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ABSTRACT This article introduces a technique for suppressing pilot-induced oscillations (PIO) in aircraft equipped with fly-by-wire (FBW) flight controls. Drawing from the real-time oscillation verifier (ROVER) concept proposed by Mitchell and Hoh, in 1994, and an adaptive suppression system by Moura in 2018, the method involves dynamically adjusting stability derivatives via software during aircraft operation. The ROVER detects PIO conditions during flight, directing changes to the aircraft’s dynamics. Switching to a less susceptible model during PIO mitigates oscillations. The study focuses exclusively on longitudinal motion and pitch angle control. The proposed system is implemented and simulated using MATLAB routines, complemented by human pilot trials on a flight simulator. Results demonstrate real-time detection of PIO oscillations and effective mitigation, ensuring system integrity with acceptable degradation in flight qualities during transitions.

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ABSTRACT During the World Radiocommunication Conference to be held in 2027 (WRC-27), resolutions or agenda items that could significantly impact the operation of existing services, including aeronautical ones, will be analyzed. Among these items, those that could directly or indirectly affect aviation, in the view of the International Civil Aviation Organization (ICAO), include new frequency allocations for International Mobile Telecommunications (IMT), new allocation for aeronautical mobile service (route), new allocations for the mobile satellite service, development of telecommunications on the Moon, and new allocations for space research and Earth exploration satellite services. This study offers a comprehensive analysis of the spectrum management framework, with a particular focus on key WRC-27 agenda items affecting civil aviation. By examining the perspectives of ICAO, regulatory bodies, and industry stakeholders, it identifies potential risks to aeronautical services, their implications, and possible mitigation strategies, emphasizing the crucial role of regulatory agencies in safeguarding critical communication systems. As a valuable resource for decision-makers and researchers, this study enhances the understanding of spectrum allocation challenges and informs strategies for effective spectrum management.

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ABSTRACT In the past decade, there has been a significant increase in the development and utilization of unmanned aerial vehicles (UAVs) across various industries. Factors such as remote control, payload capacity, versatility, precision, and confidentiality have fuelled interest in UAVs for multiple applications. However, UAVs’ navigation and communication systems are increasingly vulnerable to various security threats, with the most concerning being the risks associated with Global Navigation Satellite System (GNSS) technology, such as spoofing and jamming. This paper presents a comprehensive analysis of UAV navigation security, drawing on recent peer-reviewed journals to identify and address gaps in current research. Machine learning and blockchain show promise but face scalability challenges. This review identifies underexplored gaps in environmental resilience. It examines the root causes of GNSS-related challenges, potential solutions, and promising research directions in the field of UAV navigation security.

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ABSTRACT When multiple targets are close to each other and intersect, the Gaussian mixture probability hypothesis density (GM-PHD) filtering algorithm experiences degraded tracking performance. To address this problem, a neighborhood multi-target tracking optimization algorithm based on weight correction is proposed. In the proposed method, a proximity monitoring mechanism is first introduced to detect the distance between targets. Next, the similarity between the measured data and the target predicted value is calculate to form a similarity matrix. If there are multiple data points in a row of the similarity matrix exceed the threshold, further correction should be performed on the data in that row. Finally, the weight correction matrix is formed by combining the above two steps. Simulation results demonstrate that the tracking accuracy and stability of the proposed algorithm are significantly improved in scenarios of multi-target intersection and parallel tracking, and its performance is better than that of the traditional GM-PHD filtering algorithm.

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ABSTRACT This study presents the development of a methodology for designing neuro-adaptive robust controllers based on a reference model associated with an artificial neural network of radial basis functions (ANN-RBF) for solid fuel suborbital rockets. The modelling and neuro-adaptive robust control algorithms for these rockets are presented. Initially, the methodology is evaluated for a robust controller based on a reference model with ANN-RBF for altitude control. The main objective of the control is to suppress the effect of non-linear uncertainties inherent in the process. The method involves mathematical and computational modelling, together with the design of adaptive controllers for stability and performance analysis. The controllers considered include model reference adaptive control (MRAC) techniques and a model reference neuro-adaptive control (MRNAC) approach. The analysis, carried out using computer simulations, evaluates the behavior of each controller in relation to system stability and performance. The final objective is to select the most suitable controller for the suborbital rocket, taking into account the system constraints, robust performance requirements, robust stability, and optimal adaptability. This research promotes the development of adaptive controllers for suborbital rockets, with possible applications in scientific research and commercial launches.

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ABSTRACT This paper addresses the use of cooperative systems in the management of innovative projects and their contribution to increasing the chances of success in the case study of the KC-390 Program, a significant project in the Brazilian aeronautical industry. Based on the administrative theory of cooperative systems, the study focuses on collaboration and trust in innovative projects, using the Technology Readiness Level as a guide for decisions. Complex products and systems require customized approaches due to their complexity and high engineering costs. Innovation in these projects depends on collaboration and trust between the developer and the requester. The methodology used includes applied and qualitative research, exploring bibliographic, documentary, and field research data. The KC-390 case study highlights the partnership between the Brazilian Air Force Command and Empresa Brasileira de Aeronaves (Embraer), evidencing how this relationship has been fundamental for technological development. The paper also explores the dual certification process of the KC-390, where the implementation of a collaborative process in the Conformity Demonstration Planning phase brought innovation to military certification. This innovation broke with the traditional paradigm of certification of aeronautical products in the country and was possible, mainly, due to the relationship of trust between the certifying authority and the integrating company.

