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The performance of hydrogen production by methanol steam reforming and high temperature proton exchange membrane fuel cells on drone lacks the comparison of experimental data, resulting in the overall performance improvement of the system is difficult to evaluate. Therefore, the energy management strategy of methanol reforming high temperature proton exchange membrane fuel cell hybrid power system and state machine is designed and optimized. The performance of this system is analyzed and compared with the flight experiment data of a proton exchange membrane fuel cell hybrid UAV. The results show that the SOC of the system can be stabilized between 70 and 80 during the long cruise phase. The test results show that the maximum hydrogen storage mass density of the hydrogen supply system is increased by 67.6%. The flight time of the system under economic cruise flight of the drone is improved by 29.1%–44.9% with different quality of fuel. Under the maximum flight speed of a certain wind speed, the system can meet the flight requirements and increase the flight time by 31.9% and 17.6% respectively under the wind speed of 1.5 m/s and 4 m/s. Its flight time has been greatly improved, and it has great potential as a drone system. [Display omitted] • Test the performance of system with real flight test data of experimental drone. • The SOC can be stabilized between 70 and 80 during the cruise phase. • The flight time has been improved from 29.1% to 44.9% under economic flight. • The flight time is increased by 31.9% and 17.6% at different wind speeds. [ABSTRACT FROM AUTHOR]

In recent years, micro-sized electric unmanned aerial vehicle (UAVs) have gained widespread applications in both defense and civilian sectors owing to their advantages of lightweight construction, portability, and cost-effectiveness. However, a significant drawback is the difficulty in discerning and controlling the flight attitude and trajectory of these UAVs when operating beyond the line of sight. Consequently, they heavily rely on remote control for flight operations, leading to a high degree of operational complexity. Hence, it is challenging to maintain the desired characteristics of micro-sized aerial vehicle systems, such as high sensitivity and stability. In this study, we aimed to enhance the longitudinal flight stability of micro-sized electric UAVs. To achieve this goal, control of a UAV's elevator was utilized to ensure stability in pitch and roll during flight. We employed the Digital Airborne Tactical Communications System (DATCOM) software developed by the United States Air Force to calculate the fundamental aerodynamic coefficients of the UAV. Subsequently, the longitudinal motion state space equation was employed to derive transfer functions for the pitch angle θ and the horizontal stabilizer deflection de. Furthermore, we utilized Simulink to compare the effects of two control methods, traditional Proportional-Integral-Derivative (PID) and fuzzy PID, on the longitudinal flight stability of the UAV. We aimed to identify the optimal PID values for the UAV. Finally, we validated through practical flight tests that Fuzzy PID can enhance the longitudinal flight stability of the UAV while also contributing to new technological solutions for stability in micro-sized UAV flight. [ABSTRACT FROM AUTHOR]

Multiple rows of feathers, known as the covert feathers, contour the upper and lower surfaces of bird wings. These feathers have been observed to deploy passively during high angle of attack maneuvers and are suggested to play an aerodynamic role. However, there have been limited attempts to capture their underlying flow physics or assess the function of multiple covert rows. Here, we first identify two flow control mechanisms associated with a single covert-inspired flap and their location sensitivity: a pressure dam mechanism and a previously unidentified shear layer interaction mechanism. We then investigate the additivity of these mechanisms by deploying multiple rows of flaps. We find that aerodynamic benefits conferred by the shear layer interaction are additive, whereas benefits conferred by the pressure dam effect are not. Nevertheless, both mechanisms can be exploited simultaneously to maximize aerodynamic benefits and mitigate stall. In addition to wind tunnel experiments, we implement multiple rows of covert-inspired flaps on a bird-scale remote-controlled aircraft. Flight tests reveal passive deployment trends similar to those observed in bird flight and comparable aerodynamic benefits to wind tunnel experiments. These results indicate that we can enhance aircraft controllability using covert-inspired flaps and form insights into the aerodynamic role of covert feathers in avian flight. [ABSTRACT FROM AUTHOR]

To solve the aircraft dynamics modeling problem in the entire envelope range, this work proposes a closed-loop system identification method based on deep learning. A closed-loop flight test was designed, under the framework of the closed-loop flight test, the motion mode of the aircraft was fully stimulated by the input signal of the control rudder surface and the airspeed and position commands. The lateral and longitudinal aerodynamic coefficients were solved from the flight test data, and the black box relationship between the aerodynamic coefficients and their influencing factors was established based on the deep network technology. The aerodynamic coefficient black box model was combined with the dynamics and kinematic equations of the aircraft to form a deep network dynamic model of the aircraft, which belongs to a gray box dynamics model. The deep network can easily and uniformly process different batches of flight test data, thus combining the flight test data at different flight state points, and finally building a complete aerodynamic model within the entire envelope range. Three groups of flight tests were performed: the first group of tests was used for model set training, the second group of test data was used for the selection of the best model, and the third group of flight tests was used for model validation. The model verification was completed from two aspects: the prediction of the aerodynamic coefficient and the prediction of the flight state variables. The results show that the deep network model can complete high-precision modeling of aerodynamic coefficients; and the gray box dynamic model can complete the modeling of aircraft dynamics within the entire envelope, and can be used as a long-term, high-precision flight simulator. [ABSTRACT FROM AUTHOR]

