This study presents an integrated optimization framework for fleet assignment, flight scheduling, and aircraft routing under uncertainty, addressing a core challenge in airline operational planning. A three-stage stochastic mixed-integer nonlinear programming model is developed that, for the first time, simultaneously incorporates station purity constraints, codeshare agreements, and overbooking decisions. The formulation also includes realistic operational factors such as stochastic passenger demand and non-cruise times (NCT), along with adjustable cruise speeds and flexible departure time windows. To handle the computational complexity of this large-scale stochastic problem, a Sample Average Approximation (SAA) scheme is combined with two tailored metaheuristic algorithms: Simulated Annealing and Cuckoo Search. Extensive experiments on real-world flight data demonstrate that the proposed hybrid approach achieves tight optimality gaps below 0.5%, with narrow confidence intervals across all instances. Moreover, the SA-enhanced method consistently yields superior solutions compared with the CS-based variant. The results highlight the significant operational and economic benefits of jointly optimizing codeshare decisions, station purity restrictions, and overbooking policies. The proposed framework provides a scalable and robust decision-support tool for airlines seeking to enhance resource utilization, reduce operational costs, and improve service quality under uncertainty.
Low-Reynolds-number propeller systems have been widely used in aeronautical applications, such as unmanned aerial vehicles (UAV) and electric propulsion systems. However, the aerodynamic sound of the propeller systems is often significant and can lead to aircraft noise problems. Therefore, effective predictions of propeller noise are important for designing aircraft, and the different phases in aircraft design require specific prediction approaches. This paper aimed to perform a comparison study on numerical methods at different fidelity levels for predicting the aerodynamic noise of low-Reynolds-number propellers. The Ffowcs-Williams and Hawkings (FWH), Hanson, and Gutin methods were assessed as, respectively, high-, medium-, and low-fidelity noise models. And a coarse-grid large eddy simulation was performed to model the propeller aerodynamics and to inform the three noise models. A popular propeller configuration, which has been used in previous experimental and numerical studies on propeller noise, was employed. This configuration consisted of a two-bladed propeller mounted on a cylindrical nacelle. The propeller had a diameter of <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>D</mi><mo>=</mo><msup><mn>9</mn><mrow><mo>″</mo></mrow></msup></mrow></semantics></math></inline-formula> and a pitch-to-diameter ratio of <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>P</mi><mo>/</mo><mi>D</mi><mo>=</mo><mn>1</mn></mrow></semantics></math></inline-formula>, and was operated in a forward-flight condition with a chord-based Reynolds number of <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>R</mi><mi>e</mi><mo>=</mo><mn>4.8</mn><mo>×</mo><msup><mn>10</mn><mn>4</mn></msup></mrow></semantics></math></inline-formula>, a tip Mach number of <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>M</mi><mo>=</mo><mn>0.231</mn></mrow></semantics></math></inline-formula>, and an advance ratio of <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>J</mi><mo>=</mo><mn>0.485</mn></mrow></semantics></math></inline-formula>. The results were validated against existing experimental measurements. The propeller flow was characterized by significant tip vortices, weak separation over the leading edges of the blade suction sides, and small-scale vortical structures from the blade trailing edges. The far-field noise was characterized by tonal noise, as well as broadband noise. The mechanism of the noise generation and propagation were clarified. The capacities of the three noise modeling methods for predicting such propeller noise were evaluated and compared.
António André C. Freitas, Victor Wilson G. Azevedo, Vitor Hugo A. Aguiar
et al.
Unmanned Aerial Vehicles (UAVs) have become indispensable across various industries, but their efficiency, particularly in multirotor designs, remains constrained by aerodynamic limitations. This study investigates the integration of airfoil shapes into the arms of multirotor UAV frames to enhance aerodynamic performance, thereby improving energy efficiency and extending flight times. By employing Computational Fluid Dynamics (CFD) simulations, this research compares the aerodynamic characteristics of a standard quadrotor frame against an airfoil-integrated design. The results reveal that while airfoil-shaped arms marginally increase drag in cruise flight, they significantly reduce downforce across all flight conditions, optimizing thrust utilization and lowering overall energy consumption. The findings suggest potential applications in military reconnaissance, agriculture, and other fields requiring longer UAV flight durations and improved efficiency. This work advances UAV design by demonstrating a feasible method for enhancing the performance of multirotor systems while maintaining structural simplicity and cost-effectiveness.
