, at least in the short and medium term.

ДЕФОРМАЦИЯ ИЕРАРХИИ КРУПНЕЙШИХ АЭРОПОРТОВ МИРА И ЕВРОПЫ В УСЛОВИЯХ ПАНДЕМИИ COVID-19

The passenger turnover of almost all airports fell sharply from 30% to 90% in COVID-19 pandemic - most of all in those where the share of international passengers dominated, less - where domestic traffic prevailed. Changes in the rank of the hierarchy of the 60 largest airports in the world and 60 airports in Europe, caused by the consequences of the COVID-19 pandemic, are analyzed. A special technique has been developed for assessing the stability and variability of such a hierarchy. The values of three indicators of variability of the hierarchy of airports are compared in the pre-covid and in the first phase of the covid period. The level of internal instability in the global aviation system increased from 82 to 98%, in Europe – from 62 to 93%. The degree of rank lability of airports in the world has increased 8.8 times, in Europe – 4.5 times. The hierarchy of world and European air transport systems turned out to be relatively stable in the pre-covid era. In a pandemic, it has become deformed and very unstable. Its main deformers were airports in those countries where flight restrictions were lifted much earlier than in the rest of the world, as well as the new ones opened. Empirically, 5 types of variability in the hierarchy of airport systems have been identified: a very unstable hierarchy. The larger the territorial size of the airport system, the more changeable and unstable its hierarchical structure. Systems that are very large in terms of territorial size are more vulnerable to external influences (pandemics) than large or medium-sized ones, which is manifested in the degree of variability of their hierarchical structures.

Managing a multiple-gateway airport system with super high-speed rail

In this study, we analyzed the airport choice behavior of inbound Chinese travelers to Japan. We determined the effect of launching super high-speed rail (SHSR) on air-rail integration and its effect on the gateway functions of airports connected by high-speed rail or SHSR. We developed a bi-level model adopting nested-type stochastic user equilibrium using a capacity constraints model. Based on simulations, we concluded that (i) introducing SHSR can reduce the congestion at the primary gateway airport; (ii) direct connection with SHSR can enhance the gateway function of secondary gateway airports; (iii) when a low-cost carrier is operating in the market, the gateway function at secondary airports without SHSR may be diminished by the introduction of SHSR.

The enlightenment of the cost control of regional tourism airports: Taking Airport A as an example

<p>Since the reform and opening up, the civil aviation industry has accelerated its pace of development and achieved world renowned achievements. It has been the world’s second largest civil aviation transportation market for many years. With the rapid development of the civil aviation industry, the construction of transportation airports has always maintained a rapid development trend, the number of airports and business volumes continue to increase, and the annual passenger throughput has basically maintained a double-digit rapid growth. However, at present, the popularity of China’s aviation market is not high, the situation of insufficient capacity of regional airports and large losses has not changed, and a balanced and coordinated development of the airport system has not really taken shape. If China is to move from a major aviation country to an aviation power, it must make up for the shortcomings of insufficient regional airport development as soon as possible. The regional tourism airport is the main component of the regional airport and the most active part of the development of regional airports. It complements the development of regional airports and focuses on accelerating the development of regional airports. Airport A was completed and opened to traffic in May 2017. It is a young and distinctive regional tourist airport. The annual passenger throughput has jumped from more than 100,000 passengers to more than 500,000 passengers in 2019. In the operation process, there are many worth learning from local. Especially in terms of cost control, Airport A creates “airport+” tourist traffic to improve passenger throughput, promotes a transition to management to adjust and optimize the cost structure, green planning and construction to reduce resource and energy consumption, and combines supervision with services to enhance the effectiveness of financial supervision, all of which give a good inspiration for other regional tourism airports to improve cost control.</p>

Resilience Endangered: The Role of Regional Airports in Remote Areas in Sweden

This paper examines the role of regional airports in regional and municipal crisis preparedness based on evidence from a case study in Sweden. During the summer of 2018, Sweden experienced some of the most extensive wildfires in modern time. Aerial suppression, for which airports provided the essential preconditions, played an important role in extinguishing these fires. This study includes analyses of public policies that shape the Swedish airport system as well as evidence from interviews and a workshop with stakeholders. The results show that an efficiently operated network of regional airports is critical not only for crisis management but also to ensure important societal services such as health care in sparsely inhabited regions. Moreover, access to quick transportation by air is necessary for the Swedish Prison and Probation Service, tourism industry, public institutions and private businesses. Additionally intensified by effects of both the public debate on flight shame and the COVID-19 pandemic on air-based transportation, the insights arising from this study emphasise that the currently one-sided focus on the number of passengers is an insufficient foundation for the Swedish airport system to construct a resilient base for regional development, crisis management and civil defense.

