Hasil untuk "Motor vehicles. Aeronautics. Astronautics"

Buhong Wang, Jin Xiao, Ruochen Dong et al.

Satellite networks are essential to global connectivity yet face severe multidimensional cybersecurity threats. This systematic review conducts a holistic analysis of threats across the physical, network, and user layers. We propose the Sat-ATT&CK knowledge matrix to model satellite-specific attack chains. Corresponding defense technologies are organized within the core functions (Protect, Detect, Respond) of the National Institute of Standards and Technology (NIST) Cybersecurity Framework, establishing a structured threat–defense mapping. Furthermore, an exploratory case study on fine-tuning a large language model (SatSec) using the compiled literature corpus is presented. Finally, we identify key challenges and outline the future research directions toward a more resilient and intelligent security paradigm.

Yevhenii Kovryzhenko, Ehsan Taheri

Motion planning is critical for ensuring precise and efficient operations of unmanned aerial vehicles (UAVs). While polynomial parameterization has been the prevailing approach, its limitations in handling complex trajectory requirements have motivated the exploration of alternative methods. This paper introduces a finite Fourier series (FFS)-based trajectory parameterization for UAV motion planning, highlighting its unique capability to produce piecewise infinitely differentiable trajectories. The proposed approach addresses the challenges of fixed-time minimum-snap trajectory optimization by formulating the problem as a quadratic programming (QP) problem, with an analytical solution derived for unconstrained cases. Additionally, we compare the FFS-based parameterization with the polynomial-based minimum-snap algorithm, demonstrating comparable performance across several representative trajectories while uncovering key differences in higher-order derivatives. Experimental validation of the FFS-based parameterization using an in-house quadrotor confirms the practical applicability of the FFS-based minimum-snap trajectories. The results indicate that the proposed FFS-based parameterization offers new possibilities for motion planning, especially for scenarios requiring smooth and higher-order derivative continuity at the expense of minor increase in computational cost.

Tyrone Bright, Sarp Adali, Cristina Trois

As the generation of Municipal Solid Waste (MSW) has exponentially increased, this poses a challenge for waste managers, such as municipalities, to effectively control waste streams. If waste streams are not managed correctly, they negatively contribute to climate change, marine plastic pollution and human health effects. Therefore, waste streams need to be identified, categorised and valorised to ensure that the most effective waste management strategy is employed. Research suggests that a more efficient process of identifying and categorising waste at the source can achieve this. Therefore, the aim of the paper is to identify the state of research of AI-powered drones in identifying and categorising waste. This paper will conduct a systematic review and meta-analysis on the application of drone technology integrated with image sensing technology and deep learning methods for waste management. Different systems are explored, and a quantitative meta-analysis of their performance metrics (such as the F1 score) is conducted to determine the best integration of technology. Therefore, the research proposes designing and developing a hybrid deep learning model with integrated architecture (YOLO-Transformer model) that can capture Multispectral imagery data from drones for waste stream identification, categorisation and potential valorisation for waste managers in small-scale environments.

JIANG Lihong, FAN Lianhai, LIU Zheng et al.

B4C/TC4 titanium matrix composites are fabricated by laser-directed energy deposition（L-DED） to investigate the effect of B4C content on the microstructure and mechanical properties of the deposited layers. The results indicate that during the deposited process，B4C reacts in-situ with the TC4 matrix，generating TiC and TiB reinforcement phases. With the addition of B4C content，the hardness of the composites increases significantly，while the plasticity decreases accordingly. When the mass fraction of B4C is 0.2%，the precipitated phases of TiC and TiB exhibit the most uniform distribution. At this point，the composite achieves the highest strength while still maintaining good plasticity，demonstrating the optimal comprehensive mechanical properties. This performance optimization is mainly attributed to the synergistic effect of multiple strengthening mechanisms，including the load transfer effect of TiB phases with a high aspect ratio，the pinning effect of precipitated phases on grain boundaries and the resulting grain refinement.