This study presents a cooperative system where drones and ground robots share information to efficiently complete tasks in environments that challenge the capabilities of a single robot. Drones focus on exploring high-interest areas for ground robots, generating occupancy grid maps and identifying high-risk routes. Ground robots use this information to evaluate and adapt routes as needed. Flexible action planning through behavior trees enables the robots to respond dynamically to environmental changes, facilitating spontaneous and adaptable cooperation. Experiments with real robots confirmed the system’s performance and adaptability to various settings. Specifically, when high-risk areas were identified from drone provided information, ground robots generated alternative routes to bypass these zones, demonstrating the system’s capacity to navigate complex paths while minimizing risks. This establishes a basis for scaling to larger environments. The proposed system is expected to improve the safety and efficiency of robot operations by enabling multiple robots to accomplish complex tasks collaboratively-tasks that would be difficult or time consuming for an individual robot. The findings demonstrate the potential for multi-robot cooperation to enhance task execution in challenging environments and provide a framework for future research on effective role sharing and information exchange in autonomous systems.
Software-in-the-loop simulation tools have been extensively used in the development of safety-critical software. Utilizing these tools substantially accelerates software development, eliminating potential risks and resource costs of physical experiments. This paper investigates the effects of model-specific parameters on the development and testing of custom modules in a simulation environment. Models of a fixed-wing unmanned aerial vehicle with vertical takeoff and landing capabilities and a steerable sensor platform/gimbal are used as a case study for this investigation. The effects of parameters of these aerial vehicle and sensor platform models are taken into consideration in the development of a custom module that is incorporated into PX4 Autopilot and controls the dynamics of the steerable sensor platform mounted on the vehicle model. The work also presents steps necessary to customize the PX4 Autopilot software-in-the-loop tool and Gazebo simulation environment to incorporate parameters of the vehicle and sensor platform models in the development and testing process of the custom module. Based on these instances, simulation results are obtained and discussed. The results show that the effective use of the PX4 Autopilot software-in-the-loop simulation framework is justified by its proper customization and integration with the Gazebo simulator.
The new deployment system for a precise rigid petal reflector is proposed and investigated. The deployment of the reflector is performed in two stages. At the first stage, the reflector is transferred from the folded (transport) state to a state close to the deployed (working) one. At the second stage, a high-precision fixation of the final deployed state is performed. To achieve this, a new type of self-setting locks based on kinematic couplings of a novel design is used. Results of computer simulations of the new deployment system are presented. To validate the proposed technical solutions, a physical model of the reflector with a diameter of one meter, consisting of twenty-three petals and a central mirror, was manufactured. This model serves as an experimental platform for testing deployment kinematics, evaluating structural stiffness, and assessing deployment repeatability. Results of both computer and physical simulations are discussed. The problem of numerical measurement of deployment repeatability is addressed. An optical 3D scanning method is employed for this purpose. Measurement results of the physical model demonstrate that the self-setting locks ensure petal positioning accuracy at the level of 0.1 mm without active mirror shape correction.
Temperature distribution inside the vacuum chamber of the TRX 2000(A) near space environment simulation test system (NSESTS) was investigated through both experimentation and computational fluid dynamics simulation. Comparison between the experimental result and the simulation result showed that these two results were very close to each other, validating the feasibility of using the simulation method to study the temperature distribution inside the NSESTS. Then, the effect of wind, either downwind or upwind, on temperature uniformity inside the NSESTS was investigated through the simulation method. The simulation result showed that the non-uniformity coefficient will be reduced from 0.2757 to 0.2012 (by 27.1%) in the case of downwind and to 0.2055 (by 25.5%) in the case of upwind. Then, the simulation result was validated by experiment. The result of this research indicates that the temperature uniformity can be greatly improved through installment of additional fans inside the NSESTS.
Wide-body aircraft is the key technical product in the field of civil aviation. The development of wide-body aircraft is the important reflection of national comprehensive strength, as well as the inevitable course to achieve technological autonomy. This paper provides systematic review on the current status and future trend of key technologies for wide-body aircraft in the field of aerodynamics, structure, strength, power plant and main airborne systems, based on the analysis on global wide-body aircraft development. Key technological breakthroughs for wide-body aircraft will primarily focus on areas such as aerodynamic design of high aspect ratio wing with variable camber, nonlinear static aeroelastic design with large deformation, fly-by-wire control law design with more advanced functions, large-scale application of advanced composite structure, structural health monitoring, cockpit integrated warning systems, multi-mode and multi-orbit satellite communication and closed-loop attitude control in flight control systems, etc.