AbstractObjectiveMethodsResultsConclusionThis paper focuses on the relationship between stressful life events experienced by young refugees and their reports of psychological and somatic stress symptoms and well-being. It examines whether this relationship is mediated by personal and social resources and by acculturation hassles experienced in the host country.Path analyses were calculated based on data from 147 adolescents aged 11 to 18 years from the Middle East after their flight to Germany to test the proposed mediation model.The number of experienced stressful life event types was directly linked to current psychological and somatic stress symptoms. The association with psychological stress symptoms was partially mediated by acculturation hassles experienced in the host culture. Well-being was not related to stressful life events but showed significant associations with available social resources. A closer inspection of the mediation by acculturation hassles showed that discrimination hassles and socio-cultural adaptation hassles are important mediators in the relationship between stressful life events and the included outcome variables.The results indicate that stressful life events as well as resources and acculturation hassles should be considered in measures to improve the adjustment of young refugees. [ABSTRACT FROM AUTHOR]

This paper proposes a novel approach for absolute velocity estimation of unmanned aerial vehicles in unknown and unmapped GNSS‐denied environments. The proposed method leverages the advantages of Fourier‐based image phase correlation and utilizes off‐the‐shelf onboard sensors, including a downward‐facing monocular camera, an inertial sensor, and a sonar. The non‐matching tracking approach is particularly appealing, offering accurate estimation while remaining robust against frequency‐dependent noise, significant intensity variations, and time‐varying illumination disturbances. In the proposed method, the first step involves computing global pixel motion from consecutive images using phase correlation, which utilizes the shift property of the Fourier transform. This pixel motion estimation serves as the basis for creating a closed‐loop solution for absolute velocity estimation. To further enhance accuracy, a Kalman filter is implemented to fuse all available data and provide a reliable velocity estimate. Validation of the proposed visual‐inertial technique is conducted through simulation experiments using AirSim and real‐world flight tests. The results demonstrate the practicality and effectiveness of the approach across a range of challenging scenarios. [ABSTRACT FROM AUTHOR]

The Portable (2.7 kg) Cavity-enhanced Absorption of Nitrogen Dioxide (PCAND) instrument for measuring in situ nitrogen dioxide (NO2) was developed using incoherent broadband cavity-enhanced absorption spectroscopy (IBBCEAS). An LED light source centered at 408 nm was coupled to a cavity 15 cm in length, achieving an effective optical pathlength of ∼520 m. Precision was measured as 94 pptv (1 s). To date, we have flown this instrument on three balloon test flights. This instrument records data on an SD card and outputs data (via an RS232 port) to external devices including a commercial radiosonde (iMet) for real-time data downlink. [ABSTRACT FROM AUTHOR]

The authors have been developing small fixed-wing unmanned aerial vehicles (UAVs) for use in various scientific observations. For example, in Antarctica, atmospheric observations have been conducted using a combination of a balloon and UAV. In Ethiopia, wide-area magnetic field observations have been conducted using a UAV capable of long-range flights. These UAVs are equipped with an in-house flight control computer and are capable of automatic flights. However, although approximately 20 years have passed since the development of this computer, issues such as inadequate computing power and memory as well as insufficient number of output ports for pulse width modulation signals remain, posing challenges when constructing complicated systems. To solve these problems, we developed a flight-control computer using a 32-bit microcontroller designed to conduct atmospheric observation missions in Antarctica and withstand low temperature environments down to -40°C. Aerosol observations and sample-return missions were conducted in Antarctica, and aerosol samples were successfully collected at an altitude of 27 km using the developed computer. This paper provides detailed descriptions of the developed flight control computer named "AP-CUB-G2" and the results of the atmospheric observation flight in Antarctica. [ABSTRACT FROM AUTHOR]

A single-use aircraft launch system using a small helium balloon concept was proposed to elevate the likelihood of successful high-altitude flight tests above 30 km. The system, capable of carrying a payload of 0.5 kg, has been developed and reported. Completing the flight within a range of 92 km, which represents the maximum communication distance between the airborne flight system and the ground station for operational phase control, is imperative. Therefore, a straightforward method for simulating flight trajectories was outlined to determine launch windows and suitable locations to ensure flight completion within uninhabited areas. Simulation studies revealed that the shortest landing distance was obtained during summer at the selected launch site. Additionally, a parameter study was conducted to assess the influence of varying ascent velocities on the targeted flight test altitude, which depends on the payload weight and helium gas volume. Consequently, the parameter study results established the constraints for flight model design. A demonstration flight was conducted in 2023 to validate the feasibility of the system for high-altitude flight experiments. This flight successfully released the flight model at 31 km and recovered flight data before landing on the sea surface. The proposed system concept offers an expedited approach to aircraft design for operating in thin air. It enables component function tests and scaled model flights as an alternative to employing large high-altitude balloons for high-altitude experiments. [ABSTRACT FROM AUTHOR]

In the context of flight test planning, numerous uncertainties exist, encompassing aircraft status, number of flights, and weather conditions, among others. These uncertainties ultimately manifest significantly in the actual number of flight sorties executed, rendering high significance to engineering problems related to the execution of flight test missions. However, there is a dearth of research in this specific aspect. To address this gap, this paper proposes an opportunity-constrained integer programming model tailored to the unique characteristics of the problem. To handle the uncertainties, Sample Average Approximation (SAA) is employed to perform oversampling of the uncertain parameters, followed by the Adaptive Large Neighborhood Search (ALNS) algorithm to solve for the optimal solution and objective function value. Results from numerical experiments conducted at varying scales and validated with diverse sampling distributions demonstrate the effectiveness and robustness of the proposed methodology. By decoding the generated execution sequences, comprehensive mission planning schemes can be derived. This approach yields sequences that exhibit commendable feasibility and robustness for the flight test planning problem with sorties uncertainty (FTPPSU), offering valuable support for the efficient execution of future flight test missions. [ABSTRACT FROM AUTHOR]