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ABSTRACT This paper investigates the task scheduling problem for the Earth observation Interferometric Synthetic Aperture Radar (InSAR) satellite system. The mission time window generation method is introduced, and the constraint satisfaction model for task scheduling in the InSAR satellite system is constructed. To address the mission allocation issue between the chief satellite and deputy satellites, a mission conflict detection and resolution mechanism is developed. Moreover, based on the single-objective student psychology-based optimization (SPBO) algorithm, a modified non-dominated sorting SPBO (NSSPBO) algorithm is proposed to tackle the multi-objective task scheduling problem for the InSAR satellite system. Numerical simulations are presented to demonstrate the effectiveness and superiority of the proposed NSSPBO algorithm.

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ABSTRACT The use of non-intrusive instrumentation has been growing in different scenarios in the industry. In the aerospace field, non-intrusive or hybrid instrumentation approaches have demonstrated robustness and viability, presenting significant advantages such as mass reduction of space vehicles, flexibility, and reduction of instrumentation lead time. This work presents a brief overview of a hybrid instrumentation system, in which the Wi-Fi standard communication protocol is highlighted. As a case study, the experimental structural modal analysis technique was adopted to show the technical advantages of using this promising data acquisition (DAq) system. To achieve this, test data were acquired using the traditional wired method between sensors, DAq, and the computer, as well as a wireless transmission protocol, via Wi-Fi, between the DAq and the computer. The comparisons of the results of the modal analysis experiments showed good agreement, indicating the Wi-Fi communication protocol is suitable and reliable for the tested scenario.

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ABSTRACT Aircraft maintenance operations are carried out by aircraft maintenance technicians (AMTs) with the necessary competencies and qualifications. The level of competency of maintenance technicians directly affects the safety and effectiveness of maintenance operations and flight operations. The aim of this study is to determine the safety culture and responsibility competencies and assessment methods for AMTs. Data related to the study were collected by conducting individual interviews and focus group discussions with 83 participants. The data were analyzed using the content analysis method and coding technique. As a result of individual interviews and focus group discussions with the participants, it was decided to use “safety perception (30.14%),” “aviation culture (29.58%),” “personal protective equipment (PPE) (28.73%),” “risk perception (6.48%),” and “occupational health and safety (5.07%)” to assess safety culture competency. It was decided to use “attendance (40.08%),” “work ethics (25.95%),” “reporting and suggestion (18.99%),” and “health and wellness (14.98%)” to assess responsibility competency. It has been determined that individuals such as technicians with relevant competencies, human factors specialists, and aviation psychology specialists should take part as assessors, as well as safety management system (SMS), quality, and human resources units in the assessment processes of the competencies.

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ABSTRACT This paper presents the application of the unscented Kalman filter (UKF) for estimating the dynamic states of a maneuvering tank using a second-order Gauss-Markov process model. The proposed method is effective in capturing the oscillatory characteristics, damping effects, and the impact of uncertain disturbances on the tank’s dynamics, leading to improved estimation accuracy compared to traditional linear methods. Simulation results demonstrate that the UKF outperforms the extended Kalman filter (EKF) in accurately estimating the tank’s position, velocity, and acceleration, even in the presence of significant noise and disturbances. This study highlights the superiority of the UKF in handling nonlinear dynamics and its potential application in military vehicle tracking systems.

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ABSTRACT This study theoretically delineates China’s current airspace based on airspace management rules, primarily by constructing air corridors to optimize the existing structure, with validation through aviation carbon emissions analysis. First, seven air corridors were delineated based on route clustering analysis, and their significance was further evaluated through carbon emission efficiency comparison. The results show that: 1) the seven corridors are mainly located in central and eastern China, forming a “diamond-shaped three-dimensional structure”; 2) there are significant differences in operational scale among the corridors, with the Harbin-Haikou route being the most active and the Chongqing-Zhuhai route the least; 3) the total carbon emissions from the seven corridors amount to 619,431 tons, with carbon emissions and efficiency positively correlated with aircraft type, cruising time, and operational scale; 4) the flight density within established corridors is higher than before their formation, and they accommodate more flights. This study provides a broad coverage, highlighting the structural characteristics of China’s airspace.

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ABSTRACT This study addresses the finite-time formation control issues associated with time-delay multi-agent systems. To tackle the challenges of finite-time stability in delay systems, Artstein’s transformation is utilized. A distributed finite-time consensus algorithm is developed, incorporating an event-triggered control scheme and a corresponding triggering function to minimize unnecessary energy consumption and reduce the frequency of controller updates. The validity of the proposed approach is rigorously established through Lyapunov stability theory and finite-time stability theory, ensuring the absence of Zeno behavior. Furthermore, building upon the finite-time consensus algorithm, a finite-time formation control algorithm is formulated, enabling a group of agents to follow a designated leader while maintaining a specified formation shape. By employing feedback linearization, the unmanned aerial vehicle model is transformed into a precise linearized model. Finally, the application of this framework to formation control is presented, demonstrating the effectiveness of the proposed results.

