Aerospace, Volume 11, Issue 3 (March 2024) – 77 articles

The aim of this research paper is to propose a framework to model, simulate and control the motion of a small spacecraft in the proximity of a space station. In particular, rendezvous in the presence of physical obstacles is tackled by a virtual potential theory within a modern manifold calculus setting and simulated numerically. The roto-translational motion of a spacecraft as well as the control fields are entirely formulated through a coordinate-free Lie group-type formalism. Likewise, the proposed control strategies are expressed in a coordinate-free setting through structured control fields. Several numerical simulations guide the reader through an evaluation of the most convenient control strategy among those devised in the present work. Full article

This work details the development and validation of a methodology for high-resolution rotor models used in hybrid Blade Element Momentum Theory Unsteady Reynolds Averaged Navier–Stokes (BEMT-URANS) CFD. The methodology is shown to accurately predict single and coaxial rotor performance in a fraction of the time required by conventional CFD methods. The methodology has three key features: (1) a high-resolution BEMT rotor model enabling large reductions in grid size, (2) a discretized set of momentum sources to interface between the BEMT rotor model and the structured URANS flow solver, and (3) leveraging of the first two features to enable highly parallelized GPU-accelerated multirotor CFD simulations. The hybrid approach retains high-fidelity rotor inflow, wake propagation, and rotor–rotor interactional effects at a several orders of magnitude lower computational cost compared to conventional blade-resolved CFD while retaining high accuracy on steady rotor performance metrics. Rotor performance predictions of thrust and torque for both single and coaxial rotor configurations are compared to test the data that the authors obtained at the NASA Langley 14- by 22-ft. Subsonic Tunnel Facility. Simulations were run with both fully turbulent and free-transition airfoil performance tables to quantify the associated uncertainty. Single rotor thrust and torque were predicted on average within 4%. Coaxial thrust and power were predicted within an average of 5%. A vortex ring state (VRS) shielding phenomenon for coaxial rotor systems is also presented and discussed. The results support that this hybrid BEMT-URANS CFD methodology can be highly parallelized on GPU machines to obtain accurate rotor performance predictions across the full spectrum of possible UAM flight conditions in a fraction of the time required by conventional higher-fidelity methods. This strategy can be used to rapidly create look-up tables with hundreds to thousands of flight conditions using a three-dimensional multirotor CFD for UAM. Full article

The fluidic pintle nozzle, a new method to control the thrust of a solid rocket motor, has been proposed in recent years by combining the pintle with the aerodynamic throat (fluidic throat). The study of static characteristics has proved that it has a remarkable effect on thrust control. To study the transient characteristics of the fluidic pintle nozzle, 2D transient simulations of a fluidic pintle nozzle propulsion system were conducted, employing dynamic meshing techniques. The Reynolds-averaged Navier–Stokes equations were meticulously solved, implementing a k–ω SST turbulence model. The thrust control principle of the fluid pintle nozzle was studied, and the wave structure was summarized. The transient characteristics of the secondary flow opening, secondary flow closing, pintle moving forward (pressure rise), and pintle moving backward (pressure drop) were obtained, and the effects of the injection angle and injection port position were studied. The response process after injection can be roughly divided into three stages: pressure propagation, pressure oscillation, and equilibrium stability, with time distributions of 0.4%, 5.39%, and 94.21%, respectively. In the process of the pintle moving forward, the rate of combustion chamber pressure increases and thrust decreases gradually because of the arc wall of the nozzle throat upstream, and the process of throats moving backward is just the opposite. Compared with the condition with a maximum throat opening and no secondary flow, the thrust of the condition with a minimum throat opening and a 0.3-flow-ratio secondary flow is increased by 80.95%. Under conditions of constrained flow ratio, the injection angle of the secondary flow ostensibly exerts negligible influence on the dynamic modulation of thrust. Nevertheless, it remains evident that a reduction in throat opening accentuates the impact of reverse injection. Furthermore, the proximity of the injection port to the head of the pintle is directly proportional to the efficacy of thrust control. Full article

