General Aviation Airports Research Articles

Aircraft Surface Movement and Operation Monitoring Systems in General Aviation and Commercial Airports: A State-of-the-Art Review

Aircraft Surface Movement and Operation Monitoring Systems in General Aviation and Commercial Airports: A State-of-the-Art Review

An Experimental and Analytical Approach to Evaluate Transponder-Based Aircraft Noise Monitoring Technology

Aviation is a vital modern transportation sector connecting millions of passengers globally. Sustainable aviation development holds substantial community benefits, necessitating effective management of its environmental impacts. This paper addresses the need for an accurate and cost-effective aircraft noise monitoring model tailored to non-towered general aviation airports with limited resources for official air traffic data collection. The existing literature highlights a heavy reliance on air traffic data from control facilities in prevailing aircraft noise modeling solutions, revealing a disparity between real-world constraints and optimal practices. Our study presents a validation of a three-stage framework centered on a low-cost transponder unit, employing an innovative experimental and analytical approach to assess the model’s accuracy. An economical Automatic Dependent Surveillance-broadcast (ADS-B) receiver is deployed at Purdue University Airport (ICAO Code: KLAF) to estimate aircraft noise levels using the developed approach. Simultaneously, a physical sound meter is positioned at KLAF to capture actual acoustic noise levels, facilitating a direct comparison with the modeled data. Results demonstrate that the developed noise model accurately identifies aircraft noise events with an average error of 4.50 dBA. This suggests the viability of our low-cost noise monitoring approach as an affordable solution for non-towered general aviation airports. In addition, this paper discusses the limitations and recommendations for future research.

Research on Lateral Safety Spacing for Fusion Operation Based on Unmanned and Manned Aircraft-Event Modeling.

With the rapid development of unmanned aerial vehicle technology and its increasing application across various fields, current airspace resources are insufficient for unmanned aerial vehicles' needs. This paper, taking Zigong General Aviation Airport in Sichuan as a case study, explores the lateral safety spacing in a mixed operation mode of unmanned aerial vehicles and manned aircraft. Currently, there are no standardized regulations for the safe spacing of the fusion operation of unmanned and manned aircraft. Theoretical research is essential to provide a reference for actual operations. It introduces the UM-Event (unmanned and manned aircraft-event) collision risk model, an adaptation of the Event collision risk model, considering factors like communication, navigation, surveillance performance, human factors, collision avoidance equipment performance, and meteorology. Safety spacing was determined via simulation experiments and actual data analysis, adhering to the target safety level (TSL). Findings indicate that surveillance performance has a minor impact on safety spacing, while communication and navigation significantly influence it. The safety spacing, influenced solely by CNS (communication performance, navigation performance, surveillance performance) and combined factors, increased from 4.42 to 4.47 nautical miles. These results offer theoretical guidance for unmanned aerial vehicle safety in non-segregated airspace.

Strengthening the Understanding of the Context for Airport City Planning: A Case Study on Airport City Parafield

Airport Cities have gained momentum all over the world in the last decades. However, Airport City planning often follows a one-size-fits-all blueprint approach, with many elements incompatible with the regional, economic, and cultural context. Using a general aviation Airport City in Adelaide in South Australia as the case context, we survey the retail choices of airport users and compare them with existing facilities and those retail facilities at Airport Cities of large commercial airports from the literature and industry examples. We found that desired retail facilities at Airport City Parafield are widely different from those at large-scale commercial hub airports and commonly promoted in the Airport City literature. The results indicate that preferences for retail facilities in the Airport City differ depending on the airport user groups, which are determined by the role of the airport. These findings suggest that the often practised one-size-fits-all approach in Airport City planning should be reconsidered. In summary, this study helps to augment both knowledge and practice by reinforcing the importance of planning retail facilities in Airport Cities in alignment with the airport role, the airport user groups, and the regional, economic, and cultural context.

Lead exposure from general aviation emissions in the UK: A review and call for action

AbstractLeaded fuel emissions exposed a global population of children to lead and its profound health consequences. Recognition of its harms precipitated a global phase out and replacement with unleaded substitutes for road vehicles. Despite this widespread recognition and action, aviation fuel for piston engine aircraft still contains lead. Leaded aviation fuel (AVGAS100LL) contains 0.56 g of tetraethyl lead (TEL) per litre and this lead must be jettisoned from the engine during operation to prevent fouling. This action distributes lead and lead compounds into the air and soil around general aviation airports. This has been shown to increase the blood lead levels (BLLs) of children living nearby to clinically significant levels. Whilst this problem is recognised by the EPA in the United States, it has received little attention in the United Kingdom. We provide a review of the situation in the United Kingdom with regard to the current policy and regulation framework. We analysed the UK's general aviation airport fleet, general avation airport data and GB residential address data. We estimate the unleaded‐readiness of the UK aviation fleet and the current usage of fuels at UK general aviation airports. We provide a first‐order estimate of the number of residential addresses exposed to lead near general aviation airports. We find that the majority of aviation fuel sold in the United Kingdom is leaded and that there are 370,632 residences within 4 km of a general aviation airport at risk from exposure to lead emissions. Finally, we present a path forward for regulation change and public health monitoring.