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ABSTRACT This paper presents a method for calculating the delay time and determining the fixed delay components for laser fuzes installed on man-portable air defense systems (MANPADS), targeting small aerial vehicles such as cruise missiles. The method is based on the “kinematic-geometric” relationship between the missile, fragments, and the target, ensuring that the average fragment trajectory passes through the target’s center. Approach scenarios are divided into zones, with each zone using a common delay component. The laser beam’s inclination angle is aligned with the average fragment trajectory, ensuring delay time independence from miss distance. The approach zones are defined by kinematic relationships, including head-on or tail-chase modes and the azimuth angle. The delay time for each zone is calculated as the average delay across all scenarios within that zone. The method eliminates the effect of miss distance, with delay components dependent only on the missile’s direction of motion. A case study applying the model shows minimal error when using the average miss distance, and the results confirm that the fragment stream consistently hits the target across all approach scenarios. The proposed method offers an effective solution for accurately determining delay time and optimizing fuze performance in MANPADS.

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ABSTRACT For a robotic heterogeneous complex (RHC) consisting of a ground wheeled robot (GWR) and an unmanned aerial vehicle (UAV) connected by a tether mechanism (TM) and subject to steady wind acting on the UAV, a methodology for selecting control parameters for UAV landing on the GWR is considered. Landing is proposed along the straight line connecting the tether attachment point on the UAV with its base on the GWR. A synthesis of control for the TM and UAV engines was carried out to ensure landing within a predetermined time. A corresponding mathematical model of UAV and TM motion was derived. It is shown that the UAV’s equilibrium positions along the line are stable, ensuring minimal engine energy consumption during landing. A synthesis of piecewise-linear damping coefficients in the control systems for the TM and UAV engines was performed by selecting moments of slope change based on synchronizing the instantaneous tether length and the distance from the UAV to the landing point. Simulation of the full equations of motion confirmed the feasibility of the proposed UAV landing methodology on the GWR and the validity of the assumptions made.

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ABSTRACT To rapidly and cheaply obtain the plume characteristics of a 12.5 kW Hall thruster, a simulation model based on the fluid method is developed, and a plume measurement is conducted to verify and compare with the simulations. The results show that the discharge process will mainly occur in the upper part of the discharge channel, and the error between simulations and measurements of the magnetic field is less than 5%. The pressure in the discharge channel is the highest and the average pressure is about 0.12 Pa. In the plume diffusion region, the plasma density decays slightly along the axial direction and rapidly in the radial direction. Additionally, the plasma density and the electron temperature from the discharge channel outlet to the upper boundary of the plume region are in the range of 6.2 × 1016 to 5.2 × 1017m-3 and 1.8 to 12.2 eV, respectively. In the plume measurement, a single Faraday probe is used to scan and measure the beam current, and the simulations are consistent with the experiments. The simulation model basically achieves the purpose of obtaining the plume characteristics with certain accuracy, low cost and rapidly.

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ABSTRACT The study aims to analyze the existing computer vision techniques for commercial drone detection to identify their advantages, disadvantages, and determine the best approaches in different application scenarios. The research methodology used synthesis methods to explore and propose combinations of techniques based on an analysis of the methodology and results of other works in the literature. It employed algorithms and sensor data analysis to assess the effectiveness of detection methods, and deduction to formulate hypotheses and conclusions based on data and theories. The main research results include the development of computer vision methods for detecting commercial drones, identifying their visual detectability at different altitudes, analyzing different object detection methods, and evaluating the applicability of these methods for commercial applications. In addition, the study identified the advantages and disadvantages of applying computer vision to commercial drone detection and offered recommendations for further research and practical implementation. The practical value of this study is to improve the detection systems of commercial drones, thereby enhancing the safety and efficiency of their use.

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ABSTRACT CubeSats, small standardized commercial satellites, have emerged as platforms for carrying scientific instruments and qualifying innovative technologies in space. However, the high mission failure rate during the launch and early orbit phase (LEOP) has drawn attention to insufficient testing in their development process. Unlike traditional satellites, the shortened project life cycle of CubeSat missions often limits verification and validation (V&V) activities. Traditional V&V approaches address interoperability issues late in development, leading to time-consuming rework when nonconformities are identified during system integration. This paper proposes a Scalable Architecture Test System (SATS) to support the verification of interoperability requirements of CubeSats’ embedded software early in development. Interoperability models for two communicating software components are specified, from which test cases are automatically derived and software codes are generated to be embedded in programmable boards connected to a CubeSat communication channel. This architecture supports test execution in a model-in-the-loop (MIL) concept to verify requirements and later validate the implementation, when real hardware replaces simulated models. The approach’s effectiveness in early detection of faults is demonstrated in the NanosatC-BR2 project developed at the National Institute of Space Research (INPE), allowing the correction of the specification of software components earlier in satellite development.