Sounding rockets constitute a class of rocket with a generally simple layout, being composed of a cylindrical center-body, a nosecone, a number of fins placed symmetrically around the longitudinal axis (usually three or four), and possibly a boat-tail. This type of flying craft is typically not actively controlled; instead, a passive stabilization effect is obtained through suitable positioning and sizing of the fins. Therefore, in the context of dynamic performance analysis, the margin of static stability is an index of primary interest. However, the classical approach to static stability analysis, which consists in splitting computations in two decoupled domains, namely, around the pitch and yaw axis, provides a very limited insight to the missile performance for this type of vehicle due to the violation of the classical assumptions of planar symmetry and symmetric flight conditions commonly adopted for winged aircraft. To tackle this issue, this paper introduces a method for analyzing static stability through a novel index, capable of more generally assessing the level of static stability for sounding rockets, exploiting the same information on aerodynamic coefficients typically required for more usual (i.e., decoupled) static stability analyses, and suggests a way to assess the validity and shortcoming of the method in each case at hand. Full article

Hypersonic vehicles or engines usually employ complex thermal protecting shells. This sometimes brings multi-physics difficulties, e.g., thermal-aeroelastic problems like panel flutter etc. This paper aims to propose a novel optimization method versus thermal dynamic influence on panel vibration. A traditional panel structure was modelled and analyzed. After analyzing its dynamic characteristics of panel flutter, thermal effects were also included to propose thermal-aeroelastic analysis results of the present hypersonic panel. Then, a MMC (Moving Morphable Component) method was proposed to suggest dynamic optimization for such panel structures. The proposed method can provide arbitrary frequency control result in order to suggest a newly generated panel structure. Based on the optimal structures, dynamic analysis was presented again to verify the effectiveness of the optimization method. So aero-thermo-dynamic characteristics of the optimal panel structures could be investigated. It can be seen that the computational results presented significantly improved panel flutter results. The proposed dynamic optimization method can be employed for the design of panel structures versus high combustion temperatures or hypersonic aerodynamics. Full article

This paper presents an approach for integrating uncertainty information in air traffic flow management at the tactical phase. In particular, probabilistic methodologies to predict sector demand and sector congestion under adverse weather in a time horizon of 1.5 h are developed. Two sources of uncertainty are considered: the meteorological uncertainty inherent to the forecasting process and the uncertainty in the take-off time. An ensemble approach is adopted to characterize both uncertainty sources. The methodologies rely on a trajectory predictor able to generate an ensemble of 4D trajectories that provides a measure of the trajectory uncertainty, each trajectory avoiding the storm cells encountered along the way. The core of the approach is the statistical processing of the ensemble of trajectories to obtain probabilistic entry and occupancy counts of each sector and their congestion status when the counts are compared to weather-dependent capacity values. A new criterion to assess the risk of sector overload, which takes into account the uncertainty, is also defined. The results are presented for a historical situation over the Austrian airspace on a day with significant convection. Full article

There are hundreds of various sensors used for online Prognosis and Health Management (PHM) of LREs. Inspired by the fact that a limited number of key sensors are selected for inflight control purposes in LRE, it is practical to optimal placement of redundant sensors for improving the diagnosability and economics of PHM systems. To strike a balance between sensor cost, real-time performance and diagnosability of the fault diagnosis algorithm in LRE, this paper proposes a novel Optimal Sensor Placement (OSP) method. Firstly, a Kernel Extreme Learning Machine-based (KELM) two-stage diagnosis algorithm is developed based on a system-level failure simulation model of LRE. Secondly, hierarchical diagnosability metrics are constructed to formulate the OSP problem in this paper. Thirdly, a Hierarchy Ranking Evolutionary Algorithm-based (HREA) two-stage OSP method is developed, achieving further optimization of Pareto solutions by the improved hypervolume indicator. Finally, the proposed method is validated using failure simulation datasets and hot-fire test-run experiment datasets. Additionally, four classical binary multi-objective optimization algorithms are introduced for comparison. The testing results demonstrate that the HREA-based OSP method outperforms other classical methods in effectively balancing the sensor cost, real-time performance and diagnosability of the diagnosis algorithm. The proposed method in this paper implements system-level OSP for LRE fault diagnosis and exhibits the potential for application in the development of reusable LREs. Full article

