GaN-HEMTs on silicon (Si) or SiC or sapphire substrates are growing in popularity and is expected to completely transform the power electronics industry. Although GaN HEMTs operate in D-Mode by default, E-Mode operation is necessary for ease of IC design, low power consumption and safe operation. p-GaN gated HEMTs offer a breakdown voltage (V ${}_{\mathrm {BR}}$ ), transconductance (g ${}_{\mathrm {m}}$ ), power added efficiency (PAE) and ON-current (I ${}_{\mathrm {ON}}$ ) of over 2230 V, 205 mS/mm, 55.4 % and 1 A/mm, respectively, which makes them highly suitable for future RF-power switching applications. The time-dependent breakdown of the AlGaN-p-GaN/metal stack (due to avalanche multiplication) is a serious reliability concern in p-GaN HEMTs. Material defects, back gate effects, gate leakage, bias stress effects, ESD & short circuit failures, radiation effects and thermal effects are also important reliability concerns that can result in performance degradation, including current collapse, reduced breakdown voltage, increased on-resistance and device failure. Mechanisms like interface states, ion migration, and electron trapping are also crucial to the aging of p-GaN HEMTs. Understanding these reliability issues and degradation mechanisms is critical for enhancing the robustness of p-GaN HEMTs in power electronics and RF applications. Therefore, this article reviews the reliability issues and various degradation mechanisms of p-GaN gated E-Mode HEMTs such as forward/reverse bias stress effects, back gate effects, current collapse, charge trapping effects, radiation effects, short circuit (SC) & electrostatic discharge (ESD) failures and high temperature reliability issues. RON degradation, gate breakdown, PBTI and NBTI remains serious concerns in the development of p-GaN gated E-Mode HEMTs for future consumer electronics, wireless networks, industrial motors, electric vehicles and space/aeronautic applications.
Yubin Zhong, Fabrizio Ponti, Francesco Barato
et al.
As a cost-effective and versatile solution, small satellites are increasingly being considered for space exploration. However, one of the major challenges in deploying small satellites for high total impulse missions, particularly deep space exploration, lies in the propulsion system. These missions face strict constraints in terms of volume, mass, and power budgets. This paper proposes a potential solution to this issue through the design of a bipropellant MEMS thruster. Simulation results indicate that this type of thruster offers superior performance compared to the monopropellant propulsion systems typically used in small satellite missions. Specifically, the bipropellant MEMS thruster demonstrates enhanced specific impulse and thrust-to-weight ratio, making it a promising alternative for small satellite propulsion in high total impulse missions.
In this paper, we propose a cooperative security method for unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs) based on the Multi-Agent Deep Deterministic Policy Gradient (MADDPG) algorithm to address the scenario of unauthorized rogue drones (RDs) intruding into an airport’s restricted airspace. The proposed method integrates artificial intelligence techniques with engineering solutions to enhance the autonomy and effectiveness of air–ground cooperation in airport security. Specifically, the MADDPG algorithm enables the Security Interception UAVs (SI-UAVs) to autonomously detect and counteract RDs by optimizing their decision-making processes in a multi-agent environment. Additionally, Particle Swarm Optimization (PSO) is employed for distance-based target assignment, allowing each SI-UAV to autonomously select intruder targets based on proximity. To address the challenge of limited SI-UAV flight range, a power replenishment mechanism is introduced, where each SI-UAV automatically returns to the nearest UGV for recharging after reaching a predetermined distance. Meanwhile, UGVs perform ground patrols across different airport critical zones (e.g., runways and terminal perimeters) according to pre-designed patrol paths. The simulation results demonstrate the feasibility and effectiveness of the proposed security strategy, showing improvements in the reward function and the number of successful interceptions. This approach effectively solves the problems of target allocation and limited SI-UAV range in multi-SI-UAV-to-multi-RD scenarios, further enhancing the autonomy and efficiency of air–ground cooperation in ensuring airport security.
Kaleab A. Kinfu, Carolina Pacheco, Alice D. Sperry
et al.