Soulaimane Idiri, Mohammed Said Boukhryss, Abdellah Azmani
et al.
This paper details the development of an embedded system for vehicle data acquisition using the On-Board Diagnostics version 2 (OBD2) protocol, with the objective of predicting power loss caused by exhaust gas backpressure (EBP). The system decodes and preprocesses vehicle data for subsequent analysis using predictive artificial intelligence algorithms. MATLAB’s 2023b Powertrain Blockset, along with the pre-built “Compression Ignition Dynamometer Reference Application (CIDynoRefApp)” model, was used to simulate engine behavior and its subsystems. This model facilitated the control of various engine subsystems and enabled simulation of dynamic environmental factors, including wind. Manipulation of the exhaust backpressure orifice revealed a consistent correlation between backpressure and power loss, consistent with theoretical expectations and prior research. For predictive analysis, two deep learning models—Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU)—were applied to the generated sensor data. The models were evaluated based on their ability to predict engine states, focusing on prediction accuracy and performance. The results showed that GRU achieved lower Mean Absolute Error (MAE) and Mean Squared Error (MSE), making GRU the more effective model for power loss prediction in automotive applications. These findings highlight the potential of using synthetic data and deep learning techniques to improve predictive maintenance in the automotive industry.
Mechanical engineering and machinery, Machine design and drawing
The Cislunar economy is thriving with innovative space systems and operation techniques to enhance and uplift the traditional approaches significantly. This paper brings about an approach for sustainable small satellite constellations to retain autonomy for long-term missions in the Cislunar space. The methodology presented is to align the hybrid model of the constellation for Earth and Moon as an integral portion of the Cislunar operations. These hybrid constellations can provide a breakthrough in optimally utilizing the Cislunar space to efficiently deploy prominent missions to be operated and avoid conjunction or collisions forming additional debris. Flower and walker constellation patterns have been combined to form a well-defined orientation for these small satellites to operate and deliver the tasks satisfying the mission objectives. The autonomous multi-parametric analysis for each constellation based in Earth and Moon’s environment has been attained with due consideration to local environments. Specifically, the Solar Radiation Pressure (SRP) is a critical constraint in Cislunar operations and is observed during simulations. These are supported by conjunction analysis using the Monte Carlo technique and also the effect of the SRP on the operating small satellites in real-time scenarios. This is followed by the observed conclusions and the way forward in this fiercely competent Cislunar operation.
Abdullah Alawadhi, Constantine Eliopoulos, Frederic Bezombes
For the first time, RGB and multispectral sensors deployed on UAVs were used to facilitate grave detection in a desert location. The research sought to monitor surface anomalies caused by burials using manual and enhanced detection methods, which was possible up to 18 months. Near-IR (NIR) and Red-Edge bands were the most suitable for manual detection, with a 69% and 31% success rate, respectively. Meanwhile, the enhanced method results varied depending on the sensor. The standard Reed–Xiaoli Detector (RXD) algorithm and Uniform Target Detector (UTD) algorithm were the most suitable for RGB data, with 56% and 43% detection rates, respectively. For the multispectral data, the percentages varied between the algorithms with a hybrid of the RXD and UTD algorithms yielding a 56% detection rate, the UTD algorithm 31%, and the RXD algorithm 13%. Moreover, the research explored identifying grave mounds using the normalized digital surface model (nDSM) and evaluated using the normalized difference vegetation index (NDVI) in grave detection. nDSM successfully located grave mounds at heights as low as 1 cm. A noticeable difference in NDVI values was observed between the graves and their surroundings, regardless of the extreme weather conditions. The results support the potential of using RGB and multispectral sensors mounted on UAVs for detecting burial sites in an arid environment.
Nyo Me Htun, Toshiaki Owari, Satoshi Tsuyuki
et al.
