Browse Topic: Airports

Items (688)
With the rapid development of China’s civil aviation industry, the problem of airport noise has attracted widespread social attention. The requirement for the real-time monitoring and evaluation of acoustic environment around airports is becoming more and more intense. The identification of aircraft noise events in the complex acoustic environment surrounding the airport is the most critical technical problem in airport noise monitoring. However, the traditional noise source identification technology is difficult to be widely used in real-time monitoring system due to its large errors and complex deployment conditions. This paper presented an aircraft noise source identification technique based on a single acoustic vector sensor. The azimuth parameters of the noise source were estimated by the three-dimensional spatial positioning algorithm of sound pressure and particle vibration velocity combined with information processing, and the three-dimensional footprint of the noise event in the complex acoustic environment was described. Finally, the event was judged as an aircraft noise event by matching the noise footprint with the aircraft flight path. By monitored and analyzed the actual noise events of aircraft departure, the results show that this method can only use a single acoustic vector sensor to locate the aircraft noise source and distinguish the aircraft noise event from the background noise event, which provide a new lightweight method for the real-time airport noise monitoring system to locate the noise source and identify the aircraft noise event
Hou, JiayuHe, TianlunZhu, LinChen, YingLiu, YinhuiLv, LeiWang, YuhaoChen, Da
The features of airport clusters have a big impact on regional air transport. But problems within these clusters also affect airline operations. This study uses the Data Envelopment Analysis (DEA) model. It selects 16 airlines of different sizes as samples. It also identifies relevant input and output indicators to measure operational efficiency. The results show that the efficiency of large and medium-sized airlines generally went up. Small airlines have shown a slow but steady improvement in efficiency, with significant volatility due to cost and slot constraints. So, the study analyzes pure technical efficiency, scale efficiency, and comprehensive efficiency. It finds out the changing patterns of operational efficiency among airlines of different sizes and the reasons behind them.
Hu, KexinHuang, Tao
To mitigate the risks of runway incursions during aircraft transitions between closely spaced parallel runways, major hub airports globally have implemented End-Around Taxiway (EAT) as an effective safety solution. Operational data from leading international airports confirms that EAT installations have successfully enhanced surface safety while maintaining operational efficiency. However, the EAT involves a longer taxiing route, resulting in higher fuel consumption and pollutant emissions. This study takes the example of a set of closely spaced parallel runways at a domestic airport to analyze the ground taxiing process of arrival and departure flights, proposing a dynamic allocation strategy for EAT operations that can achieve energy conservation and emission reduction during the taxiing process. Through simulation, its effective operational performance is studied.
Wang, ZinanYe, Bojia
Automated aircraft parking systems enhance airport ground operations by enabling precise and autonomous docking of aircraft at gates. These systems reduce turnaround time, minimize human error, and optimize apron space through real-time object detection, obstacle avoidance, and dynamic path planning. Unlike fixed guided-path methods, the proposed system adapts to congestion and environmental conditions such as low visibility, ensuring safety and efficient maneuvering. Validation through simulation demonstrates the system’s potential to improve operational resilience and support scalable automation in future airport infrastructure.
Penugonda, Navya SunainaEdiga, Venkatadiwakar Goud
Air Traffic Management (ATM) must be familiar with the exact Aircraft Take-off Weights (ATOWs) of airplanes to make the most use of runways, maintain safety margins high, and keep utilization and resources in balance. This paper aims to present a dependable ATOW forecasting methodology that can assist the air transport industry in enhancing operational decision-making. This research used datasets acquired from the EUROCONTROL Performance Review Commission (PRC) 2024 Aircraft Take-Off Weight Estimation dataset featuring 527,000 flights over Europe containing aircraft details, air trips and flight conditions. Technique comprises structured data input, inspection of missing data, timestamp aggregation to identify demand cycles over time, and domain-specific feature engineering using distance_per_minute, block_minutes, taxiout_ratio, and a strong wake turbulence metric The two supervised learning models used were Linear Regression (LR) for understanding and XGBoost for performance prediction In comparison to LR's 4,409 kg MAE (mean absolute error), 7,061 kg RMSE (root mean square error), and 0.9825 R2 value, XGBoost significantly excelled with validation results showing an R2 value of 0.9992 and an RMSE of 1,514 kg In the absence of labelled test targets, cross-validation nevertheless showed a constant degree of generalizability The residual diagnostics showed that the model was reliable for practical execution with low-variance deviations that were unbiased An accurate ATOW estimate improves the demand-capacity balance and On-Time Performance (OTP) in ATM, which in turn affects the runway schedule, wake turbulence diversion, slot allocation, and fuel planning The results highlight the need to include ATOW predictions in both tactical and strategic planning to reduce delays, increase airspace usage, and promote sustainable aviation operation and possesses significant improvements will consist of weather and runway conditions, stochastic ambiguity computation, and drift monitoring to keep up with ever-changing operating variables while maintaining accurate forecasts.
Senthilkumar, N.S, GopalakrishnanGopinath, S
With the rapid development of the aviation industry, there is an increasing demand for safe apron operations and support capabilities. As a key facility in the apron fuel supply pipeline network, the performance and stability of the fuel hydrant well are crucial. However, the traditional repair and replacement process for fuel hydrant wells faces challenges, including lengthy construction times and significant impacts on airport operations. To address these issues, this article proposes a prefabricated refueling hydrant well technology, aimed at achieving rapid replacement of hydrants under non-stop construction conditions. Through on-site experiments, we have verified the feasibility of this prefabricated fuel hydrant well technology, determined the minimum dismantling boundary, and studied the rapid dismantling process, prefabricated pavement structure and installation process, as well as the application of self-compacting and fast-setting high-strength wellbore filling materials. The experimental results demonstrate that this technology can complete all processes within 12 hours and 34 minutes, including cutting the pavement, breaking the pavement, dismantling the old fuel hydrant well, installing a new type of hydrant well, installing prefabricated pavement, grouting, and filling joints, etc., without affecting oil pressure. The grouting material and the strength of the prefabricated pavement meet the design requirements, and the grouting effect is satisfactory. The connection between the fuel hydrant well and the pavement meets the operational requirements. This study provides a new technical solution for the repair and replacement of fuel supply hydrant wells in civil airports, which is expected to significantly enhance the safety guarantee capability of fuel supply in civil airports.