Eddy-viscosity-based turbulence models provide the most commonly used modeling approach for computational fluid dynamics simulations in the aerospace industry. These models are very accurate at a relatively low cost for many cases but lack accuracy in the case of highly rotational leading edge vortex flows for mid to low aspect-ratio wings. An enhanced adaptive turbulence model based on the one-equation Spalart–Allmaras turbulence model is fundamental to this work. This model employs several additional coefficients and source terms, specifically targeting vortex-dominated flow regions, where these coefficients can be calibrated by an optimization procedure based on experimental or high-fidelity numerical data. To extend the usability of the model from single or cluster-wise calibrated cases, this work presents a preconditioning approach of the turbulence model via a neural network. The neural network provides a case-unspecific calibration approach, enabling the use of the model for many known or unknown cases. This extension enables aircraft design teams to perform low-cost Reynolds-averaged Navier–Stokes simulations with increased accuracy instead of complex and costly high-fidelity simulations. Full article

UAV swarms have multiple real-world applications but operate in a dynamic environment where disruptions can impede performance or stop mission progress. Ideally, a UAV swarm should be resilient to disruptions to maintain the desired performance and produce consistent outputs. Resilience is the system’s capability to withstand disruptions and maintain acceptable performance levels. Scientists propose novel methods for resilience integration in UAV swarms and test them in simulation scenarios to gauge the performance and observe the system response. However, current studies lack a comprehensive inclusion of modeled disruptions to monitor performance accurately. Existing approaches in compartmentalized research prevent a thorough coverage of disruptions to test resilient responses. Actual resilient systems require robustness in multiple components. The challenge begins with recognizing, classifying, and implementing accurate disruption models in simulation scenarios. This calls for a dedicated study to outline, categorize, and model interferences that can be included in current simulation software, which is provided herein. Wind and in-path obstacles are the two primary disruptions, particularly in the case of aerial vehicles. This study starts a multi-step process to implement these disruptions in simulations accurately. Wind and obstacles are modeled using multiple methods and implemented in simulation scenarios. Their presence in simulations is demonstrated, and suggested scenarios and targeted observations are recommended. The study concludes that introducing previously absent and accurately modeled disruptions, such as wind and obstacles in simulation scenarios, can significantly change how resilience in swarm deployments is recorded and presented. A dedicated section for future work includes suggestions for implementing other disruptions, such as component failure and network intrusion. Full article

Mitigation strategies to eliminate existing space debris, such as with Active Space Debris Removal (ASDR) missions, have become increasingly important. Among the considered ASDR approaches, one involves using a net as a capturing mechanism. A fundamental requirement for any ASDR mission is that the capture process itself should not give rise to new space debris. However, in simulations of net capturing, the potential for structural breaking is often overlooked. A discrete Multi-Spring-Damper net model was employed to simulate the impact of a 30 m × 30 m net travelling at 20 m/s onto an ESA Envisat mock-up. The Envisat was modelled as a two-rigid-body system comprised of the main body and a large solar array with a hinge connection. The analysis revealed that more than two significant substructures had a notable likelihood of breaking, prompting the recommendation of limiting the impacting velocity. The generation of secondary space debris indicates that net capturing is riskier than previously assumed in the literature. Full article

The automatic dependent surveillance broadcast (ADS-B) system is one of the key components of the next generation air transportation system (NextGen). ADS-B messages are transmitted in unencrypted plain text. This, however, causes significant security vulnerabilities, leaving the system open to various types of wireless attacks. In particular, the attacks can be intensified by simple hardware, like a software-defined radio (SDR). In order to provide high security against such attacks, radio frequency fingerprinting (RFF) approaches offer reasonable solutions. In this study, an RFF method is proposed for aircraft identification based on ADS-B transmissions. Initially, 3480 ADS-B samples were collected by an SDR from eight aircrafts. The power spectral density (PSD) features were then extracted from the filtered and normalized samples. Furthermore, the support vector machine (SVM) with three kernels (linear, polynomial, and radial basis function) was used to identify the aircraft. Moreover, the classification accuracy was demonstrated via varying channel signal-to-noise ratio (SNR) levels (10–30 dB). With a minimum accuracy of 92% achieved at lower SNR levels (10 dB), the proposed method based on SVM with a polynomial kernel offers an acceptable performance. The promising performance achieved with even a small dataset also suggests that the proposed method is implementable in real-world applications. Full article