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ABSTRACT This paper presents the design analysis of a suborbital launch vehicle by performing a multidisciplinary optimization analysis. The design problem consists of establishing the optimized launch scenario using the interior point optimization method. The minimization of the objective function (the total mass of the launch vehicle) is validated by a multi-criteria approach. It is shown that establishing the performance of the launch vehicle should meet the criteria of security and control during the launch mission. The security aspect is represented by adherence to the dynamic pressure for structural matters of the launch vehicle and the acceleration, represented by the G-force, which should remain tolerable. Control is denoted by keeping the vehicle’s velocity within the range required for a suborbital flight mission. The approach followed is appealingly constructive for conserving the multidisciplinary design optimization (MDO) formulation for a post-performance analysis.

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ABSTRACT Internet of things (IoT) devices are widely used in various fields, with their growing diversity and complexity posing challenges for traditional security measures. Device fingerprint identification can enhance network security and reliability by verifying device features. However, traditional device fingerprint identification methods usually rely on a single mode of traffic characteristics. In the face of changing network environments and diversified device types, it is often difficult to ensure efficient identification performance and robustness. To address the above challenges, this paper proposes a multi-modal traffic classification method for device identification in IoT networks to address the challenges in accuracy and robustness posed by traditional single-modal traffic feature approaches. The method combines various traffic features, such as packet size, transmission interval, flow duration, packet rate, byte rate, and protocol number. It includes four modules: data collection, preprocessing, model training, and fingerprint identification. Network traffic data are collected using deep packet inspection and capture tools, and features are standardized. The bidirectional encoder representations from transformers (BERT) model is applied for sensitive text feature extraction, while the convolutional neural network (CNN) model aids in device identification. Experimental results demonstrate high accuracy and robustness across different network environments and device types.

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ABSTRACT Reliability assessment of a multi-state system with binary state components (MSS-BC) is highly practical because the assumption that the system has a binary state system (BSS) is often unrealistic in many engineering applications. The main research problem is to determine the state of the MSS-BC based on the minimal path required for system operation and to evaluate its components’ importance. Such information is essential for purposes such as component prioritization, reliability improvement, and risk reduction (RR), allowing for the identification of a system’s weaknesses or critical components and the quantification of the impact of their failures on an MSS-BC. In this paper, a new reliability assessment approach for MSS-BC is presented, based on disjoint product forms of minimal path sets and survival signature. It also introduces methods for the Birnbaum importance (BI), improvement potential (IP), and RR measures using these concepts. Both the numerical case and the case study presented a driving subsystem in aerospace engineering to demonstrate the applicability of the approach for MSS-BC. The proposed technique shows clear superiority and potential for applications in aerospace engineering.

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ABSTRACT The increasing complexity of embedded systems in aerospace missions, particularly within the New Space paradigm, calls for more agile and cost-effective approaches to software and hardware integration. Traditional prototype-heavy development cycles are being replaced by virtualization and emulation techniques that support faster, iterative validation. Despite the growing adoption of such techniques, few studies propose a flexible and stable software-in-the-loop (SIL) framework tailored to emulated environments in the aerospace sector, especially considering open-source and widespread tools and technologies. This work addresses this gap by introducing a formal and adaptable SIL testing architecture based on the Quick EMUlator (QEMU), an open-source emulation platform, as its core. The framework targets the LEON3 processor, widely used in aerospace applications, and was validated through three sequential test scenarios integrating emulated environments and physical counterparts. These tests assessed software correctness, logical consistency, and timing behavior. Results confirmed full test success rates and the logical fidelity of the virtualized system, while revealing inherent timing discrepancies, characterized by an average advance of 20 ms in processing and transmission times compared to the physical counterpart. Despite these differences, the framework demonstrated sufficient accuracy and reliability for software testing in virtualized environments, provided its timing variations are properly accounted for.

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ABSTRACT The use of unmanned aerial platforms has increasingly been demanded in various applications. Among these, in-flight inspection stands out, traditionally conducted by aircraft equipped with various sensors to verify the performance requirements of ground-installed navigation aids, as well as air navigation procedures for operational and airworthiness purposes. In-flight inspection is costly in terms of time, qualified personnel, necessary equipment, flight hours, and operational impact on the inspected aerodrome. In this context, the use of unmanned aerial systems (UAS) emerges as a potentially cost-effective alternative, with the potential to significantly reduce the costs associated with the in-flight inspection of navigation aids. This work presents the methodology and results of in-flight inspection of the precision approach path indicator (PAPI) using UAS. The results presented are selected from over a dozen field campaigns, wherein inspection procedures were adapted to replace conventional aircraft with UAS. The results were compared to traditional inspections performed by the conventional aircraft crewed with professional flight inspectors. The findings indicate a strong similarity between the UAS methodology and conventional inspection, suggesting that UAS could partially or completely replace conventional inspections, significantly reducing the time, costs, and impact of inspections carried out by conventional aircraft.