Ren, YuchengZhao, KunyangChang, LingsuWang, XiangjunHan, TianhuiLi, Zonghe
This paper analyzes the problems encountered in the site selection of large domestic airport towers. Combined with the site selection results of many large airports in China and a large number of scenarios simulated by FAA VIS software, multiple key factors such as line of sight angle, lateral resolution angle, target detection probability, and target recognition probability are analyzed, and quantitative calculation formulas are given. Finally, BIM software is used to simulate the airport and tower, and give coverage analysis for runways, taxiways, and aprons.
Shi, YongtaoWang, Shuo
The control of rainfall runoff drainage in large airports presents significant challenges, particularly in terms of real-time coupling with meteorological warnings. This paper proposes an optimization method for the layout of sponge-like drainage ditches in large airports under BIM-3DGIS coupling. A BIM water supply and drainage model is constructed, with detailed inspections conducted on the functions and connections of the pipeline system in Revit software. The flow velocity and equivalent water supply pressure within the pipelines are analyzed, and collision detection is performed on the components. Based on 3DGIS technology, an optimization model for the layout of sponge-like drainage ditches is established, taking into comprehensive consideration various factors such as airport topography, rainfall characteristics, and surrounding environment. By calculating the water level changes within the infiltration and drainage ditches under different design rainfall scenarios, the storage ranges, water levels, and waterlogging duration curves of various facilities during rainfall events with different return periods are simulated. Case studies demonstrate that this method can effectively improve airport drainage efficiency, reduce peak drainage flow, mitigate the risk of waterlogging, and decrease the number of collision points in drainage pipelines. It provides a scientific basis and technical support for the planning and design of sponge-like drainage ditches in large airports.
Geng, LiangsuiZhao, ZhenyuHu, Jing
Aircraft operations during landing or takeoff depend strongly on runway surface conditions. Safe runway operations depend on the tire-to-runway frictional force and the drag offered by the aircraft. In the present research article, a methodology is developed to estimate the braking friction coefficient for varied runway conditions accurately in real-time. To this end, the extended Kalman filtering technique (EKF) is applied to sensor-measured data using the on-ground mathematical model of aircraft and wheel dynamics. The aircraft velocity and wheel angular velocity are formulated as system states, and the friction coefficient is estimated as an augmented state. The relation between the friction coefficient and wheel slip ratio is established using both simulated and actual ground roll data. Also, the technique is evaluated with the simulated data as well as real aircraft taxi data. The accuracy of friction estimation, with and without the measurement of normal reaction force on the landing gear, is analyzed using the simulated data. The friction coefficient vs slip ratio curve, derived from the empirical “Magic formula”, compares well with the estimated maximum tire-to-ground braking friction, and a shift in optimal slip is observed in actuality compared to the predictions. The brake disc friction coefficient is also estimated during the process since the brake torque measurements are not available in the actual data. The estimated friction coefficient, which represents the real characteristics of the runway, can be used to tune the control algorithms of the aircraft’s anti-skid brake management system for various runway conditions. While improvements in anti-skid efficiency alone may not directly prevent all runway excursions, accurate real-time friction estimation enhances the predictability and reliability of braking action, supporting safer operations under degraded or uncertain runway conditions. Moreover, the real-time estimation of tire-to-ground friction coefficient vs slip ratio curves can be used to develop adaptive control algorithms for the brake management system.
T.K., Khadeeja NusrathSingh, Jatinder
In order to improve the operational efficiency of a multi-runway airport, an aircraft pushback and taxiing cooperative departure operation control method is proposed. First, a Markov decision process (MDP) model for dynamic pushback control is established based on the two-runway model. Then, the genetic simulated annealing algorithm is used as the optimization algorithm, and the DPC-GSAA algorithm solution model is proposed to find the conflict-free path with the least fuel consumption for the aircraft and runway selection. Finally, the effectiveness of the model and algorithm is verified by simulation experiments in Beijing International Airport, and the results show that the method can significantly reduce the taxiing waiting time of aircraft and improve the overall operational efficiency of the airport.
Luo, WeizhenLian, GuanWu, YingziLi, WenyongHuang, Haifeng
The rapid growth of the civil aviation industry has placed significant pressure on limited airport runway resources, leading to increased taxiing delays and excessive fuel consumption. These challenges are exacerbated by the constant rise in air traffic, which necessitates more efficient management of airport operations. To mitigate these issues, this study proposes a flexible management approach that categorizes busy periods based on airport traffic density, taking into account the fluctuating load demand at different times of the day. This approach ensures that resource allocation aligns with actual traffic conditions, optimizing operational efficiency. Additionally, leveraging the existing dynamic pushback control framework, this research develops a cosine-based dynamic pushback control model, which incorporates parking stand waiting penalties. This model aims to reduce departure costs by dynamically adjusting the pushback rate according to congestion levels. To further optimize the model, a novel genetic algorithm combined with continuous Markov chains is introduced. This algorithm is designed to determine the optimal control thresholds for different congestion levels throughout the day, ensuring that resources are used effectively while minimizing delays. Simulations conducted using actual operational data from Beijing Capital International Airport demonstrate the effectiveness of the proposed approach. Compared to the uncontrolled pushback method, the cosine-based dynamic pushback control method significantly reduces average taxiway waiting times by 42.92%. Furthermore, this method also reduces fuel consumption and emissions associated with taxiing delays, offering a more sustainable solution to managing airport congestion. This research provides a comprehensive strategy for improving airport operations in high-density air traffic environments.