Mohammad Aldossary, Ibrahim Alzamil, Jaber Almutairi

Due to Internet of Drones (IoD) technology, drone networks have proliferated, transforming surveillance, logistics, and disaster management. Distributed Denial of Service (DDoS) attacks, malware infections, and communication abnormalities increase cybersecurity dangers to these networks, threatening operational safety and efficiency. Current Intrusion Detection Systems (IDSs) fail to handle drone transmission data’s dynamic, high-dimensional nature, resulting in inadequate real-time anomaly identification and mitigation. This study presents the Cross-Layer Convolutional Attention Network (CLCAN), a new IDS architecture for IoD networks. CLCAN accurately detects complex cyber threats using multi-scale convolutional processing, hierarchical contextual attention, and dynamic feature fusion. Preprocessing methods like weighted differential scaling and gradient-based adaptive resampling improve data quality and reduce class imbalances. Contextual attribute transformation captures the nuanced network behaviors needed for anomaly identification. The proposed technique is shown to be necessary and effective by real-world drone communication dataset evaluations. CLCAN outperforms CNN, LSTM, and XGBoost with 98.4% accuracy, 98.7% recall, and 98.1% F1-score. The model has a remarkable AUC of 0.991. CLCAN can handle datasets of over 118,000 balanced data records in 85 s, compared to 180 s for comparable frameworks. This study pioneers a unified security solution for Drone-to-Drone (D2D) and Drone-to-Base Station (D2BS) communications, filling a crucial IoD security gap. It protects mission-critical drone operations with a strong, efficient, and scalable IDS from emerging cyber threats.

Jeshurun P. Horton, Jeffryes Chapman, T. Tallerico

In support of research and development for Urban Air Mobility (UAM) operations, the National Aeronautics and Space Administration (NASA) is developing a fleet of Vertical Takeoff and Landing (VTOL) concept vehicles. These vehicles aim to identify key areas for technological growth and provide reference data to the UAM community. A six-passenger Tiltwing concept recently added to the fleet offers new opportunities to explore the UAM design space through trade studies of the power and propulsion systems. In this paper, a turboelectric powertrain is designed and analyzed using the Numerical Propulsion System Simulation (NPSS) tool, the NPSS Power System Library, and a motor drivetrain optimization tool. Direct and geared motor drivetrains are designed and compared across a UAM design mission. Sensitivity of the Tiltwing maximum takeoff weight to motor drivetrain weights and efficiencies is estimated and used to inform optimal motor and gearbox selection. Results indicate that direct-drive and geared-drive configurations are comparable for this vehicle, with slight advantages to direct-drive when the radius of the drivetrain is unconstrained. When the drivetrain radius is constrained, a geared-drive system becomes more optimal.

Peter Suh, Patrick Hanlon, Keith R. Hunker et al.

This paper presents the development, verification, and validation results of an electrical Vertical Take-off and Landing (eVTOL) powertrain model. To better understand the potential impact of powertrain limitations on eVTOL aircraft handling qualities, a powertrain model was developed, integrated into revolutionary vertical lift technology (RVLT) reference vehicle designs, and tested in the National Aeronautics and Space Administration (NASA) Ames Vertical Motion Simulator (VMS). The high computational complexity required to capture the relevant powertrain physics may conflict with the ability to execute the simulation models in real time. In this paper, the authors present models and modeling decisions related to motors, batteries, and interconnections. Physics-based models and empirical models are used in tandem to support the modeling effort. Simulated motor-data comparisons are made to data collected from the NASA Scaled Power ElEctrified Drivetrain (SPEED) and Advanced Reconfigurable Electrified Aircraft Lab (AREAL) testbeds. The empirical battery model is compared to experimental 18650 battery data.

Zhe Geng, Wei Li, Xiang Yu et al.

Bistatic synthetic aperture radar (SAR) with spatially separated transmitter (TX) and receiver (RX) is advantageous over monostatic SAR systems in trajectory flexibility and antistealth/antijamming capability. On the other hand, since bistatic SAR imaging involves more technical complexities and incurs higher cost, the research in the field of bistatic automatic target recognition (ATR) has been mainly relying on simulated SAR imagery. Reckoning with the lack of supporting database in the public domain, the researchers at Nanjing University of Aeronautics and Astronautics (NUAA) constructed a proprietary bistatic SAR database featuring multiple types of representative military vehicles with the self-developed miniSAR system. Moreover, a multichannel multiview feature fusion network (MMFFN) is devised by incorporating the vision transformer (ViT). The simulation results show that the proposed MMFFN offers a classification accuracy improvement of 4.86%–16.63% over the baseline network (i.e., the plain ViT) in a series of experiments featuring small-to-large observation angle deviations between the training and test data.