Traffic accidents caused by collisions with animals are a significant global concern for authorities. The economic impact is substantial, including costs for treating injuries, rehabilitating victims, repairing vehicle damage, and addressing fatalities. As a contribution towards finding a solution, a wireless sensor network (WSN) and an autonomous, power-efficient, and economically feasible drone are presented. WSN is responsible for acquiring relevant information from the farm and communicating the data to the aerial drone denoted as a hexacopter; which is functioning as a mobile roadside device for transferring the warning information to the passing drivers so as to avoid any collision with animals. The proposed system involves the design of a lightweight camel-based sub-system to trigger drones for monitoring herds, a drone-based sub-system for tracking and ensuring safety in agricultural areas, and a vehicle-based sub-system to communicate collision warnings where an alarming protocol has been developed. The whole system has been designed, implemented, tested, and verified in an actual flight test. Experimental results indicate that the system has a unique capability. It can mitigate the number of accidents involving vehicles and animals, especially camels, and thus reduce the economic cost of damages associated with the problem. [ABSTRACT FROM AUTHOR]

Modeling a high-speed flying vehicle is imperative to ensure the success of vehicle development missions. Moreover, adherence to research protocols mandates a stepwise approach to testing the vehicle model, encompassing simulation trials using software-in-the-loop simulation (SILS), hardware-in-the-loop simulation (HILS), as well as diverse ground and environmental tests prior to flight testing. This study entailed a collaborative effort between MATLAB/Simulink and LabVIEW to seamlessly integrate the model developed in MATLAB/Simulink into LabVIEW for the implementation of model predictive control (MPC) strategy, aimed at trajectory correction (TC) missions for the vehicle. This MPC strategy was directly applied to the onboard flight control system (OBFCS) of the vehicle. Simulation results indicate the successful control of roll and pitch conditions by OBFCS in both SILS and HILS, ensuring the maintenance of flight conditions in accordance with predicted trajectories despite the presence of simulated disturbances. Notably, the simulation demonstrates the independence or absence of interference between each simultaneous MPC control for roll and pitch adjustments. [ABSTRACT FROM AUTHOR]

This article examines the flight dynamics and trajectory analysis of a parachute–payload system deployed from a C-17 aircraft. The aircraft is modeled with an open cargo door, extended flaps, and four turbo-fan engines operating at an altitude of 2000 feet Above Ground Level (AGL) and an airspeed of 150 knots. The payloads consist of simplified CONEX containers measuring either 192 inches or 240 inches in length, 9 feet in width, and 5.3 feet in height, with their mass and moments of inertia specified. At positive deck angles, gravitational forces cause these payloads to begin a gradual descent from the rear of the aircraft. For aircraft at zero deck angle, a ring-slot parachute with approximately 20% geometric porosity is utilized to extract the payload from the aircraft. This study specifically employs the CREATE-AV Kestrel simulation software to model the chute-payload system. The extraction and suspension lines are represented using Kestrel's Catenary capability, with the extraction line connected to the floating confluence points of the CONEX container and the chute. The chute and payload will experience coupled motion, allowing for an in-depth analysis of the flight dynamics and trajectory of both elements. The trajectory data obtained will be compared to that of a payload (without chute and cables) exiting the aircraft at positive deck angles. An adaptive mesh refinement technique is applied to accurately capture the engine exhaust flow and the wake generated by the C-17, chute, and payloads. Friction and ejector forces are estimated to align the exit velocity and timing with those recorded during flight testing. The results indicate that the simulation of extracted payloads aligns with expected trends observed in flight tests. Notably, higher deck angles result in longer distances from the ramp, leading to increased exit velocities and reduced payload rotation rates. All payloads exhibit clockwise rotation upon leaving the ramp. The parachute extraction method yields significantly higher exit velocities and shorter exit times, while the payload-chute acceleration correlates with the predicted drag of the chute as demonstrated in prior studies. [ABSTRACT FROM AUTHOR]

The economic impact of Structural Health Monitoring Systems based on optical fibre sensors is assessed in the development of composite helicopter rotor blades. Hence, the focus of this analysis is on the helicopter's Beginning Of Life stage. Two applications of the Structural Health Monitoring System are considered in the development of composite blades: curing cycle development and accomplishment of laboratory and flight certification tests. Optical fibre sensors measure the temperature field during the curing cycle and strain field during the laboratory tests and allow load identification during the load survey activity. It was found that Structural Health Monitoring Systems can potentially lead to economic benefits during the development of the blade provide that a reduction in the number of curing cycles and number of blades tested is achieved as a consequence of the improvement of the temperature and strain field quality. Moreover, an economic benefit could be achieved during the load survey activity, needed to complete the certification of the composite blade, avoiding the periodical maintenance of the applied strain gauges acquiring the strains during the flight. [ABSTRACT FROM AUTHOR]

The search for biosignatures on Mars has been a high priority for astrobiology. The approach to detecting putative biosignatures has largely been focused on chemical analyses targeting predominantly extinct life. However, this approach has limited the characterization of extant life, preventing differentiation between extinct and extant biosignatures. Detecting an extant martian lifeform requires approaches focused on identification of biological features. Identifying potential features of life, such as growth or reproduction, can contribute evidence necessary to identify extant biosignatures. While an unambiguous extant biosignature might not be possible with biologically focused approaches, the combined data can provide supporting evidence to attribute a biosignature to an extinct or extant lifeform in conjunction with flight tested instrumentation. With upcoming initiatives, such as the planned Mars Sample Return campaign and the Mars Life Explorer mission concept, the incorporation of extant life specific analysis is paramount for the future of Mars exploration. [ABSTRACT FROM AUTHOR]