Wu, YingziLian, GuanLuo, WeizhenLi, WenyongZhao, YeqiZhang, Hao
With the rapid development of the civil aviation industry, the increasing number of flights has made ensuring the safety and efficiency of airport surface movements a pressing issue. This study establishes a mathematical model to predict the collision risk of aircraft in the intersection area in real time, and proposes appropriate intervention zones for avoidance, implementing a deceleration avoidance strategy. The model is validated using historical operational data from Beijing Capital International Airport, and the results indicate that the proposed model effectively reduces the collision probability to below 0.3. It demonstrates strong performance in predicting cross-path conflicts and reducing conflict risks. Additionally, the deceleration avoidance strategy further lowers the collision probability, improving both the safety and efficiency of airport surface operations. This research offers valuable insights for enhancing the operational efficiency and proactive safety levels of civil aviation airports.
Zhang, TingLian, GuanZhang, GuoxinZhao, Yeqi
It is necessary to save fuel, shorten flight time and reduce cost in order to achieve maximum economic benefits. In this paper, based on the flight performance of aircraft, a database based on the optimal index of fuel saving is established, and the corresponding four dimension (4D) trajectory prediction information and vertical profile are generated on this basis. Finally, the vertical guidance simulation is carried out to verify the effectiveness of the algorithm. The algorithm can reduce air traffic congestion and improve airport operation efficiency while saving fuel.
Hui, HuihuiLi, Zhiyi
Smart airport is a key driver for the future development of civil aviation and a cornerstone of China’s ongoing “Four Airport” construction initiative. It is important to improve technology in many areas. This includes airport building, daily work, management, and making decisions. As air travel changes, using new tools like artificial intelligence, big data, and the Internet of Things (IoT) is very important. These tools help make airports more efficient, safe, and better for the environment. Because of this, building smart airports is not just a big goal but also a new way to deal with the challenges in today’s air travel systems. A key part in building smart airports is making a full evaluation system to check how well the projects are working. When a strong index system is made for smart airports, people involved can see clearly what is working well and what is not. So, chose using a three-scale hierarchical analysis method gives a clear and step-by-step way to look at different parts of smart airport building. This method helps check many things, like how well the technology fits in, how smoothly the airport works, how it affects the environment, and how users feel [1]. To check if this evaluation framework works in real life, a case study of Beijing Daxing International Airport is used. Daxing Airport is one of the top examples of smart airport building. It uses new technology and modern ways to manage the airport. So it is a good choice for this study. The case study shows that the evaluation system can work. It also gives useful advice for airport managers to make construction projects better.
Li, Shi-lingFu, Lu
This study establishes models of airport vertical navigation lights and aircraft vulnerable components (wings and landing gear) using SOLIDWORKS. Based on the frangibility standards for airport navigation facilities, the control dimensions of the circular tube model for navigation lights are determined. Numerical simulations are conducted in ANSYS Workbench to analyze collisions between aircraft wings/landing gear and navigation lights under three different velocity conditions. Internal energy analysis, bidirectional force response, and stress nephograms during the impact process are evaluated. The results indicate that current standards ensure that collisions with vertical navigation lights during takeoff and landing do not cause deformation or damage to aircraft vulnerable components, thereby guaranteeing the safety of aircraft and pilots.
Wang, JianwuSong, XiaoboWei, YanLiu, HongweiYou, ShengnanSun, Jinkun
Airports as Energy Nodes (AENodes) - AAAE Presentation
Cary, Scott
Electra's Ultra Short: Pioneering Direct Aviation - without Airports, Emissions or Noise
Ausman, Marc
The emergence of electric Vertical Takeoff and Landing (eVTOL) air vehicles is transforming how people and freight are moved in short distances. This transformation has a profound impact on surrounding infrastructure necessary to provide Aircraft On Ground support for eVTOLs. The hover capabilities of eVTOLs have similar operating characteristics within terminal and uncontrolled airspace. However, the need to conserve battery energy via rapid approaches and departures affects terminal airspace management. To attract eVTOL operators, existing airports, landing zones, and vertiports are modifying their infrastructure to include fixed electric charging stations, additional taxiways, upgraded fire suppression systems, separate hangers, and capable MRO facilities. Augusta Regional Airport (KAGS) is the base airport for the annual Masters Golf Tournament which experiences five times the normal airport traffic and some 40,000 commuting patrons. eVTOLs can offset land traffic issues associated with commuters and supplies. Since KAGS is centroid to 32,000 square miles of territory void of major highways, basing eVTOLs can offer expedited transit services for people and goods which will have a profound impact on the economic viability and quality of life in the area.
Stanzione, KaydonJohnston, Diane
In the last years, new rotorcraft configurations have increased the attention among industries, through which the tiltrotor one due to its capability of combining both rotorcraft and aircraft advantages. However, there are situations where the vertical take-off mode could be enhanced in hard environmental and flight conditions. Therefore, to address this challenge, this work aims to develop a methodology to characterize a roll take-off model for a general tiltrotor configuration in such situations. By combining the integration of the equation of motion and geometrical assumptions, the runway distance is determined for an acceptable range of nacelle tilting angles. The process is developed by meeting the requirements defined by the regulations, combining the aircraft certification standards (CS23 and CS25) with the available tiltrotor certification basis from the FAA project #TC3419RC-R. Following the Nominal application, a sensitivity analysis is carried out, which studies the main effects on the results by varying one variable at a time in terms of weight, wing-loading, and disk-loading.