Motor imitation impairments are commonly reported in individuals with autism spectrum conditions (ASCs), suggesting that motor imitation could be used as a phenotype for addressing autism heterogeneity. Traditional methods for assessing motor imitation are subjective, labor-intensive, and require extensive human training. Modern Computerized Assessment of Motor Imitation (CAMI) methods, such as CAMI-3D for motion capture data and CAMI-2D for video data, are less subjective. However, they rely on labor-intensive data normalization and cleaning techniques, and human annotations for algorithm training. To address these challenges, we propose CAMI-2DNet, a scalable and interpretable deep learning-based approach to motor imitation assessment in video data, which eliminates the need for data normalization, cleaning and annotation. CAMI-2DNet uses an encoder-decoder architecture to map a video to a motion encoding that is disentangled from nuisance factors such as body shape and camera views. To learn a disentangled representation, we employ synthetic data generated by motion retargeting of virtual characters through the reshuffling of motion, body shape, and camera views, as well as real participant data. To automatically assess how well an individual imitates an actor, we compute a similarity score between their motion encodings, and use it to discriminate individuals with ASCs from neurotypical (NT) individuals. Our comparative analysis demonstrates that CAMI-2DNet has a strong correlation with human scores while outperforming CAMI-2D in discriminating ASC vs NT children. Moreover, CAMI-2DNet performs comparably to CAMI-3D while offering greater practicality by operating directly on video data and without the need for ad-hoc data normalization and human annotations.
Hironori Nakajima, Shuya Wada, Takumi Matsuda
et al.
We focus on the design of a pressurized solid oxide fuel cell integrated into a hybrid electric power generation system with a gas turbine (GT) (jet engine), aimed at propelling electric aircraft1)2). Compared to conventional aircraft, distributed propulsion with electric motors is expected to enhance the propulsion system efficiency. We have thus developed a three-dimensional numerical model of a planar SOFC pressurized for the combination with a GT for the optimal design and operation of practical cells and stacks3). A software package with the finite element method (COMSOL Multiphysics) is employed to analyze the current and temperature distributions in a cell. Exchange current densities for the anode and cathode under pressurized conditions are experimentally evaluated using an electrolyte-supported (YSZ) symmetrical tubular test cell for the electrochemical kinetics in the model by using impedance spectroscopy. Acknowledgments Thanks are offered to Professor Kohei Ito and Associate Professor Tatsumi Kitahara of Kyushu University for their valuable discussions. References 1) T. Kojima, K. Okai, T. Tagashira, Y. Fukuyama, Experimental Study on SOFC/GT Hybrid Engine for Liquid Hydrogen Fueled Electric Propulsion System, in: AIAA Aviat. 2023 Forum, American Institute of Aeronautics and Astronautics, Reston, Virginia, 2023. https://doi.org/10.2514/6.2023-3989. 2) K. Okai, T. Himeno, T. Watanabe, H. Nomura, T. Tagashira, A. Nishizawa, Potential of Aircraft Electric Propulsion with SOFC/GT Hybrid Core, in: 52nd AIAA/SAE/ASEE Jt. Propuls. Conf., American Institute of Aeronautics and Astronautics, Reston, Virginia, 2016. https://doi.org/10.2514/6.2016-4713. 3) H. Nakajima, J. Yamashita, K. Okai, T. Kojima, Numerical Modeling of a Pressurized Solid Oxide Fuel Cell for Electric Aircraft, ECS Meeting Abstract MA2023-01 (2023) 2726–2726. https://doi.org/10.1149/MA2023-01562726mtgabs.
Wang Shuangyu, Shen Qingmao, Sun Mingyang, Tang Shuang, Zhen Ziyang
The weapon-target assignment problem is the key to the combat mission of the UAV against the enemy in the battlefield environment. The purpose is to find a reasonable weapon target assignment scheme based on the threat, value and damage probability of the target, so as to improve the combat efficiency. Aiming at the problem that the current multi-objective optimization algorithm has slow convergence speed and poor convergence stability when solving the static weapon-target assignment problem, and it is difficult to adapt to the high real-time performance of the current battlefield, an improved non-dominated sorting genetic algorithm based on reference points is proposed. The initial population is optimized by binary coding attack scheme, and adaptive mutation and crossover strategy as well as population optimization update strategy is introduced. Based on the threat matrix and advantage matrix obtained by evaluating the battlefield situation, the target attack scheme is generated after multiple iterations of the population. Finally, the Pareto solution set satisfying the constraint condition is calculated, and the relative optimal solution in the Pareto frontier is taken as the attack scheme of multi-UAV. Multiple experiments show that under good conditions, the improved algorithm reduces convergence time by 46.74%, reduces target threat value by 50.5%, reduces total flight range by 26.46%, and increases the number of killing targets by 11.76% compared with the original algorithm. It is proved that the algorithm is reasonable and efficient in solving the problem of target assignment of multi-UAV air-to-ground strike mission.