The purpose of the present research is to develop and to demonstrate the design architecture of the AFTS (Automatic Flight and Transition System) for "Lift/Cruise Thrust" type VTOL (Vertical Takeoff and Landing) aircraft such as tiltwing, tilt-propeller, tilt-duct aircraft, etc. VTOL aircraft of this type, characterized by propulsor installations that reorient the thrust relative to the aircraft, offer advantages of a wide flight envelope. However, flight and stability characteristics significantly change depending on airspeed and configurations such as wing tilt angles or propulsor orientations. These make it difficult to operate VTOL aircraft safely and the AFTS, which comprises both autopilot and auto-transition algorithm, should be developed to provide the safe and effective means to control the aircraft over its entire flight envelope. In this research, the autopilot was designed to provide control commands that change control strategies and gains according to the configurations. Additionally, the auto-transition algorithm, which should be coordinated with the autopilot, was designed to select and change configurations for accelerated and decelerated flight. The proposed AFTS was installed to a "Lift/Cruise Thrust" type, QTW (Quad Tilt Wing) VTOL UAS (Unmanned Aircraft System), and fully automated operation capability was demonstrated through flight test both in calm and windy conditions. [ABSTRACT FROM AUTHOR]

Airworthiness certification is challenging for novel aircraft concepts. To avoid the significant cost associated with the redesign for certification compliance, incorporating certification requirements into early aircraft design is desired for unconventional aircraft. However, epistemic uncertainties arising from modeling assumptions, and aleatory uncertainties stemming from uncontrollable noise factors may have impacts on the certification analysis and certification-constrained design process. This paper presents an uncertainty quantification study based on a certification-constrained design and optimization study previously conducted for NASA's Parallel Electric-Gas Architecture with Synergistic Utilization Scheme (PEGASUS) concept. The epistemic uncertainties are modeled through a set of multiplicative factors applied to intermediate disciplinary variables. The sensitivity analysis between design metrics and multiplicative factors reveals that uncertainties in stability and control derivatives can significantly affect certification constraint predictions, and uncertainties in drag approximations have considerable impacts on the vehicle sizing process. The aleatory uncertainties added to flight dynamics simulations include wind velocities and variations of weight and center of gravity. Four representative design candidates are evaluated for their robustness against aleatory uncertainties based on the Monte Carlo simulation performed on noise factors. The results show that aleatory uncertainties can affect the aircraft dynamic responses in flight test simulations, thus compromising certification compliance. [ABSTRACT FROM AUTHOR]

Despite the tremendous advances in aircraft design that led to successful powered flights of aircraft as heavy as the Antonov An-225 Mriya, which weighs 640 tons, or as fast as the NASA-X-43A, which reached a record of Mach 9.6, many characteristics of bird flight have yet to be utilized in aircraft designs. These characteristics enable various species of birds to fly efficiently in gusty environments and rapidly change their momentum in flight without having modern thrust vector control (TVC) systems. Vultures and seagulls, as examples of expert gliding birds, can fly for hours, covering more than 100 miles, without a single flap of their wings. Inspired by the Great Black-Backed Gull (GBBG), this paper presents "CGull", a non-flapping unmanned aerial vehicle (UAV) with wing and tail morphing capabilities. A coupled two degree-of-freedom (DOF) morphing mechanism is used in CGull's wings to sweep the middle wing forward and the outer feathered wing backward, replicating the GBBG's wing deformation. A modular two DOF mechanism enables CGull to pitch and tilt its tail. A computational model was first developed in MachUpX to study the effects of wing and tail morphing on the generated forces and moments. Following the biological construction of birds' feathers and bones, CGull's structure is mainly constructed from carbon-fiber composite shells. The successful flight test of the proof-of-concept physical model proved the effectiveness of the proposed morphing mechanisms in controlling the UAV's path. [ABSTRACT FROM AUTHOR]

For flight test engineering, the flight test task schedule is of great importance to the delivery node and the development cost of an aircraft, while in the real flight test process, dynamic events may frequently occur, which affect the schedule implementation and flight test progress. To adaptively adjust the real-world flight test schedule, this paper proposes a deep reinforcement learning (DRL) approach to solve the dynamic task scheduling problem for flight tests, with the objectives of flight test duration and task tardiness. Firstly, the task scheduling characteristics for flight tests are introduced, and a mixed-integer programming (MIP) model is constructed. Then, the addressed problem is formulated as a Markov decision process (MDP), including the well-designed state features, reward functions, and action space based on the heuristic rules for selecting the uncompleted flight test task and allocating the selected task to an appropriate aircraft. Proximal policy optimization (PPO) is adopted to train and learn the optimal policy. Finally, extensive experiments are carried out to verify the proposed method's effectiveness and efficiency in constructing a high-quality flight test task schedule in a dynamic flight test environment. [ABSTRACT FROM AUTHOR]