Prot Piyakawanich, Pattarapong Phasukkit

In the rapidly evolving domain of Unmanned Aerial Vehicles (UAVs), precise altitude estimation remains a significant challenge, particularly for lightweight UAVs. This research presents an innovative approach to enhance altitude estimation accuracy for UAVs weighing under 2 kg without cameras, utilizing advanced AI Deep Learning algorithms. The primary novelty of this study lies in its unique integration of unsupervised and supervised learning techniques. By synergistically combining K-Means Clustering with a multiple-input deep learning regression-based model (DL-KMA), we have achieved substantial improvements in altitude estimation accuracy. This methodology represents a significant advancement over conventional approaches in UAV technology. Our experimental design involved comprehensive field data collection across two distinct altitude environments, employing a high-precision Digital Laser Distance Meter as the reference standard (Class II). This rigorous approach facilitated a thorough evaluation of our model’s performance across varied terrains, ensuring robust and reliable results. The outcomes of our study are particularly noteworthy, with the model demonstrating remarkably low Mean Squared Error (MSE) values across all data clusters, ranging from 0.011 to 0.072. These results not only indicate significant improvements over traditional methods, but also establish a new benchmark in UAVs altitude estimation accuracy. A key innovation in our approach is the elimination of costly additional hardware such as Light Detection and Ranging (LiDAR), offering a cost-effective, software-based solution. This advancement has broad implications, enhancing the accessibility of advanced UAVs technology and expanding its potential applications across diverse sectors including precision agriculture, urban planning, and emergency response. This research represents a significant contribution to the integration of AI and UAVs technology, potentially unlocking new possibilities in UAVs applications. By enhancing the capabilities of lightweight UAVs, we are not merely improving a technical aspect, but revolutionizing the potential applications of UAVs across industries. Our work sets the stage for safer, more reliable, and precise UAVs operations, marking a pivotal moment in the evolution of aerial technology in an increasingly UAV-dependent world.

Abdallah Dayhoum, Alejandro Ramirez-Serrano, Robert J. Martinuzzi

This study explores the implications of the number of blades on the performance of both open and shrouded rotors. By conducting a thorough experimental analysis at a fixed solidity ratio, this research seeks to enhance our understanding of rotor dynamics and efficiency. Two-, three-, four-, and five-bladed rotors were designed and manufactured to have the same solidity ratio. This leads to smaller chord distribution values for higher blade numbers. The experimental analysis aims to quantify the effects of the number of blades and provides a comparative analysis of performance differences between the two rotor configurations (shrouded and open). For the open rotor, results indicate that increasing the number of blades has a minimal impact on overall performance. This is due to the decrease in the tip loss factor being counterbalanced by a decline in efficiency caused by the two-dimensional airfoil performance, which results from a smaller chord and a lower Reynolds number. In contrast, the shrouded rotor exhibits a noticeable performance decay with an increased blade count. Since tip loss is inherently absent in shrouded designs, the decline is primarily attributed to the two-dimensional airfoil performance. This decay occurs while maintaining a constant solidity ratio, highlighting the significant effect of blade count on shrouded rotor efficiency, thereby contributing to the optimization of rotor design in various engineering applications.

Karen Anderson, Brandi M. Shabaga, Serge Wich et al.

Summary This journal (Drone Systems and Applications; DSA) conducted a targeted “horizon scan” during 2022 within our team of editors and associate editors. We asked—Which research areas currently under-represented in Drone Systems and Applications would you like to see more heavily represented in the future? The process highlighted five areas of interest and potential growth: Drones in the geosciences Aquatic drones Ground drones Drones within calibration/validation experiments Drones and computer vision Over the past two years (2020–22), the journal has published over 50 papers with a strong leaning towards aerial drones for ecology and also with an engineering focus. DSA is keen to receive new submissions addressing the five highlighted areas, which lie firmly within the aims and scope of the journal. Further to the horizon scan, we propose two special collections for the coming year—one addressing drone applications (drones in geoscience applications) and a second addressing drone systems (aquatic drone systems). We would like to hear from scientists and practitioners in these fields as both contributors and (or) collection editors.

Hassan Waqas, Shan Ali Khan, Bagh Ali et al.