The history of the development of Russian orbital space stations and prospects for the future development of this field are presented. The significance of their use for the exploration of both near and distant outer space is discussed. A brief overview of Soviet and Russian space programs related to the development of orbital stations is provided. Trends in the development of individual orbital stations have also been analyzed, as well as implementation errors and methods for their resolution. The scientific importance of the Mir space station and experiments conducted on it are discussed. The results of 15 years of operation have been summarized. The reasons for the establishment, stages of development, current status, ongoing research and experiments of the International Space Station are analyzed, as well as future plans for its operations. In addition, the current state of development of the Russian orbital station, the stages of its evolution, planned scientific experiments, and the long-term prospects for the use of orbital stations are considered. This material can be utilized to compose a dissertation on the historical significance and scientific relevance of Russian orbital missions, as well as to undertake research on error analysis, comparative analyses with other space programmes, and the advancement of new technologies for upcoming missions.
Posture is an essential aspect of motor behavior, necessitating continuous muscle activation to counteract gravity. It remains stable under perturbation, aiding in maintaining bodily balance and enabling movement execution. Similarities have been observed between gross body postures and speech postures, such as those involving the jaw, tongue, and lips, which also exhibit resilience to perturbations and assist in equilibrium and movement. Although postural control is a recognized element of human movement and balance, particularly in broader motor skills, it has not been adequately incorporated into existing speech motor control models, which typically concentrate on the gestures or motor commands associated with specific speech movements, overlooking the influence of postural control and gravity. Here we introduce a model that aligns speech posture and movement, using simulations to explore whether speech posture within this framework mirrors the principles of bodily postural control. Our findings indicate that, akin to body posture, speech posture is also robust to perturbation and plays a significant role in maintaining local segment balance and enhancing speech production.
Vehicle roll control has been a well studied problem. One of the ubiquitous methods to mitigate vehicle rollover in the automobile industry is via a mechanical anti-roll bar. However with the advent of electric vehicles, rollover mitigation can be pursued using electric actuation. In this work, we study a roll control algorithm using sliding mode control for active suspension vehicles, where the actuation for the roll control signal is generated by electric motors independently at the four corners of the vehicle. This technology precludes the need for any mechanical actuation which is often slower as well as any anti-roll bar to mitigate vehicle rollover situations. We provide an implementation of the proposed algorithm and conduct numerical experiments to validate the functionality and effectiveness. Specifically, we perform Slalom and J-turn maneuvering tests on an active suspension electric vehicle with sliding model roll control and it is shown to mitigate rollover by atleast 50% compared to passive suspension vehicles, while simultaneously maintaining rider comfort.
The cause of the speed-accuracy tradeoff (typically quantified via Fitts' Law) is a debated topic of interest in motor neuroscience, and is commonly studied using tools from control theory. Two prominent theories involve the presence of signal dependent motor noise and planning variability -- these factors are generally incorporated separately. In this work, we study how well the simultaneous presence of both factors explains the speed-accuracy tradeoff. A human arm reaching model is developed with bio-realistic signal dependent motor noise, and a Gaussian noise model is used to deterministically approximate the motor noise. Both offline trajectory optimization and online model predictive control are used to simulate the planning and execution of several different reaching tasks with varying target sizes and movement durations. These reaching trajectories are then compared to experimental human reaching data, revealing that both models produce behavior consistent with humans, and the speed-accuracy tradeoff is present in both online and offline control. These results suggest the speed-accuracy tradeoff is likely caused by a combination of these two factors, and also that it plays a role in both offline and online computation.
Synthetic Aperture Radar (SAR) has unique advantages and plays an important role in the field of remote sensing, which makes the research of SAR Automatic Target Recognition (ATR) very hot. In recent years, due to the rapid development of deep learning networks and hardware computing power, the deep learning based ATR algorithm for SAR has gradually become the mainstream. Compared with the single-view based recognition, multi-view SAR target recognition tends to better utilize the target scattering information of different azimuth angles. In this paper, we propose a Multi-View Relation Aware (MVRA) network for SAR ATR, which can capture the latent relationships between multiple input views, achieving better recognition accuracy than single-view recognition. Additionally, to enable the network to more accurately capture the contour information of SAR image targets, the Laplacian pyramid is applied for SAR image preprocessing. The proposed MVRA network shows a significant improvement in recognition accuracy on the public dataset MSTAR compared to other multi-view SAR target recognition algorithms. Furthermore, on the new Ground Military Vehicle Target (GMVT) dataset constructed by Nanjing University of Aeronautics and Astronautics (NUAA), the proposed MVRA network demonstrates excellent generalization performance even in the scenarios with relatively strong background clutter interference.