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ABSTRACT One of the features of space-air-ground integrated networks and other heterogeneous networks is that most network applications operate in real-time, and network traffic is bursty and self-similar. An urgent task while designing heterogeneous networks is to predict the behavior of network traffic to take the necessary measures to preserve the information transmitted over the network. The article is devoted to the study of self-similarity properties of typical heterogeneous network traffic models, for the assessment of the degree of self-similarity of which the Hurst exponent and the total autocorrelation coefficient were used. A network traffic model in the form of an interval process is proposed, which allows modeling the moments of packet appearance, size, transmission rate, and time parameters of packet transmission over communication channels. Numerical results of the analysis of typical network traffic models in the form of point and interval processes are presented, which show that they have self-similarity properties. A simulation model of such a network with a monochannel and random-access protocols with collision detection has been developed. According the simulation results, with the Poisson model of subscriber traffic, network traffic has the property of self-similarity.

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ABSTRACT The next generation heterogeneous network (HetNet) consists of multiple technologies for the device to improve their quality of service (QoS) parameters for the ubiquitous connectivity. The key technology has the ability to use machine intelligence in the design of an energy-efficient HetNet. That allows internet of things (IoT) devices to choose which base station (BS) to connect with for optimal performance; the proposed QoS-aware deep Q network (Q-DQN) algorithm adapts an energy-efficient reward function to improve the performance of femto BS IoT devices without deviating from macro BS. The main objective is to ascertain the QoS requirement that should exceed the threshold level. The performance of the proposed work is validated through the QoS, system capacity, and energy efficiency. A dynamic power selection strategy in a HetNet is based on the Q-DQN algorithm subject to network QoS parameters. The Q-DQN power allocation using reinforcement learning in uplink HetNet offers a powerful approach to managing the complex trade-offs between QoS requirements and energy efficiency. By dynamically adjusting power levels based on real-time conditions, the comparative results are evident that the proposed algorithm provides improved capacity and energy efficiency in proportion to the escalating throughput enhancement.

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ABSTRACT This article describes the use of a commercial software-defined radio (SDR) to generate an intentional interfering signal for protection against drones. The system aims to counter unauthorized and offensive drone actions. The particular case of the geo-location system is analyzed, where the sensitivity limit to block its operation is measured in two different receivers: an external Stoton module and a Samsung mobile phone, serving as a drone surrogate. The USRP B-210 software-defined radio, controlled by GNU Radio, was employed to generate the jamming signal. The final experiments took place in an outdoor environment, with two different antennas and in two different sites. Results were compared with literature reports as well as a first-order approximation based on the free-space formula (Friis) free-space propagation formula (Friis). A radius of protection of approximately 29 meters was observed by using the radio with a simple omnidirectional monopole antenna, designed and constructed for this test.

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ABSTRACT The objective of research paper describes the failure study of escape-aid explosive (EAX) cartridges that failed during life assessment trials (LAT). The EAX cartridges serve as a critical component that is responsible for converting energetic materials into combustible gaseous products. The cartridges under study provide a delay between the trainer and trainee during the ejection of the seat in an adverse situation. Failure investigation plays an important role in the design and development cycle of EAX cartridges. The novelty in this research is that it attempts to carry out the failure study of the EAX cartridge during LAT. Failures of such devices lead to consequences involving missile launching, seat ejection, harness, bomb release, etc. This research paper focuses on the failure study of EAX cartridges for pilot seat ejection, methodologies for identifying root causes, and solutions for preventive and corrective actions to avoid the recurrence of such failures in the future. By applying a failure study in a systematic way, it is possible to identify the underlying causes of EAX cartridge failures and improve safety measures, reducing the risk of catastrophic failures during ejections. Failure investigation, when applied to the EAX cartridge in ejection seats, helps to identify failures that compromise the pilot’s safety or cause malfunctions in complex systems. From the study, it was inferred that failure of EAX cartridge during life trial might be attributed to improper functioning of cap.

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ABSTRACT This paper presents the design, development, and validation of KunturSat, a picosatellite developed for the CanSat France 2024 competition. KunturSat integrates multiple technological innovations, including a flag deployment system, precise descent control via a 9-cell paraglider, and a biodegradable marking mechanism using purple corn extract (Zea mays var. amilácea (L.)). The structural design utilizes lightweight, high-strength materials, such as Ripstop nylon, and employs advanced 3D printing techniques, ensuring both durability and flight efficiency. A comprehensive series of tests was conducted to evaluate its performance, including vibration analysis, communication tests, support deployment trials, free-fall simulations, and drone-based launches. These assessments validated the mechanical, electronic, and telemetry subsystems under real-flight conditions. The results confirmed KunturSat’s effectiveness in executing its primary mission of biodegradable surface marking, alongside its secondary missions of vertical stabilization and flag deployment. Identified improvements include reinforcement of structural components to enhance resilience in adverse conditions. KunturSat contributes to the aerospace sector as an innovative and sustainable platform, serving as a foundation for future picosatellites with autonomous descent control and advanced deployment mechanisms. Additionally, it underscores the importance of STEM education (science, technology, engineering, and mathematics) and accessible aerospace technologies in fostering engineering expertise.