There are plans to set up a space-based gravitational wave observatory that will use an ultra-large-scale laser interferometer in space to detect medium- and low-frequency gravitational waves. Both heliocentric and geocentric formations adopt the method of launching three satellites with one rocket, which has high requirements in terms of the carrying capacity of the rocket. Therefore, a proper transfer design is a prerequisite for achieving space-based gravitational wave detection. In this paper, the transfer orbit for three satellites of the Taiji mission is designed based on the two-impulse transfer model. Moreover, the influence on orbit design of the position of the formation relative to Earth, the initial phase angle of the formation, and the initial time of transfer is analyzed. The Earth-leading and -trailing transfers show opposite patterns in the above three aspects. A smaller velocity increment is required if a proper initial time is selected. After taking into account the stability of the formation, C3, the required velocity increment, transfer time, and the distance to Earth, 20° is determined to be the optimal initial trailing/leading angle. Full article

In recent years, the use of fixed-wing Unmanned Aerial Vehicles (UAVs) has expanded, and the use of fixed-wing UAVs is expected to expand due to their usefulness for long-range operations. Different from manned aircraft, no provision is required regarding climb angle at takeoff for fixed-wing UAVs. Therefore, fixed-wing UAVs can take off by taking advantage of their performance. In addition, propeller engines are the propulsion device currently used by most fixed-wing UAVs. However, the thrust force generated by a propeller engine decreases as its airspeed increases. In such circumstances, this paper describes how to derive a maximum rate of climb in which the characteristics of the propeller engine are taken into account, with the aim of reducing takeoff time by maximizing the rate of climb during takeoff. The derivation uses optimization problems with a dependency of the thrust force on the airspeed. After the derivation of the maximum rate of climb, we first checked whether the maximum rate of climb obtained for the mass system was feasible for takeoff at the rate of climb by using a 6-DOF flight simulation, and then confirmed its validity through flight experiments. Full article

The stratospheric airship is a type of aerostat that uses solar energy as its power source and can fly continuously for months or even years in near space. The rapid and accurate prediction of the output power of its solar array is the key to maintaining energy balance and extending flight time. This paper establishes an online learning model for predicting the output power of the solar array of stratospheric airships. The readings of radiometers arranged on the surface of the airship are used as features for training the model. The parameters of the model can be updated in real-time during the flight process without retraining the entire model. The effect of radiometer placement on the model accuracy was also analyzed. The results show that for the continuous flight of 40 days, the online learning model can achieve an accuracy of 88% after training with 10 days of flight data and the accuracy basically reaches its highest level after 20 days. In addition, placing the radiometers at the four corners of the array can achieve a higher prediction accuracy of 95%. The online model can also accurately identify and reflect the effect of module efficiency attenuation or damage and maintain high accuracy. Full article

The integration of uncertainty analysis methodologies allows for improving design efficiency, particularly in the context of instruments that demand precise pointing accuracy, such as space telescopes. Focusing on the VINIS Earth observation telescope developed by the Instituto de Astrofísica de Canarias (IAC), this paper reports an uncertainty analysis on a thermal model aimed at improving cost savings in the future testing phases. The primary objective was to identify critical parameters impacting thermal performance and reduce overdesign. Employing the Statistical Error Analysis (SEA) method across several operational scenarios, the research identifies key factors, including the Earth’s infrared temperature and albedo, and the spacecraft’s attitude and environmental conditions, as the variables with major influences on the system’s thermal performance. Ultimately, the findings suggest that uncertainty-based analysis is a potent tool for guiding thermal control system design in space platforms, promoting efficiency and reliability. This methodology not only provides a framework for optimizing thermal design and testing in space missions but also ensures that instruments like the VINIS telescope maintain optimal operating temperatures in diverse space environments, thereby increasing mission robustness and enabling precise resource allocation. Full article