Patrycja K. BAŁDYGA, Marcin JAKUBASZEK, Zygmunt MIERCZYK
The growth of the aerospace industry has made the detection of cosmic radiation essential. That led to a proposal for the development of an optoelectronic detector of cosmic radiation. This will allow continuous measurement of acceptable levels of radiation. The device is currently in its initial development phase, focusing on the detection of ionising radiation. Tests have been carried out with high-energy radiation simulators in the form of natural radioactive sources, confirming the performance of the overall system. The cosmic ray sensor of the study has numerous potential applications, particularly in the aerospace industry. Crew safety could be enhanced by a miniature sensor that measures the absorbed dose of cosmic radiation. Existing passive methods of dose measurement have been ineffective because they provide information about radiation with a delay of several weeks. Active monitoring of irradiation levels enables ongoing control of the dose taken, which is crucial for employee health.
Leandro B. Magalhães, André R. R. Silva, Jorge M. M. Barata
Supercritical nitrogen jet behavior is modeled using an incompressible but variable density approach developed for variable density jets. Following mechanical and thermal breakup concepts, several injection conditions relevant to liquid rocket propulsion are analyzed, considering heat transfer in the injector. Regarding axial density distributions, different levels of agreement with experimental data are encountered for potential core, subsided core, and plateau formations. Further comparisons with compressible formulations from the literature are a good indicator of the proposed methodology’s suitability for the simulation of supercritical injection behavior.
Steven Wiliam Soputra, Sheila Tobing, Seno Sahisnu Rawikara
The rapid growth of Unmanned Aerial Vehicle (UAV) technology, or drone, has shown its popularity and has been significantly applied to various purposes today. Nevertheless, with all the sophistication of drones, many related topics are still attractive, especially when a drone is designed to carry out a cargo mission. Thus, in this research, the dynamic model of a Hexacopter drone to deliver goods belongs to PT Aero Terra Scan is being developed. This dynamic modeling aims to further the drone's development by modeling it in 2 cases: no-payload and with a payload of 5 kg cases. The dynamic model of this Hexacopter is based on flight dynamics, a field of science studied in Aeronautical Engineering, and is implemented using Simulink. Through the results of this research, several conclusions have been withdrawn: (1) The drone's unstable nature characteristic inherently, even though it is analyzed from the initial hover condition. Thus, the drone and its system as a whole can never be separated with the feedback control that made it can maneuver adequately. (2) Several technical parameters of this Hexacopter, including the geometry, mass, the moment of inertia, until the estimation of motor throttle is required to achieve its hover conditions, both in the no-payload case and with-payload of 5 kg case. (3) The Hexacopter basic dynamic system model is based on the flight dynamics until its motion system control tuning through root locus map analysis using Simulink.
Traditional reliability analysis methods such as Reliability Block Diagram, Fault Tree Analysis, and Markov Analysis are all subjective methods whose results significantly depend on the analysts’ skills and experiences. A model-based reliability method is proposed for the wheel brake system by using the architectural analysis and design language (AADL). The wheel brake system is modeled based on the AADL, and the AADL Error Model Annex is applied to describe the fault propagation of the system. An information extraction approach is proposed for the AADL-based model, and rules for transforming AADL-based models to colored Petri nets are given according to the information extracted. The reliability analysis of the wheel brake system is conducted in terms of the Colored Petri Nets. Through Monte Carlo simulation and linear regression, it is inferred that the lifetime of the wheel brake system follows a Weibull distribution with shape parameter 1.303 and scale parameter 9.992 × 10<sup>3</sup>, and the accuracy of the method has been verified. In this study, the reliability analysis results are generated via the system model automatically; they do not depend on the analysts’ experiences and skills, and ambiguity among different analysts can be avoided.