Purpose: Torque is one of the main loads acting on the aircraft wing, the horizontal tail and the vertical tail. In flight load measurement, due to the significant influence of the bending moment and the shear force on the strain gauge, the accuracy of torque measurement is usually low. Therefore, aircraft torque measurement is difficult. Based on the characteristics of a certain type of horizontal tail, a measurement method for the torque with high accuracy was proposed in this paper. Design/methodology/approach: A new simplified torque measurement method for the all-moving horizontal tail was proposed based on the spiral driver. The feasibility of the method and key points of the tests were analyzed and studied through a virtual load calibration test. Findings: Based on the results of the real load calibration test, the torque load equation with high accuracy was established, and the torque measurement was achieved in load flight tests. Research limitations/implications: However, the proposed method is based on the structure of the spiral driver. If there is generally no spiral driver at the aircraft wings and vertical tails, then the appropriate torque measurement method needs to be derived according to the specific object. Originality/value: The research in this paper provides a new idea for the torque measurement of aircraft structures, which can be used for the torque measurement of subsequent aircraft types. [ABSTRACT FROM AUTHOR]

Three unsteady aerodynamic tools at different levels of fidelity and computational cost were used to investigate the unsteady aerodynamic behavior of a delta kite applied to airborne wind energy. The first tool is an in‐house unsteady panel method that is fast but delivers low to mid fidelity predictions. The second tool uses the open‐source CFD code SU2 to solve the unsteady Reynolds‐averaged Navier–Stokes equations with the k−ω$$ k-\omega $$ SST turbulence model. At an intermediate level of fidelity, a semiempirical dynamic stall model that combines the panel method with a phenomenological dynamic stall module is proposed. The latter has free parameters that are fine‐tuned with CFD results from the second tool. The research on the dynamic stall model has been inspired by two flight test campaigns suggesting dynamic stall phenomena possibly driven by the periodic variation of the angle of attack (aerodynamic pitching motion) during crosswind maneuvers. The recorded inflow along the flight path was prescribed in the three aerodynamic tools. As expected, the price to pay for the low computational cost of the panel method is its inability to capture the dynamic stall phenomenon. The results from unsteady CFD qualitatively matched the experimental data identifying a leading‐edge vortex that forms and detaches cyclically during the pitching motion. Using RANS data, the semiempirical tool was fined‐tuned to reproduce the dynamic stall behavior, becoming an accurate and fast aerodynamic tool for coupling with any kite flight simulator. Further discussions on the effects of kite aerostructural deflections are included. [ABSTRACT FROM AUTHOR]

Agriculture drones face important challenges regarding autonomy and construction, as flying time below the 9-minute mark is the norm, and their manufacture requires several tests and research before reaching proper flight dynamics. Therefore, correct design, analysis, and manufacture of the structure are imperative to address the aforementioned problems and ensure a robust build that withstands the tough environments of this application. In this work, the analysis and implementation of a Nylamid motor bracket, aluminum sandwich-type skeleton, and carbon fiber tube arm in a 30 kg agriculture drone is presented. The mechanical response of these components is evaluated using the finite element method in ANSYS Workbench, and the material behavior assumptions are assessed using a universal testing machine before their implementations. The general description of these models and the numerical results are presented. This early prediction of the behavior of the structure allows for mass optimization and cost reductions. The fast dynamics of drone applications set important restrictions in ductile materials such as this, requiring extensive structural analysis before manufacture. Experimental and numerical results showed a maximum variation of 8.7% for the carbon fiber composite and 13% for the Nylamid material. The mechanical properties of polyamide nylon allowed for a 51% mass reduction compared to a 6061 aluminum alloy structure optimized for the same load case in the motor brackets design. The low mechanical complexity of sandwich-type skeletons translated into fast implementation. Finally, the overall performance of the agriculture drone is evaluated through the data gathered during the flight test, showing the adequate design process. [ABSTRACT FROM AUTHOR]

For advanced aircraft, the temperature environment inside the cabin is very severe due to the high flight speed and the compact concentration of the electronic equipment in the cabin. Accurately predicting the temperature environment induced inside the cabin during the flight of the aircraft can determine the temperature environment requirements of the onboard equipment inside the cabin and provide an accurate input for the thermal design optimization and test verification of the equipment. The temperature environment of the whole aircraft is divided into zones by the cluster analysis method; the heat transfer mechanism of the aircraft cabin is analyzed for the target area; and the influence of internal and external factors on the thermal environment is considered to establish the temperature environment prediction model of the target cabin. The coefficients of the equations in the model are parameterized to extract the long-term stable terms and trend change terms; with the help of the measured data of the flight state, the model coefficients are determined by a stepwise regression method; and the temperature value inside the aircraft cabin is the output by inputting parameters such as flight altitude, flight speed, and external temperature. The model validation results show that the established temperature environment prediction model can accurately predict the change curve of the cabin temperature during the flight of the aircraft, and the model has a good follow-up performance, which reduces the prediction error caused by the temperature hysteresis effect. For an aircraft, the estimated error is 2.8 °C at a confidence level of 95%. Engineering cases show that the application of this method can increase the thermal design requirements of the airborne equipment by 15 °C, increase the low-temperature test conditions by 17 °C, and avoid the problems caused by an insufficient design and over-testing. This method can accurately predict the internal temperature distribution of the cabin during the flight state of the aircraft, help designers determine the thermal design requirements of the airborne equipment, modify the thermal design and temperature test profile, and improve the environmental worth of the equipment. [ABSTRACT FROM AUTHOR]