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ABSTRACT With the growth in air traffic and the accompanying increase in fuel consumption and carbon emissions, international demands are increasing on the civil aviation sector to comply with sustainable development (SD) requirements. Accordingly, the purpose of this study was to explore whether meeting these requirements contributes to enhancing competitive advantage by analyzing the relationship between compliance with SD requirements and the attractiveness of navigation services provided by the Sana’a flight information region (FIR). A quantitative approach was employed through a questionnaire distributed to 98 employees in the Air Navigation Sector of the Civil Aviation and Meteorology Authority (CAMA). The research concluded that there is an impact of meeting international requirements for SD on the competitive advantage of Sana’a FIR. The research recommended the need to focus on achieving the environmental, economic, and social dimensions of the international requirements for SD, in addition to implementing continuous training and qualification programs for employees of CAMA to enhance their ability to understand and meet international standards for SD. Also, the a need to improve the technological infrastructure and develop smart navigation systems, as well as improve the speed of emergency response and the attractiveness to airlines.

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ABSTRACT Mach number anomaly detection is crucial in wind tunnel experiments. Moreover, there is a need for an anomaly detection model that can detect new samples based solely on historical normal data. This paper proposes an anomaly detection model for wind tunnel flow field Mach numbers using the nonlinear dynamic global-local retaining projection method (NDGLPP). This paper first analyzes the key process variables that affect the Mach number. Then, an iterative GLPP (IGLPP) combined with implicit polynomial expansion is employed to process the selected process variables, thereby extracting both global and local features along with their nonlinear relationships. Next, the corresponding statistical metrics, squared prediction error (SPE) and T², are calculated, and the control limits are determined through the cumulative distribution function (CDF). Finally, the constructed model is applied for anomaly detection. To validate the effectiveness of the model, a comparative analysis is conducted using principal component analysis (PCA), GLPP, and other methods. The experimental results indicate that the NDGLPP-based anomaly detection model for wind tunnel flow field Mach numbers not only achieves higher accuracy in detecting abnormal values but also effectively balances the capture of both global and local features, further confirming its effectiveness and superiority.

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ABSTRACT In an increasingly competitive air transport market, understanding customer demographics is crucial for airlines to develop targeted marketing strategies. This study investigates how sociodemographic factors influence the frequency of air travel and Frequent Flyer Program (FFP) adoption. Data from 427 online surveys of travelers aged 18 and above revealed that gender had no significant impact on either travel frequency or FFP adoption (p = 0.796). However, attributes such as age, marital status, ethnic/racial origin, education, and income significantly influenced these behaviors. While education (p = 0.165) and occupation (p = 0.061) showed no direct impact on FFP adoption, they were significant for travel frequency. Interestingly, lower-income groups exhibited a strong inclination toward FFP enrollment despite their lower flying frequency, indicating a tendency for segments with fewer benefits from FFPs to adopt them more readily. These findings suggest that airlines can enhance loyalty and market penetration by tailoring strategies to specific demographic segments, optimizing offerings for diverse traveler needs. The study highlights opportunities for future research into customer behavior and its implications for competitive advantage in the aviation industry.

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ABSTRACT Modeling of the internal flow of a nozzle is a vital step in the design of a rocket engine. This study focuses on providing an in-depth examination of a thermochemical rocket engine’s operation through chemical equilibrium. The computation extends to cover both gaseous and condensed species, as well as phase transitions, offering a comprehensive understanding of the engine’s behavior. Notably, this research introduces the ability to freeze the composition at any chosen point within the nozzle, allowing for tailored modeling to specific engine conditions and enhancing its versatility as a tool for analysis and design. Moreover, the study takes an additional step by calculating the transport properties along the nozzle. Special note is made of the difference between equilibrium and frozen variables. By integrating equilibrium composition, condensed species, and transport properties, this research exemplifies a holistic approach to analyzing and optimizing the performance of thermochemical rocket engines, with several illustrative examples showcasing the capabilities of the program.

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ABSTRACT This study aimed to propose different zigzag rib topologies for a trailing-edge morphing wing for low-speed applications. This study aimed to determine the best zigzag rib topology in terms of stiffness and safety factor. Numerical analysis was carried out using ANSYS under linear-static conditions for different test cases, such as rib topologies, rib thicknesses, deflection angles, and materials. A total of 81 test cases were studied with a point load applied at the trailing edge of each rib topology in each test to obtain the stiffness and safety factor. Experimental studies were also conducted to evaluate the mass and shapes of 3D-printed ribs. The findings revealed that thermoplastic polyurethane ribs with a 5 mm thickness exhibited moderate stiffness and a good safety factor, with no failure occurring under the applied conditions. Additionally, there was a perfect match between numerical and experimental results in terms of the mass and shape of the topologies under different test cases.

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ABSTRACT Near-field (NF) measurements are commonly used to predict the far-field (FF) of an antenna through NF to FF conversion. Conventional automated setup measurements use linear robotic systems that occupy a large space and are limited to scan multiple planes and co- and cross-polar in a sequence. Modern systems use a robotic arm to overcome this issue, but it is very expensive. This work explains how to perform 2D NF measurements using an outdated robotic arm controlled by Python and Arduino. This low-cost system was validated through horn lens measurements from X- to Ka-band. The maximum difference in beam waist between theoretical and measured was ~3.17 mm for the X-band horn lens antenna due to the focal distance difference of ~11.11 mm. The source of errors and limitations is discussed here. The measured data along with the Python code to generate 2D color maps are available on GitHub. Although it involves more complexity and additional steps compared to commercial systems, this budget system provided good agreement with the theoretical values of the horn lens antennas, becoming a viable alternative to perform raster NF measurements over a three-dimensional volume. Further works may include implementations of cylindrical or spherical measurements.