The electric solar wind sail, or E-sail, is a propellantless interplanetary propulsion system concept. By deflecting solar wind particles off their original course, it can generate a propulsive effect with nothing more than an electric charge. The high-voltage charge is applied to one or multiple centrifugally deployed hair-thin tethers, around which an electrostatic sheath is created. Electron emitters are required to compensate for the electron current gathered by the tether. The electric sail can also be utilised in low Earth orbit, or LEO, when passing through the ionosphere, where it serves as a plasma brake for deorbiting—several missions have been dedicated to LEO demonstration. In this article, we propose the ESTCube-LuNa mission concept and the preliminary cubesat design to be launched into the Moon’s orbit, where the solar wind is uninterrupted, except for the lunar wake and when the Moon is in the Earth’s magnetosphere. This article introduces E-sail demonstration experiments and the preliminary payload design, along with E-sail thrust validation and environment characterisation methods, a cis-lunar cubesat platform solution and an early concept of operations. The proposed lunar nanospacecraft concept is designed without a deep space network, typically used for lunar and deep space operations. Instead, radio telescopes are being repurposed for communications and radio frequency ranging, and celestial optical navigation is developed for on-board orbit determination. Full article

Structural vibration has always been a major concern in the engineering field. A dynamic vibration absorber in the form of contacts with adjustable stiffness (CDVA) offers effective vibration suppression and can improve conventional dynamic vibration absorbers with high sensitivity to frequency deviation and difficulty in adjusting the frequency. In this research, first, based on the theoretical model of the contact between a rubber ball and an inner cone, the feasibility of changing the axial contact state to change the structure’s natural frequency was verified using an ANSYS simulation. A theoretical model of the static contact stiffness between the ball and the inner cone was constructed using Hertzian contact theory and Hooke’s law, and a theoretical model of the cubic nonlinear elastic restoring force was used to characterize the stiffness properties of the rubber ball during compressive rebound. The steady-state frequency response equations of the main vibration structure were derived using the averaging method in conjunction with the two-degree-of-freedom dynamics model, and the stability of the solutions to the frequency response equations was obtained in conjunction with the stability determination criterion. Then, the impact of the CDVA’s design parameters on the nonlinear dynamic response of the primary vibration structure was simulated and analyzed. The resulting findings can serve as guidance for designing dynamic vibration absorber parameters. Based on the principles of ball-inner cone contact, a dynamic vibration absorber structure was proposed. A design test was conducted to verify the correctness of the contact stiffness model, and an experimental study was carried out to investigate the law of change in the dynamic stiffness and damping of the principle structure of CDVA under dynamic excitation conditions. Finally, the vibration test platform of the solidly supported beam structure was constructed, and vibration suppression tests of the CDVA in different compression states were conducted to investigate the tunability and feasibility of CDVA vibration suppression. The results showed that the dynamic vibration absorber had good vibration absorption characteristics and could be used for single-mode vibration suppression of multimodal main structures. Full article

This paper demonstrates the utilization of Pontryagin Neural Networks (PoNNs) to acquire control strategies for achieving fuel-optimal trajectories. PoNNs, a subtype of Physics-Informed Neural Networks (PINNs), are tailored for solving optimal control problems through indirect methods. Specifically, PoNNs learn to solve the Two-Point Boundary Value Problem derived from the application of the Pontryagin Minimum Principle to the problem’s Hamiltonian. Within PoNNs, the Extreme Theory of Functional Connections (X-TFC) is leveraged to approximate states and costates using constrained expressions (CEs). These CEs comprise a free function, modeled by a shallow neural network trained via Extreme Learning Machine, and a functional component that consistently satisfies boundary conditions analytically. Addressing discontinuous control, a smoothing technique is employed, substituting the sign function with a hyperbolic tangent function and implementing a continuation procedure on the smoothing parameter. The proposed methodology is applied to scenarios involving fuel-optimal Earth−Mars interplanetary transfers and Mars landing trajectories. Remarkably, PoNNs exhibit convergence to solutions even with randomly initialized parameters, determining the number and timing of control switches without prior information. Additionally, an analytical approximation of the solution allows for optimal control computation at unencountered points during training. Comparative analysis reveals the efficacy of the proposed approach, which rivals state-of-the-art methods such as the shooting technique and the adaptive Gaussian quadrature collocation method. Full article