Civil aircrafts are highly complex systems. During the manufacturing process, deviations can occur due to cumulative errors in installation, system control, and other factors. These deviations often lead to the phenomenon of aircraft "runaway" during ground taxiing, taking off, and landing. Corrective maneuvers to address this issue not only increase the pilot's workload but also heighten the risk of aircraft deviation from the runway. Therefore, accurately testing and aligning the side deviation angle of an aircraft is crucial for ensuring safe operations. In this paper, we first construct a mathematical model of aircraft dynamics and derive a simplified mathematical model specifically designed for aircraft trimming tests. Next, a ground taxiing trimming test is conducted to verify the accuracy of this simplified model. Additionally, we investigate the crosswind factor, which has the greatest impact on side deviation measurements, to establish the relationship between the crosswind factor and the nose wheel trimming angle. Based on this, we innovatively propose a method for achieving aircraft trimming through the equivalent trimming angle of the nose wheel. Ultimately, this approach allows aircraft trimming to be achieved with a single taxiing side deviation test, which will reduce the cost of flight tests and normal operation of the airplane when finding taxiing deviation. The method innovatively proposed in this paper offers an efficient and accurate solution for aircraft trimming tests and adjustments, significantly reducing the cost of such tests and improving the safety of civil aircraft. [ABSTRACT FROM AUTHOR]

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In airborne radar, false alarms caused by surface clutter returns through antenna sidelobes need to be suppressed to detect the target of interest. Sidelobe blanking is widely used to reject false alarms. Ideally, an auxiliary antenna radiation pattern should cover entire sidelobes of the main antenna radiation pattern. However, this may not always be satisfied, especially in the case of far sidelobes (FSL) of the main antenna, for various reasons. In this work, rejection techniques for false alarms caused by surface clutter returns through FSL are proposed. The distortion of the measured angle and velocity of the surface clutter are explained, and a measurement process for estimating the true location and velocity of the clutter is derived. Subsequently, two techniques for false alarm rejection are presented. The first technique is based on the look-up table (LUT) of FSL, which is robust but not practical due to the time and cost required to build a LUT with sufficient resolution. In the second technique, false alarms are rejected when they satisfy predefined criteria derived from their common characteristics, and flight test results confirm that false alarms can be effectively rejected by applying the second technique. [ABSTRACT FROM AUTHOR]

Turbulence excitation is an unavoidable form of excitation in flutter flight tests, and it is also a necessary and effective excitation method in high-speed flights, dives, other high-risk test, and high-frequency modal information mining. However, because the turbulence excitation signals are unmeasurable in the time domain, although the turbulence response contains rich and valuable flutter test information, the randomness and low quality of the data often cause difficulties in modal analysis. Therefore, an improved frequency domain decomposition algorithm for turbulence response processing is proposed in this paper. First, due to the irrelevancy of the atmospheric excitation, the power spectral density function matrix of the multi-channel turbulence response is subjected to singular value decomposition. There is a mathematical relationship between the maximum singular value curve and the system frequency response function. Second, the modal assurance criteria are used to calculate the maximum singular value of a single-degree-of-freedom system. Finally, an orthogonal polynomial method is applied to fit the maximum singular value curve, and the system identification is performed directly in the frequency domain. The simulated data and a certain type of aircraft flutter flight test data are used to verify the proposed method, and the results confirm the effectiveness and engineering applicability of the method developed in this work. [ABSTRACT FROM AUTHOR]

Fresh, nutritious, palatable produce for crew consumption on long-duration spaceflight missions may provide health-promoting, bioavailable nutrients and enhance the dietary experience. VEG-04A and VEG-04B explored growing leafy greens on the International Space Station using the Veggie Vegetable Production System. Two flight tests with ground controls were conducted in 2019 growing mizuna mustard, where Veggie chambers were set to different red-to-blue-to-green light formulations. Light quality affects plant growth, nutrition, microbiology, and organoleptic characteristics on Earth, and we examined how these vary in microgravity and under different harvest scenarios. Astronauts harvested and weighed mizuna and completed organoleptic evaluations. Flight samples were returned to Earth for nutritional quality and microbial food safety analyses. Yield and chemistry differed between ground and flight samples and light treatments, and bacterial and fungal counts were lower in ground than in flight samples. This research helps increase our understanding of the requirements for growing high-quality crops in spaceflight. [ABSTRACT FROM AUTHOR]

BACKGROUND: Migration and immunity are behavioral and physiological traits that protect organisms from environmental stressors or pathogen infection. Shifting from migration to residency has become more common in some wildlife populations owing to environmental changes. However, other biological shifts, such as interactions between migration and immunity among populations within a species are largely unexplored for many agricultural migratory pests. In the field, entomopathogenic fungi infection and transmission, particularly Beauveria bassiana, can cause reduced fitness and population declines across a broad range of insect species. RESULTS: Here, we investigated migration–immunity interactions between migrant and resident populations of the oriental armyworm, Mythimna separata, infected with B. bassiana (the sole fungus used in this work). We found that migratory M. separata exerted stronger pathogen resistance, faster development and lower pupal weight than residents. High‐dose infections (5.0 × 105 and 5.0 × 106 conidia mL−1) led to seriously decreased reproductive capacity in migrants and residents. Low‐dose infections (1.0 × 104 and 5.0 × 104 conidia mL−1) led to significantly increased host flight capacities. Consecutive flight tests showed that five flight nights inhibited the reproduction of paternal infected M. separata populations. The flights also led to far‐reaching transgenerational impairment of larval development and immune defense among offspring populations. By contrast, two flight nights enhanced the reproductive capacities of both M. separata populations and did not exert negative transgenerational effects on offspring populations, which may facilitate migration. CONCLUSIONS: This study provides insights into interactions between migration and immunity among M. separata populations. These insights will guide development of future monitoring and management technologies of this pest. © 2024 Society of Chemical Industry. [ABSTRACT FROM AUTHOR]