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ABSTRACT The lifespan of the Intelligent Transport System (ITS) nodes should be expanded, as overloaded nodes dying early affects existing hierarchical routing protocols, thus impacting the nodes lifetime. Inspired by this idea, an energy-efficient multipath routing method is proposed by utilizing adaptive clustering in wireless sensor networks (WSNs). A game-theoretic method for managing low energy multipath routing (LEMR-GT) in noncooperative games is developed to create energy-efficient network communication with equitable energy distribution. The utility function is based on the remaining power, amount of traffic, and number of links of nearby nodes. The contention radius for nodes is modified according to the topology and traffic load used to choose the cluster head. Then, the active nodes select the final cluster leader by assessing competitive parameters. Simulation results demonstrate that the proposed approach significantly outperforms conventional clustering protocols, such as Low-Energy Adaptive Clustering Hierarchy (LEACH) and Hybrid Energy-Efficient Distribute, in terms of network lifetime, energy efficiency, packet delivery ratio, and end-to-end delay. The LEMR-GT results indicate that our method achieves up to 38% improvement in energy savings, a 25% increase in network lifetime, and over 15% higher packet delivery ratio.

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ABSTRACT This study presents georeferenced data for the characterization of runways at public aerodromes, focusing on the organization of information to support macrotexture maintenance planning. A total of 499 public aerodromes and their respective runways were mapped and categorized according to operational classes. Additionally, 1,174 operational occurrences recorded in 2024 and directly related to runway conditions were extracted. A spatial and statistical analysis was conducted using linear regression between the number of occurrences and the measurement frequency assigned to each aerodrome. The results indicated a statistically significant correlation between the number of occurrences and the suggested analysis frequency. The findings demonstrate the applicability of integrating georeferenced data with operational records in the formulation of monitoring and management strategies aimed at improving the operational safety of airport infrastructure.

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ABSTRACT In Brazil, the concession of major airports to private entities aims to enhance infrastructure and operations, yet its fiscal impact on state revenues remains a critical question for policymakers. This study analyses this fiscal impact, with a specific focus on whether the 2017 privatization of Fortaleza Airport boosted the collection of the ICMS tax in the state of Ceará. We employ a dual-method approach. First, a panel data regression assesses the general impact of concessions on ICMS revenue across five northeastern states (2000–2022). Second, the Synthetic Control Method (SCM) isolates the specific causal effect of the Fortaleza concession by comparing Ceará to a weighted combination of similar untreated states. The panel regression reveals passenger movement as a key revenue driver, with the Fixed Effects model indicating a significant positive relationship from concessions. The SCM analysis shows a significant positive divergence emerging four years post-concession, suggesting a long-term positive impact on Ceará’s ICMS collection. The findings confirm that airport concessions can generate significant, long-term fiscal benefits for state governments by stimulating the tax base. These benefits, however, materialize only after a prolonged operational stabilization period, providing crucial evidence for policymakers designing temporal planning and risk-sharing arrangements in future infrastructure privatization policy.

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ABSTRACT Boarding is crucial to turnaround time and can cause significant delays, with the Federal Aviation Administration (FAA) estimating $30 billion in pre-pandemic losses. Previous studies on airport boarding focus on pre-defined strategies that often overlook passenger behavior. This has led to a lack of consensus on the best way to reduce boarding time and improve the level of service (LoS) in different contexts. To address this, this study proposes modeling boarding time using passenger behavior variables across different strategies by combining different techniques. A simulation of three boarding strategies is conducted using screening design of experiments (DOE) with 24 runs each, resulting in 72 samples for A320 boarding time estimation. Machine learning methods, including linear regression, k-nearest-neighbor (KNN), multi-layer-perceptron (MLP), random forest, and XGBoost, are then applied to the simulation data for analysis. As a result, a model that can be used to predict boarding time for a given context of passenger behavior is discussed. Although random forest and XGBoost showed the highest R-squared values, they presented overfitting. Linear regression, with an R-squared close to 0.5, reveals that boarding strategy and bag distribution are the most influential variables, consistent with the literature. Steffen’s strategy provides the lowest boarding time, averaging 12 ± 0.02 minutes to board 180 passengers.

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ABSTRACT This study assesses the aviation safety risks in Brazil posed by fireworks balloons, a cultural practice that has become a significant concern for air operations. The methodology involved analyzing Centro de Investigação e Prevenção de Acidentes Aeronáuticos (CENIPA) data on notifications and recorded collisions from 2014 to 2023, using descriptive and statistical approaches, alongside the application of the Federal Aviation Administration (FAA) risk matrix to assess the probability and severity of collisions. The results reveal a high concentration of notifications in the states of São Paulo, Rio de Janeiro, and Paraná, with a focus on the airports of Guarulhos (SBGR), Galeão (SBGL), Santos Dumont (SBRJ), Curitiba, Viracopos (SBKP), Congonhas (SBSP), and Campo de Marte (SBMT). The final risk analysis indicated that SBGR and SBGL airports present the highest collision risks, while SBRJ, despite not recording collisions, requires attention due to the high number of notifications. Additionally, SBKP and SBSP showed moderate risks, and SBMT, assessed using the general aviation risk matrix, exhibited a high risk for smaller aircraft. Pearson’s correlation (0.9157) between the number of notifications and collisions suggests that increased notifications are associated with a higher risk of collision. The study concludes with an urgent call for stricter regulations and preventive measures, emphasizing the need for new technologies to mitigate risks to Brazilian airspace.