Passarelli D'Onofrio, Anna SofiaPecoraro, Matteo
Due to the crucial impact on flight scheduling, airline planning, and airport operations, flight departure delay prediction has emerged as a severe and prominent issue within the realm of smart aviation systems. Accurately predicting flight departure delay durations constitutes a crucial aspect of smart aviation management. Such predictive capability empowers aviation authorities and airport regulators to implement optimized air traffic control strategies, mitigating delays and elevating airport operational efficiency, while enhancing the satisfaction of travelers. The methodology employed in flight delay prediction has undergone substantial evolution in recent years, progressing from rudimentary statistical models to more sophisticated and intricate machine learning models. In this study, we introduce a novel machine learning model enriched with network features and grid search-based parameter selection for advanced predictive analytics of flight departure delays. This model integrates air traffic network feature extraction, feature selection, and machine learning-based prediction. Specifically, we leverage complex network theory to extract both node-level and edge-level features from the air traffic network. Subsequently, the XGBoost algorithm is employed for feature selection and delay prediction, capitalizing on its flexibility and robust performance. A case study utilizing a high-dimensional flight dataset from the U.S. Bureau of Transportation Statistics (BTS) was conducted to assess the model’s effectiveness. The experimental results and the visualization results demonstrate that the proposed framework surpasses several benchmark models, achieving an average delay prediction accuracy with a deviation of about 3.7 minutes. This framework exhibits strong potential for addressing high-dimensional, large-scale predictive challenges in flight delay management while maintaining superior accuracy.
Chen, LinxianShen, XiuyuChen, JingxuLiu, Xize
Aiming at the problem of insufficient capacity of taxiways in hub airports, which combine the safety interval, conflict resolution and fair principles, a taxiway planning model is established by taking the shortest taxiway as the optimisation goal, considering fuel consumption and exhaust emissions. Dijkstra algorithm is used to transform the taxiing path into an adjacency matrix, and conflict resolution is carried out in a weighted way. Under the premise of ensuring zero conflict of taxiways, the total taxiing distance is reduced. Based on actual operational data from a hub airport in China, the results show that the proposed taxiing path planning method is feasible, shortening the aircraft taxiing distance and improving the surface taxiing efficiency.
Feng, BochengQi, XinyueZhang, Hongbin
As the demands for air travel and air cargo continue to grow, airport surface operations are becoming increasingly congested, elevating the operational risks for all entities. Conventional measurement methods in airport traffic scenarios are limited by high temporal and spatial costs, uncontrollable variables, and their inabilities to account for low-probability events. Moreover, current simulation software for airport operations exhibits weak simulation capabilities and poor interactivity. To address these issues, this study developed a virtual reality traffic simulation platform for airport surface operations. The platform integrated 3D modeling technologies, including Blender and Unity, with the Photon Fusion multiplayer platform and Simulation of Urban Mobility (SUMO) traffic simulation software. By incorporating Logitech external devices, the platform enabled real-time human-driven simulations, multiplayer online interactions, and validation of airport traffic flow models. To enhance practical applicability of the platform, a scenario library for vehicle-aircraft-taxiway coordinated operations was designed based on historical data. A stated preference survey was distributed to aviation experts, evaluating scenario risk ratings and occurrence frequencies. Principal component analysis and rank sum ratio were applied to identify key scenarios, which were embedded into the platform. The results of this study simulate the interaction among vehicles, aircraft, and airport taxiways, providing a scenario-driven control strategy verification platform and real-time interactive driving decision support. This approach contributes to the digital transformation of airport surface management, enhancing operational efficiency and safety.
Zhang, YuhengHan, ZhongyiZhang, YuhanYe, Zhirui
Pushing the Envelope: Decarbonizing Aerospace/ Airport
Schneider, Jesse
SAE Hydrogen Airport Task Group - Enabling H2 Fueling of Aircraft
Schneider, Jesse
Economic Feasibility Study of Deploying Clean H2 Infrastructure at Los Angeles International Airport (LAX)
Rezaei, SajjadAlsamri, KhaledSimeoni, ElioHuynh, JacquelineBrouwer, Jack
CONOPS: Battery and Hydrogen-Powered Aircraft at Aerodromes
Novelo, Alejandro
2025-VFS H2-Aero Symposium: Decarbonizing Aerospace and Airports with H2 - Wrap Up and Needs
Schneider, Jesse
Decarbonizing Aerospace and Airports with H2
Schneider, Jesse
X-rays are a common component of diagnostic testing and industrial monitoring, used for everything from monitoring your teeth to scanning your suitcase at the airport. But the high-energy rays also produce ionizing radiation, which can be dangerous after prolonged or excessive exposures. Now, researchers publishing in ACS Central Science have taken a step toward safer x-rays by creating a highly sensitive and foldable detector that produces good quality images with smaller dosages of the rays.
Since the COVID-19 pandemic that advanced contactless service, robots are increasingly being seen conducting routine deliveries around hospitals and hotels. Developed by Robotise Technologies, JEEVES is one such autonomous service robot used in hotels, healthcare facilities, offices, airports, and other settings. Its main duty is to transport materials and products.