Improved Framework for Classification of Flight Phases of General Aviation Aircraft

Flight data mining enables airport owners, operators, and governmental entities to explore more intelligent management strategies; in particular, cost-effectively obtaining accurate operational data is beneficial for general aviation (GA) airports and their associated communities. The current data collection modus operandi, however, does not meet future needs, as aircraft operations are counted manually or estimated by sampling methods. The increasing traffic flow and limited available personnel at most GA airports make it unrealistic to continue using traditional methods to analyze aircraft operational statistics; therefore, a customized approach is needed to address this problem. Since different flight phases have different levels and types of impact on the environment, acquiring information related to the duration of each flight phase at the airport and within its surrounding airspace is critical to the assessment of emissions and noise pollution from aircraft. The primary goal of the research is to provide quantified inputs for the environmental evaluation model, such as the Aviation Environmental Design Tool (AEDT). This paper demonstrates a programmed framework that successfully achieves satisfactory performance in solving flight phase identification problems by testing the synthetic flight data as well as validating the empirical Automatic Dependent Surveillance-Broadcast (ADS-B) data. The experimental results suggest that the proposed methods achieve promising classification accuracy, leading to feasible deployment in airport operations.

Development of a Reliable Method for General Aviation Flight Phase Identification

Aircraft operations statistics have typically received significant attention from U.S. airport owners and operators and state, local, and federal agencies. Accurate operational data is beneficial in assessing airports’ performance efficiency and impact on the environment, but operational statistics at nontowered general aviation airports are, for the most part, limited or not available. However, the increasing availability and economy of capturing and processing Automatic Dependent Surveillance-Broadcast (ADS-B) data shows promise for improving accessibility to a wide variety of information about the aircraft operating in the vicinity of these airports. Using machine learning technology, specific operational details can be decoded from ADS-B data. This paper aims to develop a reliable and economical method for general aviation aircraft flight phase identification, thereby leading to improved noise and emissions models, which are foundational to addressing many public concerns related to airports.

It all adds up…the impact of cumulative changes on safety and production

AbstractOn December 21, 1999, a Cessna 150 M aircraft attempted a take‐off at Moorabbin General Aviation Airport in Australia. Just after take‐off, the engine lost all power. The pilot managed a forced landing onto the grass at the end of the runway. On touch down, the engine resumed power. This event led to approximately 5000 piston engine aircraft being grounded and triggered an investigation from the refinery that manufactured the fuel in the plane. An independent investigation by the Australian Transport Safety Bureau determined that a series of cumulative changes in how the fuel was manufactured led to the carry over of a corrosion inhibitor, which contaminated the fuel. Cumulative changes are often hard to track, as their consequences may not be readily apparent. This paper will explore the cumulative changes that occurred and how the application of a new risk assessment technique, Delta HAZOP, might have assisted in uncovering the impacts of the cumulative changes. Delta HAZOP views a system more holistically and looks for the impacts of cumulative changes to uncover risks that may be missed via the guideword approach.

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.

Developing Capacity Estimation Metrics for Airports Accommodating Smaller Aircraft Using Locally Collected Automated Dependent Surveillance-Broadcast Data

Airport operators need good capacity estimates for many purposes, including to bolster applications for funding support for capacity improvements. Based on a recognized need to enhance models for estimating the operating capacity of airports serving a user base of smaller aircraft, such as small general aviation airports, this paper describes research conducted to leverage automated dependent surveillance-broadcast (ADS-B) data to develop aircraft performance characteristics for use as inputs to future small airport capacity models. The research addresses this challenge by constructing home-built ADS-B data collection units using a Raspberry Pi-based hardware platform and an Amazon Web Services-based cloud architecture housing the study’s PostGreSQL database, and python-based codebase. The work was focused at three participating airports: The Ohio State University Airport in Columbus, OH (KOSU); College Park, MD (KCGS); and Republic Airport in Farmingdale, NY (KFRG). The hardware units were deployed at three study airports, collecting more than 90 million individual ADS-B messages transmitted by aircraft operating within the vicinity of the study airport. Models were developed to clean, process, and assess the data, and leveraged to determine aircraft performance characteristics within these environments. Initial work focusing on assessing the fleet mix, approach speeds, aircraft separation in arrival streams, and runway occupancy times was performed. Findings from this research revealed a very high accuracy and richness of collected and processed data, and performance metrics that were reasonable, valid, and applicable for use as inputs to future airport capacity models.