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ABSTRACT The functional quality of runways (RWY) is a critical factor for the safety and comfort of airport operations. One of the main indices used to assess this quality is the International Roughness Index (IRI). Maintaining IRI values within acceptable limits is essential to avoid operational problems, reduce aircraft maintenance costs, and ensure safety. In this context, the aim of this article is to analyze whether there is variability in the IRI with maintenance and rehabilitation (M&R) costs on a RWY. The research method used data provided by the National Agency for Civil Aviation (Agência Nacional de Aviação Civil [ANAC]) for the years 2020, 2021, and 2023, collected by a laser profilometer. The results show that the interventions carried out in 2020 reduced the IRI values in 2021, improving the pavement condition. However, an increase in the IRI values was observed in 2023, indicating the onset of deterioration. The financial analysis showed that the most expensive interventions occurred in 2020 due to the need for pavement reconstruction, while in 2021, costs were lower due to preventive maintenance. In 2023, costs increased again, highlighting the importance of continuous M&R. In conclusion, fair M&R interventions are essential to maintain RWY quality and safety, prevent degradation, and avoid high future costs.

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ABSTRACT Advancing Air Traffic Management with the implementation of novel airspace structures, systems and procedures is crucial to enhancing the economic and environmental performance of aviation. This requires a solid understanding of operational performance through advanced data analysis. In this paper, large-scale historical aircraft tracking data and aeronautical information data are used to characterize the performance of terminal area operations at São Paulo/Guarulhos International Airport (SBGR) after the most recent airspace redesign, known as TMA-SP Neo. A key aspect of the TMA-SP Neo project was redesigning the SBGR arrival procedures with a Point Merge (PM) system, an innovative operational concept for terminal area traffic management. A trajectory classification approach is developed to identify the use of arrival procedures and several performance indicators are proposed to evaluate the actual utilization of the terminal airspace structure with PM and to quantify trajectory efficiency and conformance. The results reveal an uneven distribution of air traffic across arrival gates and types of procedures and a significant utilization of the novel PM structure for delay absorption during the sequencing process. The findings also highlight air traffic control preferences and opportunities for further improvements in delay management.

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ABSTRACT This study proposes and applies an integrated geospatial and statistical approach to investigate the spatial distribution of aircraft noise complaints (2021–2023) near Congonhas Airport (CGH). The methodology comprised four stages: (1) developing a multivariate theoretical framework; (2) collecting and integrating operational and territorial data; (3) spatial modeling using Geographic Information System (GIS) tools; and (4) multiscale statistical analysis incorporating Ordinary Least Squares (OLS) regression and spatial autocorrelation (Moran’s I = 0.565). Results reveal that 70% of complaints fall outside the noise contours established by the airport’s Specific Noise Zoning Plan, highlighting significant regulatory limitations. Additionally, 87% of complaints originated from residential areas directly under landing and takeoff trajectories. Statistical modeling identified the most influential variables as the presence within 65- and 70-dB zones, inclusion in landing routes, total built-up area, maximum building height, and distance to the runway. The study offers a replicable conceptual and methodological framework for urban airports, with applications in airport noise management, public policy development, acoustic zoning revision, and environmentally sensitive urban planning. This approach is particularly relevant for airport managers, regulatory agencies, and professionals in geotechnologies and urban sustainability.

Resumo em Inglês:

ABSTRACT This study investigates the applicability of electric vertical take-off and landing aircraft (eVTOLs) for emergency medical transport in the Brazilian Legal Amazon, a region characterized by vast territorial extension, limited road infrastructure, and restricted access to critical healthcare. The research estimates the population coverage potential of a selected eVTOL model and compares it to that of the Airbus H125, a conventional helicopter commonly used in aeromedical operations across Brazil. Using a Geographic Information System (GIS) spatial analyses were performed based on operational ranges, identifying populated areas within reach of hospitals equipped with adult Intensive Care Unit beds. Data from the Humanitarian Data Exchange (HDX) and Brazil’s Ministry of Health supported the analysis. After filtering eVTOL models by technical feasibility and technological maturity, the Joby S4 was selected due to its extended range and load capacity. The findings indicate that while helicopters can cover a broad area from a few operational bases, eVTOLs require a larger number of strategically distributed bases to achieve similar population coverage. Our findings show that network expansion with eVTOLs is economically viable if the total operating costs per eVTOL base do not exceed roughly 3.6 times those of an equivalent helicopter base. These results support the consideration of eVTOLs as a complementary solution to improve access to emergency care in remote areas of the Amazon, contributing to the broader discussion on advanced air mobility (AAM) in complex territorial contexts.