This paper proposes an innovative approach for optical flow-based control of micro air vehicles (MAVs), addressing challenges inherent in the nonlinearity of optical flow observables. The proposed incremental nonlinear dynamic inversion (INDI) control scheme employs an efficient data-driven approach to directly estimate the inverse of the time-varying INDI control effectiveness in real-time. This method eliminates the constant effectiveness assumption typically made by traditional INDI methods and reduces the computational burden associated with inverting this variable at each time step. It effectively handles rapidly changing system dynamics, often encountered in optical flow-based control, particularly height-dependent control variables. Stability analysis of the proposed control scheme is conducted, and its robustness and efficiency are demonstrated through both numerical simulations and real-world flight tests. These tests include multiple landings of an MAV on a static, flat surface with several different tracking setpoints, as well as hovering and landings on moving and undulating surfaces. Despite the challenges posed by noisy optical flow estimates and lateral or vertical movements of the landing surfaces, the MAV successfully tracks or lands on the surface with an exponential decay of both height and vertical velocity almost simultaneously, aligning with the desired performance. [ABSTRACT FROM AUTHOR]

The AquaFly project is a research collaboration between the Flight Systems and Control (FSC) Laboratory at the University of Toronto Institute for Aerospace Studies (UTIAS) and Queen’s University Biology Department in Canada to offer a fast, reliable, and efficient method of sampling water bodies by using autonomous Unmanned Aerial Systems (UAS). To this end, two UAS are custom-designed and flown for autonomous water sampling, incorporating an octocopter configuration and a ratchet and pawl mechanism for retracting and releasing payloads. This design offers easy-to-use and safe deployment and retraction without continuous motor engagement while eliminating load swinging and the risk of instability by positioning the sampler close to the drone’s center of mass. Furthermore, the system enables autonomous water sampling in remote or inaccessible areas with pre-programmed flight paths and sampling locations, ensuring consistent data collection. The sampling mechanism allows controlled retrieval and release of payloads and further facilitates multi-drone operations to support a variety of sampling missions. This innovative UAS has the potential to revolutionize water sampling and enhance efficiency and safety in environmental monitoring, research, and resource management. Flight tests over several water bodies demonstrate successful simultaneous water sampling missions with two UAS. To the best of the authors’ knowledge, this is the first work to include multiple UAS, each equipped with a payload deployment and retraction mechanism, for autonomous water sampling. [ABSTRACT FROM AUTHOR]

Traditional particle swarm optimization(PSO) is prone to getting stuck in local optima and low search ability for energy consumption optimal solutions when planning plant protection operation paths. The study focuses on improving the PSO algorithm in order to improve the efficiency of crop protection drone operations and reduce drone losses. The study proposes an adjacent competition (AC) algorithm for crop protection operation path planning based on a crop protection UAV model in order to solve the problem of poor effectiveness of traditional particle swarm optimization algorithms applied to UAV plant protection operations. The adjacent competition algorithm ensures that the total distance of crop protection UAV operations is constant, provides prior knowledge of the search direction, and ensures that special points are not missed, preventing the algorithm from getting stuck in local optimal solutions: Firstly, all particles initialize the homework distance range to prevent extreme situations where the single homework distance is too long or too short. Secondly, each drone is randomly assigned the operating distance for each particle within the operating range. Finally, adjacent particles compete with each other for the operating distance, indirectly changing the operating distance of each flight and searching for the optimal path. The study used Matlab to conduct algorithm simulation verification on a simulated plant protection site of 420 m×200 m. Traditional particle swarm optimization algorithm often gets stuck in local optima and the final planning results fluctuate greatly, while the adjacent competition algorithm obtains the optimal energy consumption solution 9 times out of 10 planning iterations, and the planning energy consumption of non-optimal solutions is similar to the optimal energy consumption, still better than all planning results of the traditional particle swarm algorithm, proving that the neighboring contention algorithm has stronger searchability. The results show that traditional particle swarm optimization algorithms often got stuck in local optima and increased energy consumption by 16.16% to 38.14% compared to neighboring contention algorithms in 10 rounds of path planning. This indicated that the energy consumption of the adjacent competition algorithm proposed in this study for planning results is much lower than that of the traditional particle swarm optimization algorithm, and the algorithm has stronger search capabilities. This study used the RflySim simulation platform to build a crop protection drone model and a 420 m×200 m work site in order to compare the simulated tracking results of the traditional particle swarm optimization algorithm and adjacent competition algorithm in a virtual environment. The results show that the energy consumption of adjacent competition algorithm planning results is reduced by 25.15% compared to the traditional particle swarm algorithm. This study conducted actual flight tests using the drone M300 at a 420 m×200 m work site to validate the practicality of the algorithm. Actual flight experiments have shown that the energy consumption of adjacent contention algorithm planning results is reduced by 34.48% compared to traditional particle swarm optimization algorithms, making it more suitable for multiple crop protection operations. In actual experiments, the return points of multiple UAVs in the adjacent contention algorithm are closer to the supply point, the distance of departure and return is shorter, and the ineffective energy consumption is lower compared with the traditional particle swarm optimization algorithm, indicating that its planning is more reasonable. Adjacent particles indirectly change the distance of each operation by competing for each other's operation distance, effectively improving the convergence speed of the algorithm, preventing the algorithm from getting stuck in local optima, and improving the efficiency of multiple crop protection operations with a single drone. [ABSTRACT FROM AUTHOR]