Design and Research of Double-Wheeled Helicopter Tractor

Due to the limited wheel size, existing domestic helicopter tractors are only applicable to some small and medium-sized single-wheeled helicopters. This paper introduces a double-wheeled helicopter tractor. The wheel holding mechanism can maximally hold a helicopter with a wheel diameter of 500mm, thus suitable for most common types of general aviation airports, such as Z-9, AS-365N, EC-155, AW -139, AS-332, etc. By improving stable torque output of the motor at low speed, self-developed reducer greatly increases the applicability and safety of helicopter traction.

Airspace Operation Effectiveness Evaluation Based on q-Rung Orthopair Probabilistic Hesitant Fuzzy GRA and TOPSIS

In order to improve the ability of airspace management, a multi-attribute decision-making tool based on q-rung orthopair probability hesitant fuzzy GRA-TOPSIS is proposed to solve the problem of airspace operation effectiveness evaluation; this is in view of the fact that there are few airspace operation effectiveness evaluation methods in general aviation airports. Firstly, taking general aviation airports as the research object, a complete airspace operation effectiveness evaluation system is newly established, its evaluation indicators are introduced, and its multi-attribute decision-making ideas are explained. Then, based on the q-rung orthopair probability hesitant fuzzy set, a new distance measure and information aggregation operator are defined, which can better deal with symmetry information. Secondly, we build a deviation maximization model to calculate the attribute weights of indicator elements in the decision-making process. Then, we combine the GRA method and TOPSIS method to rank the airspace operation effectiveness evaluation schemes. Finally, combined with calculation examples and comparative analysis, the reliability and rationality of the method proposed in this paper are verified, and the symmetry relationship between the evaluation results and the actual situation is better reflected. Experiments show that the method proposed in this paper can obtain more accurate airspace operation effectiveness evaluation results, and can provide reference for related research.

Substantial Near-Field Air Quality Improvements at a General Aviation Airport Following a Runway Shortening.

Santa Monica Airport (SMO), a general aviation airport in Southern California, recently shortened its only runway by 225 m at both ends to limit jet aircraft operations. We evaluated the resulting changes in aviation activity and air quality by measuring particle number (PN), black carbon (BC), and lead (Pb) concentrations, before and after the runway was shortened at two near-airfield locations including a residential site. Postshortening, there was a 50% decrease in total operations, driven mostly by the greater than 80% decrease in jet operations; however, there was no significant change in piston engine aircraft operations (which use leaded fuel). We measured greater than 75%, 30%, and 75% reductions in the concentrations of PN, BC, and Pb, respectively, after the runway was shortened, largely due to enhanced dispersion resulting from the increased distance to the newly shortened runway. Overall, the runway shortening improved air quality in nearby areas such that airport impacts were comparable to or lower than impacts from other sources such as vehicular traffic. Until aviation fuel becomes completely unleaded, runway shortening or relocating operations away from the edge abutting residential areas may be the most effective environmental impact mitigation strategy for general aviation airports situated adjacent to residential areas.

General Aviation Aircraft Identification at Non-Towered Airports Using a Two-Step Computer Vision-Based Approach

Aircraft identification in airport operations is critical to various applications, including airport planning and environmental studies. Previous research and commercially available systems heavily rely on recognizing aircraft tail numbers using text recognition. However, this approach alone does not provide accurate results in situations when the tail number visibility is reduced or obstructed. Furthermore, general aviation aircraft are harder to identify because they are small in size, and their tail numbers include substantial variations in fonts, sizes, and orientations. To tackle these issues, we propose a two-step computer vision-based aircraft identification method, first identifying the aircraft type and then recognizing the tail number in a probabilistic multi-frame-based (MFB) framework. In the first step, a convolutional neural network (CNN)-based aircraft classifier is customized to decrease the search space in the registration database. In the second step, the identification process is finalized by integrating the text recognition results into the designed probabilistic MFB framework. The proposed method achieves approximately 90% identification accuracy when tested on video data collected from three general aviation airports. This is a significant improvement compared to text recognition alone, which recognizes 67% of the individual tail number characters.