The current article investigates the numerical study of the micropolar nanofluid flow through a 3D rotating surface. This communication may manipulate for the aim such as the delivery of the drug, cooling of electronic chips, nanoscience and the fields of nanotechnology. The impact of heat source/sink is employed. Brownian motion and thermophoresis aspects are discussed. The rotating sheet with the impacts of Darcy-Forchheimer law is also scrutinized. Furthermore, the influence of activation energy is analyzed in the current article. The numerical analysis is simplified with the help of befitted resemblance transformations. The succor of the shooting algorithm with built-in solver bvp4c MATLAB software is used for the numerical solution of nonlinear transformed equations. The consequences of different physical factors on the physical engineering quantities and the subjective fields were examined and presented. According to outcomes, it can be analyzed that the flow profile declined with the rotational parameter. It is observed that angular velocity diminishes via a larger porosity parameter. Furthermore, the temperature gradient is declined via a larger magnitude of the Prandtl number. The heat transfer is enhanced in the occurrence of Brownian motion. The activations energy parameter causes an increment in the volumetric concentration field. Moreover, the local Nusselt number is reduced via a greater estimation of the porosity parameter.

Xing Yang, Hang Wu, Zhenping Feng

In this paper, detailed flow patterns and heat transfer characteristics of a jet impingement system with extended jet holes are experimentally and numerically studied. The jet holes in the jet plate present an inline array of 16 × 5 rows in the streamwise (i.e., the crossflow direction) and spanwise directions, where the streamwise and spanwise distances between adjacent holes, which are normalized by the jet hole diameter (<i>x</i>_n/<i>d</i> and <i>y</i>_n/<i>d</i>), are 8 and 5, respectively. The jets impinge onto a smooth target plate with a normalized distance (<i>z</i>_n/<i>d</i>) of 3.5 apart from the jet plate. The jet holes are extended by inserting stainless tubes throughout the jet holes and the extended lengths are varied in a range of 1.0<i>d</i>–2.5<i>d</i>, depending on the jet position in the streamwise direction. The experimental data is obtained by using the transient thermochromic liquid crystal (TLC) technique for wide operating jet Reynolds numbers of (1.0 × 10⁴)–(3.0 × 10⁴). The numerical simulations are well-validated using the experimental data and provide further insight into the flow physics within the jet impingement system. Comparisons with a traditional baseline jet impingement scheme show that the extended jet holes generate much higher local heat transfer levels and provide more uniform heat transfer distributions over the target plate, resulting in the highest improvement of approximately 36% in the Nusselt number. Although the extended jet hole configuration requires a higher pumping power to drive the flow through the impingement system, the gain of heat transfer prevails over the penalty of flow losses. At the same pumping power consumption, the extended jet hole design also has more than 10% higher heat transfer than the baseline scheme.

M. Cardone, Bonaventura Gargiulo, E. Fornaro

This article presents a numerical model of an aeronautical hybrid electric propulsion system (HEPS) based on an energy method. This model is designed for HEPS with a total power of 100 kW in a parallel configuration intended for ultralight aircraft and unmanned aerial vehicles (UAV). The model involves the interaction between the internal combustion engine (ICE), the electric motor (EM), the lithium battery and the aircraft propeller. This paper also describes an experimental setup that can reproduce some flight phases, or entire missions, for the reference aircraft class. The experimental data, obtained by reproducing two different take-offs, were used for model validation. The model can also simulate anomalous operating conditions. Therefore, the tests chosen for the model validation are characterized by the EM flux weakening (“de-fluxing”). This model is particularly suitable for preliminary stages of design when it is necessary to characterize the hybrid system architecture. Moreover, this model helps with the choice of the main components (e.g., ICE, EM, and transmission gear ratio). The results of the investigation conducted for different battery voltages and EM transmission ratios are shown for the same mission. Despite the highly simplified model, the average margin of error between the experimental and simulated results was generally under 5%.

N. V. Sokolov, M. B. Khadiev, P. E. Fedotov et al.

The article presents the basic principles of three-dimensional mathematical modeling of the operation of a thrust plain bearing with fixed pads of the compressor. The model is based on the periodic thermoelastichydrodynamic (PTEHD) theory which allows calculating the temperature at the inlet to the pad and considering the complete thermal pattern. A description of the main provisions of the numerical implementation is given. In the stationary mode of the bearings operation, using the Sm2Px3Tx program, numerical experiments were carried out aimed at studying different boundary conditions to the Reynolds equation, the physics of the hydrodynamic process in the lubricating and boundary films of the bearing and the heat propagation in the body of the pad and thrust collar.