Uneven-aged mixed forests have been recognized as important contributors to biodiversity conservation, ecological stability, carbon sequestration, the provisioning of ecosystem services, and sustainable timber production. Recently, numerous studies have demonstrated the applicability of integrating remote sensing datasets with machine learning for forest management purposes, such as forest type classification and the identification of individual trees. However, studies focusing on the integration of unmanned aerial vehicle (UAV) datasets with machine learning for mapping of tree species groups in uneven-aged mixed forests remain limited. Thus, this study explored the feasibility of integrating UAV imagery with semantic segmentation-based machine learning classification algorithms to describe conifer and broadleaf species canopies in uneven-aged mixed forests. The study was conducted in two sub-compartments of the University of Tokyo Hokkaido Forest in northern Japan. We analyzed UAV images using the semantic-segmentation based U-Net and random forest (RF) classification models. The results indicate that the integration of UAV imagery with the U-Net model generated reliable conifer and broadleaf canopy cover classification maps in both sub-compartments, while the RF model often failed to distinguish conifer crowns. Moreover, our findings demonstrate the potential of this method to detect dominant tree species groups in uneven-aged mixed forests.
Ermioni Qafzezi, Kevin Bylykbashi, Shunya Higashi
et al.
Vehicular Ad Hoc Networks (VANETs) have gained significant attention due to their potential to enhance road safety, traffic efficiency, and passenger comfort through vehicle-to-vehicle and vehicle-to-infrastructure communication. However, VANETs face resource management challenges due to the dynamic and resource constrained nature of vehicular environments. Integrating cloud-fog-edge computing and Software-Defined Networking (SDN) with VANETs can harness the computational capabilities and resources available at different tiers to efficiently process and manage vehicular data. In this work, we used this paradigm and proposed an intelligent approach based on Fuzzy Logic (FL) to evaluate the processing and storage capability of vehicles for helping other vehicles in need of additional resources. The effectiveness of the proposed system is evaluated through extensive simulations and a testbed. Performance analysis between the simulation results and the testbed offers a comprehensive understanding of the proposed system and its performance and feasibility.
Mechanical engineering and machinery, Machine design and drawing
Currently, the borescope is the most used method with non-destructive testing in the process of aero-engine inspections and is the only way to obtain borescope images. In recent years, the artificial intelligence technologies such as deep learning are applied to aero-engine damage classification and detection, and some effective methods are proposed to achieve intelligent inspection of aero-engines, which have significant value for industrial applications. The benefits and disadvantages of aero-engine borescope inspection and its development are reviewed. The progress in the application of artificial intelligence technologies such as expert system and machine learning to engine borescope detection images is over-viewed. Some of the challenges in achieving intelligent aero-engine borescope inspection are summarized.
Contrapose the highly integrated, multiple types of faults and complex working conditions of aircraft electro hydrostatic actuator (EHA), to effectively identify its typical faults, we propose a fault diagnosis method based on fusion convolutional neural networks (FCNN). First, the aircraft EHA fault data is encoded by gram angle difference field (GADF) to obtain the fault feature images. Then we build a FCNN model that integrates the 1DCNN and 2DCNN, where the original 1D fault data is the input of the 1DCNN model, and the feature images obtained by GADF transformation are used as the input of 2DCNN. Multiple convolution and pooling operations are performed on each of these inputs to extract the features. Next these feature vectors are spliced in the convergence layer, and the fully connected layers and the Softmax layers are finally used to attain the classification of aircraft EHA faults. Furthermore, the multi-strategy hybrid particle swarm optimization (MSPSO) algorithm is applied to optimize the FCNN to obtain a better combination of FCNN hyperparameters; MSPSO incorporates various strategies, including an initialization strategy based on homogenization and randomization, and an adaptive inertia weighting strategy, etc. The experimental result indicates that the FCNN model optimized by MSPSO achieves an accuracy of 96.86% for identifying typical faults of the aircraft EHA, respectively, higher than the 1DCNN and the 2DCNN by about 16.5% and 5.7%. By comparing with LeNet-5, GoogleNet, AlexNet, and GRU, the FCNN model presents the highest diagnostic accuracy, less time in training and testing. The comprehensive performance of the proposed model is demonstrated to be much stronger. Additionally, the FCNN model improved by MSPSO has a higher accuracy rate when compared to PSO.