Hall thrusters are plasma-based devices that have established themselves as one of the most attractive and mature electric propulsion technologies for space applications. These devices often operate in a regime characterized by low frequency, large amplitude oscillations of the discharge current, which is commonly referred to as the ‘breathing mode’. The intensity of these oscillations depends on the thruster’s design and operating conditions and can reach values of the order of the average discharge current, posing issues for the thruster’s performance and for coupling with the driving electronics. A 0D model of the thruster discharge was developed to investigate the core physical mechanisms leading to the onset and sustenance of the breathing mode. The model was found to be capable of reproducing oscillations with characteristics in line with those observed in the breathing mode. In this work, we extend the use of the 0D model to investigate the effect of the magnetic field intensity and of different propellants on the system stability. Full article

The statistical analysis of civil aircraft accidents reveals that the highest incidence of mishaps occurs during the approach and landing stages. Predominantly, these accidents are marked by abnormal energy states, leading to critical situations like stalling and heavy landings. Therefore, it is of great significance to accurately predict the aircraft energy state in the approach and landing stages to ensure a safe landing. In this study, a deep learning method based on time sequence data for the prediction of the aircraft approach and landing energy states is proposed. Firstly, by conducting an extensive overview of the existing literature, three characteristic parameters of altitude, velocity, and glide angle were selected as the indicators to characterize the energy state. Following this, a semi-physical simulation platform for a certain type of aircraft was developed. The approach and landing experiments were carried out with different throttle sizes and flap deflection under different wind speeds and wind directions. Then, a deep learning prediction model based on Long Short-Term Memory (LSTM) was established based on the experimental data to predict the energy state indicators during the approach and landing phases. Finally, the established LSTM model underwent rigorous training and testing under different strategies, and a comparative analysis was carried out. The results demonstrated that the proposed LSTM model exhibited high accuracy and a strong generalization ability in predicting energy states during the approach and landing phases. These results offer a theoretical basis for designing energy early warning systems and formulating the relevant flight control laws in the approach and landing stages. Full article

Improving airflow pressure is of great significance for the cooling and sealing of aeroengines. In a co-rotating cavity with radial inflow, vortex reducers are used to decrease the pressure drop. However, the performance of traditional vortex reducers is limited by their drag reduction mechanism and cannot meet the needs of next-generation aeroengines. In this study, a novel vortex reducer (NVR) consisting of de-swirl shroud orifices and fins is proposed. Meanwhile, a design strategy is developed to ensure the NVR provides steady airflow and excellent drag reduction performance. Furthermore, experiments and numerical simulations are utilized to investigate the flow characteristics and drag reduction mechanism of the NVR. The results reveal that the de-swirl jets created by the de-swirl shroud orifices limit the enhancement of the Ekman layers at large radii, while the fins break down the high-speed vortices at small radii. Compared to a traditional finned vortex reducer with identical fins, the pressure drop of the NVR is relatively reduced by 28.52%. Specifically, the pressure drop of the NVR is monotonous in the operating range, indicating its suitability for engineering. Finally, a surrogate model and particle swarm optimization (PSO) are utilized to identify the optimal parameters of the de-swirl shroud orifices in the design range. This study provides a potential solution for the design of next-generation vortex reducers. Full article

In recent years, the interest in proximity operations to uncooperative and non-collaborative objects has been growing and and demanding for specific technology advances to tackle these challenging cases of in-orbit servicing and removal missions. Indeed, these architectures hold a crucial role in guaranteeing future sustainable and efficient space operations. One of the main challenges of conducting robotic operations with a chaser in close proximity to an uncooperative object stems from its rotational motion. A tumbling motion of a large target object may require a costly and complex synchronisation of the servicer relative trajectory to the capture point and hinder the safety of operations due to rotating appendages. In this paper, the plume impingement strategy is employed to control the target’s tumbling motion in a contactless fashion, thus guaranteeing feasible approach and capture operations. Specifically, guidance and control strategies to be employed during this delicate and complex operation are devised, focusing on improving the safety of the trajectory while maximising the efficiency of the impingement effect during proximity flight. Simulations discuss the detumbling of a satellite of a large constellation, critically comparing delta-v cost, trajectory safety and overall time of operations. Full article