JoungSoon Jang

For nonsmall cell lung cancer (NSCLC), surgery is indicated only for stage 3 as a curative measure. Even so, there is a high risk of recurrence following stage 3 lung cancer surgery, a third (33.9%) of patients experienced a cancer recurrence mostly within 2 years after surgery. The median survival time for all stages reaches only 21.9 months. For people undergoing surgery for stage 3A NSCLC, a pre-operative course of (neoadjuvant chemotherapy) can improve survival times, by improving the resectability and lowering the risk of recurrence. Pleural metastases are frequently associated with tumors of the lung and breast. Chest radiographs and computed tomography scans of pleural metastases can present as an effusion or smooth or nodular pleural thickening. In the absence of irregular or nodular pleural thickening, it is difficult to distinguish a benign from a malignant pleural effusion. To treat lung cancer, tyrosine kinase inhibitors (TKIs) recently have been used to cope with genetic mutations, apart from cytotoxic anticancer drugs. Compared to cytotoxic drugs, they are effective, have fewer side effects, and are easy to administer. Airman must have no cancer disease to apply for Class-I medical certification. Specifically, if previously operated on cancer, the cancer should not remain in the body at present, and the disease free state should persist at least one year after all kinds of anti-cancer treatments including adjuvant chemotherapy are completed. Here, this case deals with a 41-year-old pilot who has ATP license who had stage 3A NSCLC. The pilot underwent curative lung cancer surgery (lobectomy) a year ago and showed suspicious pleural metastasis at the time of his application for certification and was still using an unauthorized TKI agent alectinib (Alecensa; Roche, Basel, Switzerland).

Galen Richardson, Sylvain G. Leblanc, Julie Lovitt et al.

Relating ground photographs to UAV orthomosaics is a key linkage required for accurate multi-scaled lichen mapping. Conventional methods of multi-scaled lichen mapping, such as random forest models and convolutional neural networks, heavily rely on pixel DN values for classification. However, the limited spectral range of ground photos requires additional characteristics to differentiate lichen from spectrally similar objects, such as bright logs. By applying a neural network to tiles of a UAV orthomosaics, additional characteristics, such as surface texture and spatial patterns, can be used for inferences. Our methodology used a neural network (UAV LiCNN) trained on ground photo mosaics to predict lichen in UAV orthomosaic tiles. The UAV LiCNN achieved mean user and producer accuracies of 85.84% and 92.93%, respectively, in the high lichen class across eight different orthomosaics. We compared the known lichen percentages found in 77 vegetation microplots with the predicted lichen percentage calculated from the UAV LiCNN, resulting in a R² relationship of 0.6910. This research shows that AI models trained on ground photographs effectively classify lichen in UAV orthomosaics. Limiting factors include the misclassification of spectrally similar objects to lichen in the RGB bands and dark shadows cast by vegetation.

Benedikt Reick, Anja Konzept, André Kaufmann et al.

Due to increasing sales figures, the energy consumption of battery-electric vehicles is moving further into focus. In addition to efficient driving, it is also important that the energy losses during AC charging are as low as possible for a sustainable operation. In many situations it is not possible or necessary to charge the vehicle with the maximum charging power e.g., in apartment buildings. The influence of the charging mode (number of phases used, in-cable-control-box or used wallbox, charging current) on the charging efficiency is often unknown. In this work, the energy consumption of two electric vehicles in the Worldwide Harmonized Light-Duty Vehicles Test Cycle is presented. In-house developed measurement technology and vehicle CAN data are used. A detailed breakdown of charging losses, drivetrain efficiency, and overall energy consumption for one of the vehicles is provided. Finally, the results are discussed with reference to avoidable CO<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mrow></mrow><mn>2</mn></msub></semantics></math></inline-formula> emissions. The charging losses of the tested vehicles range from 12.79 to 20.42%. Maximum charging power with three phases and 16 A charging current delivers the best efficiencies. Single-phase charging was considered down to 10 A, where the losses are greatest. The drivetrain efficiency while driving is 63.88% on average for the WLTC, 77.12% in the “extra high” section and 23.12% in the “low” section. The resulting energy consumption for both vehicles is higher than the OEM data given (21.6 to 44.9%). Possible origins for the surplus on energy consumption are detailed. Over 100,000 km, unfavorable charging results in additional CO<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mrow></mrow><mn>2</mn></msub></semantics></math></inline-formula> emissions of 1.24 t. The emissions for an assumed annual mileage of 20,000 km are three times larger than for a class A+ refrigerator. A classification of charging modes and chargers thus appears to make sense. In the following work, efficiency improvements in the charger as well as DC charging will be proposed.

O. Gohardani, M. Elola, C. Elizetxea

Soumya Vasisht