MULTI-ENERGY SYSTEMS IN GREEN AIRPORTS

With air transport electrification to achieve net-zero emissions targets, airports will play a vital role in providing charging system for future electric aircraft. Airports are expected to become an energy hub to integrate distributed and renewable energy resources to be self-sufficient and target for net-zero emissions. This paper proposes a multi-energy system (MES) with distributed energy resources (DER) integration for future “green” airports, aiming to meet electric aircraft charging load, and electricity and thermal energy requirements for airport operation. Distributed energy resources considered herein includes solar, wind, power-to-gas, hydrogen fuel cell, and multi-type energy storages. In order to evaluate the energy consumption, economic and environmental benefits of the multi-energy system with DER integration for green airport, Kansai airport is selected as case study. The optimal environmental and economic benefits for proposed airport multi-energy system are obtained by using the multi-objective particle swarm optimization algorithm.

Emergence Time Phasing for the Potential New Airports in the Middle District of Iraq

With the growing demand for air transportation and limited capacity at Baghdad International airport (BIAP), there is a need to increase the capacity of airport systems in the middle district of Iraq. The increased use of secondary airports has been and is expected to be one of the key mechanisms by which future demand is met in congested metropolitan areas. This paper analyzed the factors influencing the emergence of secondary airports in the Iraqi middle district and the dynamics of multi-airport systems. A system dynamics model was developed to simulate the relationship between the core airport in Baghdad and three potential secondary airports, one in each adjacent governorate. The model takes under consideration such characteristics as; capacity, location, proximity to populated communities, and ground transportation services for each airport. the main outcomes of this model are; the passenger's persuasion in an airport, which reflects their propensity to use this particular airport, and the predicted number of annual passengers in each airport. The system dynamics model was consulted twice. The outcomes of the first run facilitated the economic analyses of the secondary airports on which the sequence of the airports emergence was determined, and it also showed that the new airport feasibility is highly affected by the location, due to the influence on the road user cost for passengers, in addition to the capital expenses. The second run of the model helped in predicting the time schedule and interval between an airport emergence and the other. If the new airports have an equal capacity of one million passenger per year, the expected timing for the emergence is in 2023, 2027, and 2032 for the airports in Balad, Habbaniyah, and Baquba respectively.

Comparative evaluation of the Brazilian air transport system centrality

This work seeks to analyze the centrality of the Brazilian airport commercial system and compare flights data of 2015 and 2019. This paper is an extension and updated study from article presented at VII RIDITA (Pereira et al., 2019). We evaluated the Brazilian airport system by the results of layer centrality and h-centrality. These methodologies of centrality, unlike other traditional methods in graphs theory, try to evaluate the comprehensiveness of each vertex (in the case of the airport) and the influence on the others in the network. The results show the main characteristic of the Brazilian airport system regarding the concentration of the operation in regions and airports. Central airports demand greater attention from the agents in several operational fields (maintenance, traffic control, mobility, etc.) to raise the quality of the system.

Smart Airport: Evaluation of Performance Standards and Technologies for a Smart Logistics Zone

Owing to the current context of Industry 4.0, the importance of smart technologies in airport systems have increased substantially. State-of-art applications for transportation planning incorporating baggage services, routing, security, and safety are an evolving domain for both practitioners and researchers dealing with aviation applications. In this context, this paper seeks to answer these questions: Which standards are aimed at a smart airport to make the transportation planning sound? Which propositions are made based on the obtained prioritized standards? This study deals with standards including Environmental Effects, Docking & Navigation, Object Detection & Protection, Communications & Integration, and Terminology using a practical decision support system based on an analytical hierarchy process (AHP) and fuzzy inference system (FIS). Computational results reveal that the Object Detection & Protection standard has an effect on a safe and smart system. To give an overview of this standard for a smart logistics zone (SLZ), an architecture of autonomous robot units and a baggage handling system is proposed in this study. The suggested approach analyzes the obstacle photos obtained by cameras and allows the end-user to control the calculations visually. This research could provide advice to airport planners about smart policies and improving operations.

Foreign Object Debris Automatic Target Detection for Millimeter-Wave Surveillance Radar.

Foreign Object Debris (FOD) refers to any foreign material on the airfield that may injure and threaten the aircraft and airport system. Due to the complex background on the airfield pavement and weak target echoes in long-distance monitoring, it is not easy to detect objects of various types and sizes. The existing FOD radar system’s detection method has a short effective range, and the detectable objects’ radar cross-section intensity is no less than −20 dBsm. In this paper, we propose an integrated FOD automatic target detection algorithm for millimeter-wave (MMW) surveillance radar to improve small target detection under long-range conditions of over 660 m. The signal form of FOD and a clutter model of ground clutter received by millimeter-wave radar are primarily utilized and established theoretically. The runway edge detection means that it is employed based on the in-continuity features as the runway region of interest during the automatic extraction step. Following the clutter map constant false alarm detection algorithm, we utilize a time-domain algorithm that functions as the vital detection processor. Moreover, an explicit definition of the FOD detection performance is developed in a characteristic quantitative way. This criterion involves an absolute reference value for all FOD radar systems. The well-designed FOD frequency-modulated continuous-wave MMW surveillance radar is utilized, and actual experiments are carried out in a real airport in Beijing, China. The results validate the proposed method’s effectiveness and the superior performance of FOD target detection in long-range situations.