Examination of Temporal, Classification, and Population Impacts of Flight Operations at Airports in the United States during the COVID-19 Pandemic

Airports provide essential infrastructure to connect travelers and products to destinations across regions, nations, and the world. However, these connections were the focus of restrictions in the midst of a global pandemic because the same potential to provide access to people and products as a hub of long-distance travel can also serve as an opportunity to spread a virus. The objective of this paper is to explore the temporal effects of the COVID-19 pandemic on flight operations at airports in the US, in addition to an examination of the differences among various classifications of airports. For commercial service and general aviation airports, the airports with the quickest and most substantial recoveries were in areas with populations of under 100,000 people [within 48.2 km (30 mi) of the airport]. Airports with higher and lower populations within 48.2 km experienced sharper declines in flights and slower recoveries. Local, state, and national airport infrastructure investments will need to consider these effects and changes in demand spurred by COVID-19 while monitoring the long-term sustainability of the changes.

The Dangers of Lift on Parked Planes: General Aviation Airport Safety

The focus of this paper is to investigate proper aircraft management for safety on an airfield. This is accomplished by looking at lift caused by powerful winds to the aircrafts stored on an airfield, and the tension it places on the rope that secures them. This work could be used to determine when aircrafts are in high-risk and need to be stored either in hangars or moved to other airports prior to storms. The calculations used to determine these conclusions are also explored in the paper.

Optimal Sizing and Operation of Airport Infrastructures in Support of Electric-Powered Aviation

The adoption of hybrid-electric aircraft is expected to have a considerable impact on airport operations, with the need of new infrastructural requirements to support electric-powered fleets. In particular, battery-charging requirements shall play a decisive role. Preliminary investigations useful to perform scenario studies for the future implementation of electric-powered aviation can take advantage of the ARES methodology presented here, which provides the optimal solution to the sizing of airport battery recharging infrastructures. Based on the flight schedule and on the specifications of the aircraft fleet and the charging equipment, the solution assesses the number and type of charging points, the related electrical consumption in terms of energy and power, and further information needed to guarantee the required operational level while minimizing the procurement and operating costs. The method allows considering and comparing two charging strategies: plug-in recharge and battery swapping. Energy price variation in time is also taken into account and a full description of the optimal time scheduling of recharging operations is provided. Application studies to the reconfiguration of two existing aerodromes, a General Aviation airport and a large regional hub, are discussed, showing the potential of the proposed approach.

Leveraging Aircraft Transponder Signals for Measuring Aircraft Fleet Mix at Non-Towered Airports

The general aviation sector has contributed significantly to the overall growth of the aviation industry. Fleet mix and operations information is important for the analysis of both the safety and the environmental and economic impact of general aviation activity. Factual data on the impact of environment and safety is particularly important, given the scarcity of airport improvement funds and the strong stakeholder engagement that often occurs when airport investments are evaluated. The research presented herein evaluates Mode S short and extended squitter data collected from three general aviation airports over a one-month period. This article demonstrates that by utilizing the unique ICAO code present in Mode S records in the United States, ICAO identification can be used as a primary key for retrieving information from publicly available databases, permitting the determination of aircraft type and engine models. An aircraft operation type with the corresponding fleet mix information can thus be estimated at non-towered airports. The techniques reported here are also useful in monitoring the increase in aircraft compliant with the FAA’s January 1, 2020 mandate for ADS-B out to operate in large portions of the national airspace system. For the three Indiana airports studied, the proportion of ADS-B transponder messages received ranged from approximately 29% at the Terre Haute Regional Airport (KHUF) to 79% at the Purdue University Airport (KLAF).

Development challenges facing general aviation airports: A case study of Archerfield Airport, Queensland, Australia

In the last 30 years, many major airports around the world have embraced the concept of an ‘airport city’ through the development of both aviation and non-aviation related businesses and a localised planning policy response in support of these endeavours. In the Australian neo-liberal planning environment, there has been little federal policy direction and muted investment by the aviation community. This paper examines the case of Archerfield Airport in Brisbane, Australia, and identifies issues that may impede its growth and evolution towards an integrated and sustainable economic hub. These issues include zoning, airspace usage patterns, and the friction between social utility, historical preservation and commercial imperatives. Such issues likely represent endemic challenges nationally, requiring more affirmative planning action by stakeholders seeking to replicate international successes.

Multiple-Case Study of U.S. General Aviation Airports for Operational Sustainability

Improving operational sustainability may help U.S. general aviation (GA) airports improve overall sustainable development without substantial financial inputs. An exploratory multiple-case study of five GA airports was conducted to explore the current understandings of airport operational sustainability among U.S. GA airports. Based on findings, a new definition of airport operational sustainability for U.S. GA airports was developed. A set of performance metrics for measuring operational sustainability in U.S. GA airports was identified. The new definition may help GA airports to develop sustainable management plans, and may help airports in other categories to expand their sustainability perspectives. The metrics identified in this study may be used to measure progress to the sustainable development, identify problems, and set performance goals or targets for airports.