The advent of the low-altitude economy represents a novel economic paradigm that has emerged in recent years in response to technological advancement and an expanding social demand. The low-altitude economy is currently undergoing a period of rapid development, which underscores the importance of ensuring the safety of airfield operations. To enhance operational efficiency, unmanned aerial vehicles (UAVs) can be utilized for the inspection of the surrounding area, runway inspection, environmental monitoring, and other tasks. This paper employs TurMass technology, the TurMass gateway is miniaturised as the communication module of FT24, and the TK8620 development board replaces the LoRa RF module in the ELRS receiver to achieve the communication transmission between the remote control and the receiver. Additionally, a TurMass chip is integrated into the UAV to transmit beacons, while an airfield management aerial vehicle is employed to receive nearby UAV data, thereby preventing collisions. A new ground test device was employed to mitigate the risks associated with the actual test. The article provides a comprehensive account of the underlying principles, system architecture, pivotal technologies, and prospective applications of the aerial vehicle.
Zhang, XiaoyangChen, Hongming
The purpose of this AIR is to establish a baseline for hydrogen fueling protocol and process limits for both gaseous and liquid hydrogen fueling of aircraft (eCTOL, eRotor, eVTOL, LTA) at the airport from small aircraft to wide-body. A further goal is to harmonize and establish common aircraft fueling safety definitions wherever possible with other SAE and EUROCAE standards and NFPA codes alike. Hydrogen fueling process limits (including the fuel temperature, the maximum flow rate, time required, etc.) are affected by factors such as ambient temperature, fuel delivery temperature, and initial pressure in the hydrogen storage system. The further goal is to establish basic fueling protocols within these limits as a starting point while evaluating minimum criteria, including evaluation of fueling with or without communications. AIR8466 establishes the protocol and process limits for hydrogen fueling of aircraft and plans to establish fueling protocols starting with small aircraft. Optionally, communications may be used, and a general description will be included. Gaseous hydrogen fueling and liquid hydrogen fueling at cryogenic temperatures are two very different types of fuel stored in different types of vessels with safety mitigations. The goal is to start with an all-encompassing AIR for hydrogen fueling, both gaseous and liquid, and, after publishing, establish a family of documents covering categories of fueling as determined by the SAE AE-5CH team. To minimize storage volumes, compressed hydrogen gas stored under pressure up to 700 bar (70 MPa) achieves 39.5 kg per m3, or as a cryogenic liquid 20 K achieves 71 kg per m3. Other methodologies of liquified hydrogen, such as subcooled liquid or cryo-compressed, offer the potential for higher storage densities (the latter is not covered in this document). Figure 1 compares the volumetric and gravimetric densities of hydrocarbon fuels as well as the most common hydrogen storage methods in liquid and gaseous hydrogen and three types of hydrogen storage with different hydrogen density versus phases, pressure, and temperature (gaseous hydrogen, liquid hydrogen, and cryo-compressed). Presently, there are established codes and standards for ground vehicles at SAE, ISO, NFPA, etc., that could also be applicable to some applications for hydrogen at the airport. While there are some existing fuel cell and hydrogen standards for aerospace (such as SAE/EUROCAE information reports), there is a need to create new fueling station standardization efforts, which are outlined herein. The volume of hydrogen required will depend on the pressure and phase (ambient gaseous or cryogenic liquid) and the size of aircraft. Therefore, a series of ground standards will be required to cover the phase, thermal, and pressure variables.
AE-5C Aviation Ground Fueling Systems Committee
This equipment specification covers requirements for airfield liquid anti-icing/deicing equipment for airfield snow removal purposes. The unit shall include a combination of a carrier vehicle, liquid product tank, and dispensing system. This vehicle as a unit shall be an integrated chemical dispensing deicing/anti-icing application system. Primary application is for the liquid chemical application for cleaning of ice and snow from airfield operational areas such as runways, taxiways, and ramp aprons. The term “carrier vehicle” represents the various self-propelled prime movers that provide the motive power necessary to move snow and ice control equipment during winter operations. The airport operator may require this specified piece of equipment in order to maintain the airfield during large and small snow events. When necessary, the airfield liquid anti-icing/deicing chemical applicator (ALAD) shall be a central and critical element in the winter pavement maintenance fleet in the effort to accomplish the airport’s published snow plan. This ARP defines the minimum functionality for a vehicle to be classified as an ALAD specifically as an integrated snow and ice removal system capable of performing multiple and simultaneous functions requiring no more than one operator. ALADs may be utilized to perform additional pavement maintenance tasks such as deicing or anti-icing, rubber removal, or others. If additional features are required, they must be defined by the airport operator as part of their ALAD specification. The airport operator may add to or delete from any item of this specification to meet its requirements providing there is no compromise in safety.
G-15 Airport Snow and Ice Control Equipment Committee
The winged body reusable launch vehicle needs to be tested and evaluated for its functionality during the pre-flight preparation at the runway. The ground based checkout systems for the avionics and the actuator performance testing during pre-flight evaluation are not designed for rapid movement. This new kind of launch vehicle with solid rocket first-stage and winged body upper-stage demands the system testing at Launchpad and at the runway. The safety protocol forbids the permanent structure for hosting the checkout system near runway. The alternative is to develop a rapidly deployable and removable checkout system. A design methodology adopting conventional industrial instrumentation systems and maintaining mobility is presented. This paper presents the design and development of a mobile checkout system for supporting the ground pre-flight testing during autonomous flight landing trials.