This paper presents the second stage of a tandem fixed-wing unmanned aerial vehicle (UAV) aerodynamic development. In the initial stage, the UAV was optimized by analyzing its characteristics only in symmetrical flight conditions. Posted requirements were that both wings should produce relevant positive lift, the initial stall must occur on the front wing first, the center of pressure should be close to the center of gravity, and longitudinal static stability should be in the optimum range. Computational fluid dynamic (CFD) analyses were performed, where the applied calculation model was derived from the authors’ previous successful projects. The eighth version TW V8 has satisfied all longitudinal requirements. Lateral-directional CFD analyses of V8 showed that the ratio of the lateral and directional stability at the nominal cruising regime was optimal, but both lateral and directional static stabilities were too high. On further development versions, the lower vertical tail was eliminated, a negative dihedral was implemented on the front wing, and four inverted blended winglets were added. Version TW V14 has largely improved lateral and directional stability characteristics, while their optimum ratio at the cruising regime was preserved. Longitudinal characteristics were also well preserved. Maximum lift coefficient and lift-to-drag ratio were increased, compared to the V8. Full article

An increase in aircraft availability and readiness is one of the most desired characteristics of aircraft fleets. Unforeseen failures cause additional expenses and are particularly critical when thinking about combat jets and Unmanned Aerial Vehicles (UAVs). For instance, these systems are used under extreme conditions, and there can be situations where standard maintenance procedures are impractical or unfeasible. Thus, it is important to develop a Health and Usage Monitoring System (HUMS) that relies on diagnostic and prognostic algorithms to minimise maintenance downtime, improve safety and availability, and reduce maintenance costs. In particular, within the realm of aircraft structures, landing gear emerges as one of the most intricate systems, comprising several elements, such as actuators, shock absorbers, and structural components. Therefore, this work aims to develop a preliminary digital twin of a nose landing gear and implement diagnostic algorithms within the framework of the Health and Usage Monitoring System (HUMS). In this context, a digital twin can be used to build a database of signals acquired under healthy and faulty conditions on which damage detection algorithms can be implemented and tested. In particular, two algorithms have been implemented: the first is based on the Root-Mean-Square Error (RMSE), while the second relies on the Mahalanobis distance (MD). The algorithms were tested for three nose landing gear subsystems, namely, the steering system, the retraction/extraction system, and the oleo-pneumatic shock absorber. A comparison is made between the two algorithms using the ROC curve and accuracy, assuming equal weight for missed detections and false alarms. The algorithm that uses the Mahalanobis distance demonstrated superior performance, with a lower false alarm rate and higher accuracy compared to the other algorithm. Full article

Evacuation simulation is an important method for studying and evaluating the safety of passenger evacuation, and the key lies in whether it can accurately predict personnel evacuation behavior in different environments. The existing models have good adaptability in building environments but have weaker adaptability to personnel evacuation in civil aircraft cabins with more obstacles and stronger hindrances. We target the narrow seat aisle environment on airplanes and use a BP neural network to establish a continuous displacement model for personnel evacuation. We compare the simulation accuracy of evacuation time with the social force model based on continuous displacement and further compare the similarity of personnel evacuation process behavior. The results show that both models were close to the experimental values in simulating evacuation time, while our BP neural network evacuation model based on experimental data was more accurate in predicting the personnel evacuation process, showing more realistic details such as the probability of conflicts and bottleneck evolution in the cross aisle. Full article

Urban air mobility is expected to play a role in improving transportation of people and goods in growing urban areas while contributing to sustainable urban growth and zero-emissions future aviation. The research presented herein computationally investigated the performance of control laws for a generic Urban Air Taxi (UAT) subjected to empirically-developed urban airflow disturbances. This involved developing a representative flight dynamics model of a UAT in steady level cruise flight with an inner-loop autopilot. Active Disturbance Rejection Control (ADRC) and Proportional-Integral-Derivative (PID) control laws were implemented to investigate the controlled and uncontrolled acceleration responses and compare them to the acceleration limits in ISO 2631. Using a linear flight dynamics model, ADRC demonstrated improved performance over PID control with equal initial tuning effort. PID was able to reduce passenger accelerations to unharmful, though still uncomfortable, levels while ADRC further reduced the lateral accelerations to comfortable levels. Full article