A digital twin of a direct current brushless (BLDC) electric motor and propeller is developed for predicting the generated thrust when there is no motion of the system (static conditions). The model accounts for the back electromotive force, the propeller drag force, and the finite response time arising from the electromagnet winding inductance and DC resistance. The model is compared to a textbook model of BLCD dynamics and to experimental measurements on a KDE Direct KDE2315XF-885/885 Kv motor with a 945 propeller and a Holybro electronic speed controller (ESC) driving an AIR 2216/880 Kv motor with a 1045 propeller. These systems are typically found on Group 1 uncrewed quadcopters (drones). Both the steady-state and transient dynamics depart substantially from linearized models found in the literature. This study is a starting point for disentangling the dynamics of the motor and the change in propeller dynamics due to complex airflow conditions.
This paper proposes a method to improve the mixing efficiency of a supersonic combustor by using arrayed pulsed energy depositions, and this method is verified by a numerical simulation. In the simulation, the Navier-Stokes equations with an energy source are solved to simulate the effects of energy depositions in various distributions on the fuel mixture in the combustor. It is found that the energy deposition arranged in the streamwise direction leads to a significant improvement in the mixing efficiency and maximum concentration decay rate of the ethylene fuel by increasing the scale of the jet-induced counter-rotating vortex pair. The energy deposition arranged in the spanwise direction introduces another counter-rotating vortex pair which can also contribute to the fuel mixture. By comparison, the energy deposition distributed in the streamwise direction and downstream of the jet orifice is shown to be the most effective case in the fuel mixing enhancement. Under the energy deposition, the wall pressure on the trailing edge of the cavity is increased which leads to a decrease in the total pressure recovery of the combustor, but this decrease is not significant.
The VOF (volume of fluid) multiphase transient simulation model of the windage loss of the gear pair under oil-jet lubrication was carried out by using the dynamic mesh technology with the powerful parallel computing capabilities of the Super Cloud Computing Center. Firstly, a two-phase (oil-gas) turbulence numerical model was established in the process of oil-jet lubrication. The numerical simulation test was designed by orthogonal experiment. The influence of the oil-jet lubrication parameters and their interaction on the windage power loss was studied by means of variance analysis. The results showed that the influence of injection speed on the windage power loss was the largest and proportional, followed by injection temperature and injection pressure, and the latter two factors were inversely proportional. Then, the fitting calculation formula of windage loss related to each influencing factor is obtained based on the numerical simulation results. Furthermore, by observing the velocity vector distribution of the internal flow field of the gearbox with different time, the formation mechanism of windage loss is understood intuitively, and the measures to reduce windage loss are put forward. Finally, the mechanical and energy characteristics of the windage loss under different oil injection parameters are proposed, by analyzing and calculating the differential pressure force, viscous force, turbulent kinetic energy, and turbulent dissipation rate around the gear pair. This paper provides a method guidance for the calculation of windage power loss and efficiency of aviation gear pair under elastohydrodynamic lubrication in engineering application.
In this paper, a wideband high-gain microstip patch array antenna for high resolution synthetic aperture radar applications is presented. The antenna operation frequency is in the X-band and the antenna structure is a four-layer configuration consisting of radiating patches, slots, coupling cavities, and a corporate feeding network, which in turn is fed by a coaxial probe. The increased frequency bandwidth of the radiating patch is achieved by employing a square slot, which appears as a cavity for it, and improves the gain and impedance bandwidth of the antenna array by isolating the patch feeding slot and eliminating the mutual coupling effect. The whole antenna structure is fabricated by using a combination of the milling process and printed circuit technology. Measurement results show a relative gain bandwidth of more than 10%, in which the antenna gain is measured above 28.8 dBi over the frequency band of more than 1 GHz. Moreover, the relative impedance bandwidth of the antenna for VSWR>2 is more than 16%.
Understanding how movement is controlled by the central nervous system remains a major challenge, with ongoing debate about basic features underlying this control. In this review, we introduce a new conceptual framework for the distribution of common input to spinal motor neurons. Specifically, this framework is based on the following assumptions: 1) motor neurons are grouped into functional groups (clusters) based on the common inputs they receive; 2) clusters may significantly differ from the classical definition of motor neuron pools, such that they may span across muscles and/or involve only a portion of a muscle; 3) clusters represent functional modules used by the central nervous system to reduce the dimensionality of the control; and 4) selective volitional control of single motor neurons within a cluster receiving common inputs cannot be achieved. We discuss this framework and its underlying theoretical and experimental evidence.