V, Vivekanand
Transporting cargo has been a goal of helicopter operations since the earliest days of development. The concept of carrying passengers and cargo from and to remote locations without a runway was originally exploited by the US military in times of peace and war. Early helicopter designs were limited in fixed useful load after onboarding crew and fuel. The 1940's saw helicopters transporting small, lightweight packages on an as-needed basis. The decade of the 1960's started seeing heavy lift helicopters transporting specialty loads in construction and logistics supply, again on an as-needed basis. Today, several Part 135 helicopter operators offer as needed VTOL cargo services. Blade Air Mobility has developed a successful public company business model in Part 135 passenger transport and is also expanding in carrying parcels. With the advent of transformative VTOL air vehicle designs, there has been increasing emphasis on examining parcel delivery on a regular basis. As omni-channel ecommerce drives the ever-increasing need for same day delivery post order. Retails and distributors need to compete with big box retailers and warehouse companies such as Walmart and Amazon, respectively. This results in reducing or eliminating over-the-road transport delivery. The future of parcel and cargo distribution is proposed to be with VTOL air vehicles. To understand the future of such distribution, it is imperative to examine the development of helicopter size, performance, and operational uses.
Stanzione, KaydonSchrage, Daniel
When the aircraft towing operations are carried out in narrow areas such as the hangars or parking aprons, it has a high safety risk for aircraft that the wingtips may collide with the surrounding aircraft or the airport facility. A real-time trajectory prediction method for the towbarless aircraft taxiing system (TLATS) is proposed to evaluate the collision risk based on image recognition. The Yolov7 module is utilized to detect objects and extract the corresponding features. By obtaining information about the configuration of the airplane wing and obstacles in a narrow region, a Long Short-Term Memory (LSTM) encoder-decoder model is utilized to predict future motion trends. In addition, a video dataset containing the motions of various airplane wings in real traction scenarios is constructed for training and testing. Compared with the conventional methods, the proposed method combines image recognition and trajectory prediction methods to describe the relative positional relationship between the wings and obstacles, which enhances the accuracy of aircraft wing collision prediction during aircraft towing operations.
Zhu, HengjiaXu, YitongXu, ZiShuoJiYuan, LiuZhang, Wei
This specification covers runway deicing and anti-icing products in the form of a liquid. Unless otherwise stated, all specifications referenced herein are latest (current) revision.
G-12RDP Runway Deicing Product Committee
This specification covers a runway deicing and anti-icing product in the form of a solid. Unless otherwise stated, all specifications referenced herein are latest (current) revision.
G-12RDP Runway Deicing Product Committee
Nowadays, the rapid growth of civil aviation transportation demand has led to more frequent flight delays. The major problem of flight delays is restricting the development of municipal airports. To further improve passenger satisfaction, and reduce economic losses caused by flight delays, environmental pollution and many other adverse consequences, three machine learning algorithms are constructed in current study: random forest (RF), gradient boosting decision tree (GBDT) and BP neural network (BPNN). The departure flight delay prediction model uses the actual data set of domestic flights in the United States to simulate and verify the performance and accuracy of the three models. This model combines the visual analysis system to show the density of departure flight delays between different airports. Firstly, the data set is reprocessed, and the main factors leading to flight delays are selected as sample attributes by principal component analysis. Secondly, the mean absolute error (MAE), mean absolute percentage error (MAPE) and root mean square error (RMSE) were selected as evaluation indexes to compare the prediction results of three different models. The final results show that the departure flight delay prediction model based on BPNN algorithm has faster solution speed and overcomes the over-fitting problem, and has higher prediction accuracy and robustness. Based on the algorithm developed in this paper, the airport system can be planned in a targeted manner, thereby alleviating the pressure of air transportation and reducing flight delays.
Qi, XinyueQian, PinzhengZhang, Jian
Transporting baggage is critical in airport ground support services to ensure smooth flight operations. However, the scheduling of baggage transport vehicles faces challenges related to low efficiency and high costs. A multi-objective optimization vehicle scheduling model is proposed to address these issues, considering time and space costs, vehicle utilization, and passenger waiting time. An improved genetic algorithm (IGA) based on the large-scale neighborhood search algorithm is proposed to solve this model. The simulation experiment is conducted using actual flight data from an international airport. The IGA algorithm is compared with the standard genetic algorithm (SGA) based on experimental results, revealing that the former achieves convergence in a significantly shorter time. Moreover, the scheduling paths of baggage cars that violate flight service time window requirements are significantly lower in the final scheduling scheme under the IGA algorithm than in SGA. Additionally, there is a 14.89% reduction in total scheduling costs compared to SGA. The results indicate that the proposed model and algorithm are feasible and effective, which can provide a reference for the actual operation of the airport.
Jiang, HanZhang, JianZhang, HaiyanQian, Pinzheng
Ground vibration testing (GVT) is an important phase of the development, or the structural modification of an aircraft program. The modes of vibration and their associated parameters extracted from the GVT are used to modify the structural model of the aircraft to make more reliable dynamics predictions to satisfy certification authorities. Due to the high cost and the extensive preparations for such tests, a new method of vibration testing called taxi vibration testing (TVT) rooted in operational modal analysis (OMA) was recently proposed and investigated by the German Institute for Aerospace Research (DLR) as alternative to conventional GVT. In this investigation, a computational framework based on fully coupled flexible multibody dynamics for TVT is presented to further investigate the applicability of the TVT to flexible airframes. The time domain decomposition (TDD) method for OMA was used to postprocess the response of the airframe during a TVT. The framework was then used to examine the impact of the taxiing speed, shock absorber damping coefficient, and bump geometry on the outcome of the computational TVT. It was found that higher taxiing speed does not necessarily mean a better quality TVT, and one must find the optimal speed using the computational framework presented herein. A higher shock absorber damping coefficient was found to increase the amplitude of the response during the TVT without significantly impacting the extracted modes and their frequencies. Also, the quality of the TVT was found to be inversely proportional to the curvature of the bump cross section. The proposed TVT computational framework is validated against the normal modal analysis technique and certain experimental data.