This work presents a systematic approach to analyzing the aerodynamic characteristics of tandem rotor forward autorotation considering rotor-to-rotor interference. The single-rotor computational model trimmed from a generic helicopter flight dynamics analysis program was used as the baseline model. The effectiveness of the baseline model is demonstrated by a comparison with data from wind tunnel tests performed in this work. The rotor disk angle of attack and driven moment distribution obtained by the modified model indicate the fact that the rotor acceleration is primarily caused by the higher angle of attack region of the disk. This is of great significance in the rotor blade design, in terms of the drag-to-lift ratio characteristics of the airfoil under different angle-of-attack ranges. The influence of wind speed, rotor shaft angle, and collective pitch on the steady-state rotor speed was then studied. The results show a nonlinear nature of the variation of steady rotor speed with collective pitch, which can cause a thrust control reverse problem during flight operations. To reveal the flow field details of rotor-to-rotor interference, the flow field Navier–Stokes equations of tandem rotor autorotation were solved. Computational results of both rotors’ inflow velocities were considered when deriving the empirical model of interference. The refined interference model was compared to the wind tunnel test data of the tandem rotor autorotation and showed good performance. This synthetical methodology, which combines mechanism analysis with CFD-aided refinement and experiment verification, achieves a balance between computational costs and accuracy and thus can be readily applied to engineering practices.
A noncircular engine cross-section could provide great flexibility in the integration of propulsion into the airframe. In this work, a tri-arc RDE was constructed and tested as an example of noncircular cross-sectioned RDE. The operational characteristics of detonation wave propagation and thrust performance were investigated and compared with an equivalent circular RDE under the same operating conditions. High-speed camera images, short-time Fourier transform (STFT), and fast Fourier transform (FFT) were used for the investigation. The tri-arc RDE showed very similar characteristics to the circular RDE but exhibited slightly better stability and propulsion performance than the circular RDE. We consider that repeated curvature changes positively affect the stability of detonation wave propagation. The experimental data show contradicting results from the numerical analysis with a homogeneous mixture assumption in which the detonation pressures at the convex corner were greater than those at the concave corner. It is reasoned that the tri-arc injector design provides a non-uniform mixture composition, resulting in a strong detonation at the convex corner. Overall, the noncircular RDE of a tri-arc shaped cross-section is demonstrated, one which performs slightly better than an ordinary circular-shaped RDE both in detonation stability and performance.
Shen Pengfei, Wu Wei, Huang Yimin, Wei Zhongwei, Luo Chuyang, Pan Lijian
The flutter analysis model of composite rudder is established, and the flutter velocity at ambient temperature is calculated, the influence of the layup scheme on the flutter characteristics of the composite rudder is studied. The results show that the flutter velocity of the composite rudder is 575.8 m/s at sea level, and flutter coupling form of the composite rudder is a typical bending and torsional modal coupling. The flutter velocity of composite rudder increases with the flight height, and it is related to the frequency difference between the first-order modal and the second-order modal. When the frequency difference between the first-order modal and the second-order modal increases, the flutter velocity of the composite rudder increases correspondingly. The frequency difference between the first-order modal and the second-order modal is increased by adjusting the layup angle, layup proportion and layup sequence, thereby the flutter velocity of the composite rudder can be increased.
Numerical simulations are crucial for fast and accurate estimations of the flow characteristics in many engineering applications such as atmospheric boundary layers around buildings, external aerodynamics around vehicles, and pollutant dispersion. In the simulation of flow over urban-like obstacles, it is crucial to accurately resolve the flow characteristics with reasonable computational cost. Therefore, Large Eddy Simulations on non-uniform grids are usually employed. However, an undesirable accumulation of energy at grid-refinement interfaces was observed in previous studies using non-uniform grids. This phenomenon induced oscillations in the spanwise velocity component, mainly on fine-to-coarse grid interfaces. In this study, the two challenging test cases of flow over urban-like cubes and flow over a 3-D circular cylinder were simulated using three different scale-resolving turbulence models. Simulations were performed on uniform coarse and fine grids on one hand, and a non-uniform grid on the other, to assess the effect of mesh density and mesh interfaces on the models’ performance. Overall, the proposed One-Equation Scale-Adaptive Simulation (One-Equation SAS) showed the least deviation from the experimental results in both tested cases and on all grid sizes and types when compared to the Shear Stress Transport-Improved Delayed Detached Eddy Simulation (IDDES) and the Algebraic Wall-Modeled Large Eddy Simulation (WMLES).