In recent years, automatic speech recognition (ASR) technology has improved significantly. However, the training process for an ASR model is complex, involving large amounts of data and a large number of algorithms. The task of training a new model for air traffic control (ATC) is considerable, as it may require many researchers for its maintenance and upgrading. In this paper, we developed an improved fusion method that can adapt the language model (LM) in ASR to the domain of air traffic control. Instead of using vocabulary in traditional fusion, this method uses the ATC instructions to improve the LM. The perplexity shows that the LM of the improved fusion is much better than that of the use of vocabulary. With vocabulary fusion, the CER in the ATC corpus decreases from 0.3493 to 0.2876. The improved fusion reduces the CER of the ATC corpora from 0.3493 to 0.2761. Although there is only a difference of less than 2% between the two fusions, the perplexity shows that the LM of the improved fusion is much better. Full article

The increase in greenhouse gas emissions, as well as the risk of fossil fuel depletion, has prompted a transition to electric transportation. The European Union aims to substantially reduce pollutant emissions by 2035 through the use of renewable energies. In aviation, this transition is particularly challenging, mainly due to the weight of onboard equipment. Traditional electric motors with radial magnetic flux have been replaced by axial magnetic flux motors with reduced weight and volume, high efficiency, power, and torque. These motors were initially developed for electric vehicles with in-wheel motors but have been adapted for aviation without modifications. Worldwide, there are already companies developing propulsion systems for various aircraft categories using such electric motors. One category of aircraft that could benefit from this electric motor development is traditionally constructed training aircraft with significant remaining flight resource. Electric repowering would allow their continued use for pilot training, preparing them for future electrically powered aircraft. This article presents a study on the feasibility of repowering a classic training aircraft with an electric propulsion system. The possibilities of using either a battery or a hybrid source composed of a battery and a fuel cell as an energy source are explored. The goal is to utilize components already in production to eliminate the research phase for specific aircraft components. Full article

In the field of aircraft engine diagnostics, many advanced algorithms have been proposed over the last few years. However, there is still wide room for improvement, especially in the development of more integrated and complete engine health management systems to detect, identify, and forecast complex faults in a short time. Furthermore, it is necessary to ensure that these systems preserve their capabilities over time despite engine deterioration. This paper addresses these necessities by proposing an integrated system that considers the joint operation of feature extraction, anomaly detection, fault identification, and prognostic algorithms for engines with long operation times. To effectively reveal the actual engine condition, light adaptive degraded engine models are computed along with different health indicators that are used as inputs to train and test recognition and prediction models. The system is developed and evaluated using a specialized NASA platform which provides data from a turbofan engine fleet simultaneously experiencing long-term performance deterioration and faults. Contrary to other compared solutions, our results show that the proposed system is robust against the effects of engine deterioration, maintaining its level of detection, recognition, and prediction accuracy over a total engine service life. The low computational cost algorithms has generally fast performance in all stages, making the system suitable for online applications. Full article

Developing wind tunnel models is time consuming, labor intensive, and expensive. Rapid prototyping for wind tunnel tests is an effective, faster, and cheaper method to obtain aerodynamic performance results while considerably reducing acquisition time and cost for the models. Generally, the rapid prototyping models suffer from insufficient stiffness or strength to withstand the loads generated during a wind tunnel test. In the present study, a rapid prototype model reinforced with metallic inserts was produced to experimentally investigate the aerodynamic characteristics of an uncrewed aerial vehicle with various wingtip deflections. The fused deposition modeling process was used to make the outer mold, whereas the metallic parts were produced using laser cutting and the computer numerical control machining process. Then, the model was evaluated both experimentally and numerically. The test campaign presented in this work was conducted in the de Havilland low-speed wind tunnel facility at the University of Glasgow. For better characterization of flow patterns dominated by leading edge vortices, numerical simulations were run using OpenFOAM 8.0 and validated with experimental data. The experimental data obtained from the hybrid rapid-prototyped model agreed well with the numerical results. This demonstrates the efficacy of hybrid rapid-prototyped models in providing reliable results for initial baseline aerodynamic database development within a short period and at a reduced cost for wind tunnel tests. Full article