Al-bess, LohayKhouli, Fidel
More airports are starting to adopt and test the use of radio frequency (RF) mitigation techniques to counter the operation of unmanned aircraft systems (UAS) in violation of civilian airspace rules. While civilian aviation regulatory agencies are welcoming the integration of more commercially operated UAS into civilian airspace, airports are responding to the growing number of incidents in recent years with counter measures to ensure drones do not interfere with regular operations. In the U.S., the Federal Aviation Authority (FAA) now receives more than 100 reports per month from pilots that have observed UAS operating near airports or within a restricted area of civilian airspace. The problem is a unique one for the FAA and other civilian aviation regulatory agencies who want to unleash as much commercial UAS innovation as possible within civilian airspace, but simultaneously recognize rogue operators are a problem. The FAA's method for addressing the operation of drones near airports or in violation of civilian airspace rules is currently a loose collection of reactionary penalties or fines based on what occurred. But that is starting to change, and RF is one of several counter measures under evaluation at U.S. airports.
The goal of the automated mobility platforms (AMPs) initiative is to raise the bar of service regarding equity and sustainability for public mobility systems that are crucial to large facilities, and doing so using electrified, energy efficient technology. Using airports as an example, the rapid growth in air travel demand has led to facility expansions and congested terminals, which directly impacts equity (e.g., increased challenges for Passengers with Reduced Mobility [PRMs]) and sustainability—both of which are important metrics often overlooked during the engineering design process. Therefore, to evaluate systems and inform critical near- and long-term decisions more effectively, a holistic evaluation framework is proposed focused on four key areas: (1) mobility, with emphasis on travel time and accessibility within an airport, (2) environment, focused on energy consumption and greenhouse gas (GHG) emissions associated with intra-airport mobility, (3) equity, specifically to the PRM community, but with an eye to the whole of society, and (4) built environment, or the fundamental changes in building design enabled by different mobility systems for larger and more flexible, functional, and energy-efficient structures. Below, AMPs are defined, and each metric is discussed further, all with a focus on airport mobility. Automated Mobility Platform (AMP): AMPs are broadly defined as mobility systems and/or services that leverage automation technologies to improve efficiency and reduce costs. In addition, advanced sensing and communications technologies are used in parallel with state-of-the-art methods in optimization and analytics to inform real-time decisions in complex operating environments. In the airport context, the AMPs system would consist of a mixed fleet of lightweight, electric vehicles that are centrally controlled and can reposition using automation technologies. At the same time, individual vehicles may also be equipped with a joystick/steering wheel to allow users to independently experience airport amenities – while larger vehicles designed for terminal-to-terminal movement may only operate in completely automated mode. AMPs benefits to equity and sustainability are closely tied to improved mobility (and user autonomy – not fully reliant on airport escorts) for PRMs and reduced energy consumption through the used of right-sized, lightweight electric vehicles that can be optimized to best respond to fluctuations in demand. Mobility: Mobility benefits were identified and evaluated through engagement with airport facility and disabled community stakeholders with emphasis on discerning requirements for PRMs at airports. As airports continue to expand, creating longer paths to traverse between curb drop-off and boarding gates, as well as between connecting gates, the ability to efficiently convey passengers along these paths without excessive delay is becoming more challenging. While automated vehicles will continue to evolve and at some point, allow people to navigate public roadways without physically driving the vehicle, evidence points toward a need to concurrently enhance mobility systems to serve large facilities in a similar fashion. This report analyzes and quantifies the challenges of transporting people—both ambulatory and PRM—through airports, as well as the fundamental limits that current airport design practice is confronting with respect to acceptable pedestrian travel times and distances. Environment: The energy and GHG benefits of airport mobility systems follow a near-term and long-term perspective. The near-term benefit assessment compares the energy consumption and GHG emissions for both PRM and non-PRM travelers. Long-term energy and GHG impacts are associated with building and facility design and functionality, enabling not only larger, more efficient tailored structures, but also more efficient regional transport by providing highly effective first-mile/last-mile services, and interfacing seamlessly with emerging electrified and automated roadway mobility services. This study evaluates the environmental impacts of current and future airport mobility options from a systems perspective – from strategic planning and facilities design to daily operations. Equity: Travel time and ease of pedestrian-related travel is closely associated with equity concerns of the PRM community. It is estimated that 20% or more of the traveling public possesses some type of disability or impairment that prevents them from being fully ambulatory and participating in routine walking, standing, and navigating functions within airports [1]. Some subpopulations can be identified and delineated within this group (such as those in need of daily wheelchair assistance or the legally blind), but the total number of PRMs is more difficult to enumerate, and the delineation is not purely a matter of binary classification. Natural human aging limits the ability to walk long distances, stand for long periods while boarding, or navigate complex terminals to find one’s departure gate. With a growing portion of the aging population (air travel demand increasing at twice the rate compared to the general population [2]) and ever larger airport terminal complexes, more elderly people with physically diminished skills will continue to travel and require improved accommodation to effectively move through such facilities. This report presents findings related to the difficulties faced by vulnerable population groups in the airport setting and presents solutions to address and mitigate these challenges through AMPs technologies. Built Environment: The fourth dimension focuses on building design, and how different mobility systems and infrastructure impact facility performance. Currently, many different mobility options exist that span from the most rigid (moving walkways) to highly flexible (fleet of single passenger automated vehicles). This study will bring together expert knowledge and related literature to discuss near- and long-term impacts of mobility infrastructure on facilities and potential new designs enabled by various mobility systems. Overall, this report develops a holistic framework from which to evaluate different mobility systems and technologies in the large facility setting. The primary focus will be airports, however, similar approaches can be used for other large facilities, such as hospitals. AMPs will be the baseline for comparison, as they contain many characteristics (if deployed and managed intelligently) that can directly address issues related to mobility, environment, equity, and the built environment.
Young, StanleyGrahn, RickDuvall, Andrew
An extensive evaluation of the Deep Image Prior (DIP) technique for image inpainting on Synthetic Aperture Radar (SAR) images. Air Force Research Laboratory, Wright Patterson Air Force Base, OH Synthetic Aperture Radar (SAR) images are a powerful tool for studying the Earth's surface. They are radar signals generated by an imaging system mounted on a platform such as an aircraft or satellite. As the platform moves, the system emits sequentially high-power electromagnetic waves through its antenna. The waves are then reflected by the Earth's surface, re-captured by the antenna, and finally processed to create detailed images of the terrain below. SAR images are employed in a wide variety of applications. Indeed, as the waves hit different objects, their phase and amplitude are modified according to the objects' characteristics (e.g., permittivity, roughness, geometry, etc.). The collected signal provides highly detailed information about the shape and elevation of the Earth's surface. SAR images are also used for monitoring natural disasters, such as earthquakes, floods, and landslides, as well as for detecting changes in land-use patterns, such as urbanization and deforestation. Due to their nature of providing detailed imagery regardless of daylight and weather conditions, SAR images are also a precious asset in military applications. As a matter of fact, SAR images can be used to detect sensible military targets like aircrafts, airports, ships, tanks or other vehicles.
Measurements in snow conditions performed in the past were rarely initiated and best suited for pure and extremely detailed quantification of microphysical properties of a series of microphysical parameters, needed for accretion modelling. Within the European ICE GENESIS project, a considerable effort of natural snow measurements has been made during winter 2020/21. Instrumental means, both in-situ and remote sensing were deployed on the ATR-42 aircraft, as well as on the ground (ground station at ‘Les Eplatures’ airport in the Swiss Jura Mountains with ATR-42 overflights). Snow clouds and precipitation in the atmospheric column were sampled with the aircraft, whereas ground based and airborne radar systems allowed extending the observations of snow properties beyond the flight level chosen for the in situ measurements. Overall, five flight missions have been performed at different numerous flight levels (related temperature range from -10°C to +2°C) beyond the ‘Les Eplatures’ airport. The manuscript focuses primarily on statistical retrievals of temperature dependent microphysical snow properties, with in particular, the total condensed water content (TWC), number and mass size distributions, the latter allowing to calculate the mass representative diameter proxy of the median mass diameter (MMD), ice crystal effective density, and a series of snow particle size dependent descriptors of morphological properties (3D volumetric diameter versus 2D image diameter, sphericity, crosswise sphericity, aspect ratio). In addition, snow properties from the ground based MASC imaging probe and complementary retrievals of snow properties from ground based and airborne radar observations are included in this study.
Jaffeux, LouisSchwarzenboeck, AlfonsCoutris, PierreFebvre, GuyDezitter, FabienAguilar, Borisbillault-Roux, Anne-claireGrazioli, JacopoBerne, AlexisKöbschall, KilianJorquera, SusanaDelanoe, Julien
One of the most significant challenges for the aviation industry in the winter is the deicing operations on runways. As a result, deicer chemicals can pollute the environment if used in a large amount. A mathematical model could help optimize the use of deicer chemicals. Road deicing models exist to predict pavement temperature covered by snow/ice during deicing operations. However, the specificity of airport operations requires a model for the runway deicing to simulate the mass of ice melted with usage of deicing agents. Here we propose a model for runway deicing and validate it against experimental results. Our model considers temperature, diffusive flux, and time changes in a normal direction. It also calculates the mass and heat transfer in three regions (liquid, mushy, and solid). We used the enthalpy method to determine the temperature and the interface location at each time step. In the liquid and solid, the deicer concentration is obtained by Fick’s law and updated at each time step and location. The melting point temperature is variable due to the dilution of the deicer in the solution. Therefore, melting points are updated depending on the concentration at each location and time. The model uses the phases diagram for water and deicer agent mixture, considering eutectic point, for melting point calculation. The mesh dependency of the model is first investigated. To verify the model sensitivity, the paper proposes parametric studies for the heat transfer coefficient and the diffusion coefficients. Then, to validate the model, the Anti-Icing Materials International Laboratory (AMIL) in Chicoutimi conducted experimental tests on deicer agents for runways. Validation of the model is achieved for potassium acetate and potassium formate, two types of deicers.
Maroufkhani, AidaCharpentier, ClaireMorency, FrancoisMomen, Gelareh
Surveillance cameras are becoming more commonplace in public environments, as well as finding use in private security and military operations. We are particularly interested in scenarios where a single pan-tilt-zoom (PTZ) camera is used to perform surveillance in large outdoor environments, which may include 360-degree horizontal coverage and depths out to 1 km or more. These scenarios exist in many environments such as security for building exteriors, airports, highways, parking lots, and property perimeters; anomaly detection in dense urban environments; and surveillance in military overwatch missions. In environments with many vertical obscurations (e.g., trees and buildings), ground-based cameras will need to be carefully located to provide long-range views. As the elevation of the camera is increased above the ground level, by placement on tall poles or building rooftops, for example, obtaining views of distant regions becomes easier.
This SAE Recommended Practice establishes uniform Installation Parameters for desiccant Air Dryers for vehicles with compressed air systems.
Truck and Bus Brake Supply and Control Components Committee
Items per page:
1 – 50 of 688