Modal parameter estimation of turbulence response is an important aspect of flutter test data processing. Using the modal parameter estimation results of turbulence response and the damping extrapolation curve, the flutter boundary of aircrafts can be predicted. However, owing to the randomness of atmospheric turbulence excitation, modal parameter estimation of the turbulence response has a challenge. This study analyses the turbulence response and calculates the corresponding impulse response using the seq-to-seq self-attention generative network. The encoder performs feature compression of the turbulence response, whereas the multi-head self-attention structure in the middle layer extracts the time series features. Up-sampling is performed based on the decoder to obtain the impulse response, and modal parameter estimation of the turbulence response is achieved. The self-attention generative model is validated using simulation data and the turbulence response is obtained by the wind tunnel test and the flutter flight test. The results demonstrate the feasibility and engineering applicability of the seq-to-seq generative model. [ABSTRACT FROM AUTHOR]

This paper presents the development, characterization, and testing of PP/PE-g-MA composites with 10 and 15 wt% surface-modified aramid fibers, and aluminum-based pigment, as covers for a small drone body for collision protection. The successful fiber surface modification with SiO2 by the sol–gel method using TEOS was confirmed by FTIR, SEM, and EDS analyses. The composites were characterized by FTIR and SEM analyses and surface energy and water contact angle measurements and tested in terms of tensile, flexural, impact, and thermal properties. The materials exhibited hydrophobic character and compact and uniform morphostructures, with increased surface energy with fiber content owed to improved adhesion between modified fibers and the matrix. Compared to the control sample, composites with modified fibers showed an increase by 20% in tensile strength, and 36–52% in the modulus, and an increase by 26–33% in flexural strength and 30–47% in the modulus, with higher values at room temperature. Impact resistance of modified fiber composites showed an increase by 20–40% compared to the control sample, due to improved interaction between SiO2-modified fibers and maleic anhydride, which inhibits crack formation, allowing higher energies' absorption. The composites were vacuum-thermoformed on 3D-printed molds as a two-part cover for the body of a drone, successfully withstanding the flight test. [ABSTRACT FROM AUTHOR]

The ice crystal icing in aero-engines poses a significant threat to aircraft flight safety, and investigating the correlation between ice crystal size and velocity in icing wind tunnels is essential for correlating ground tests with flight conditions. In this paper, a digital holographic particle tracking velocimetry system is developed and integrated with an icing wind tunnel, and the ice crystal size and velocity are simultaneously measured in experiments at four different wind speeds. The velocity difference between the ice crystal and wind has been experimentally observed, and it increases with both the ice crystal size and wind speed. The normalized velocities of the ice crystals by the wind speeds decrease with size, and the maximum velocity difference in the experiments reaches 28% of the wind speed. Additionally, quantitative correlations between ice crystal size and normalized velocity based on the power function and polynomial model are established. The relationship between the particle Reynolds number of ice crystal and size is also analyzed, resulting in the development of a model based on the power function, and the power index ranges from 1.51 to 1.64. These findings will provide valuable assistance in the calibration and commissioning of the ice crystal simulation system in icing wind tunnels, as well as in exploring the correlation between ground icing tests and flight and in developing corresponding models. [ABSTRACT FROM AUTHOR]

Conventional angular acceleration estimation methods generate non-negligible errors when the control surface rapidly deflects; hence, the estimated angular acceleration cannot be used for aerodynamic parameter identification directly. This paper proposes an angular acceleration estimation method based on angular velocity equivalent model. The angular acceleration of the angular velocity equivalent model, whose angular velocity response is consistent with the flight test data, is used as the estimated angular acceleration. Firstly, the equivalent angular velocity model is established by combining the generic aerodynamic model with the rotational dynamic equations of aircraft. Secondly, the angular velocity data and the control surface deflection data are synchronized. Finally, the angular velocity response of the equivalent model is used as the predictor, and the estimated angular acceleration is obtained by extended Kalman filter. The aerodynamic parameter identification and validation are carried out using the estimated angular acceleration of a large civil aircraft flight test data. The results show that the angular acceleration obtained through the proposed angular acceleration estimation method meets the accuracy requirement of aerodynamic parameter identification. [ABSTRACT FROM AUTHOR]

A coaxial helicopter with a maximum take-off weight of 600 kg was converted to an unmanned aerial vehicle. A minimally invasive robotic actuator system was developed, which can be retrofitted onto the copilot seat of the rotorcraft in a short period of time to enable automatic flight. The automatic flight control robot includes electromechanical actuators, which are connected to the cockpit inceptors and control the helicopter. Most of the sensors and avionic components were integrated into the modular robotic system for faster integration into the rotorcraft. The mechanical design of the control system, the development of the robot control software, and the control system architecture are described in this paper. Furthermore, the multi-body simulation of the robotic system and the estimation of the linear low-order actuator models from hover-frame flight test data are discussed. The developed technologies in this study are not specific to a coaxial helicopter and can be applied to the conversion of any crewed flight vehicle with mechanical controls to unmanned or fly-by-wire. This agile development of a full-size flying test-bed can accelerate the testing of advanced flight control laws, as well as advanced air mobility-related functions. [ABSTRACT FROM AUTHOR]

This paper presents an integrated framework for aircraft engines, which consists of three phases: modeling, control, and experimental testing. The engine is formulated as an uncertain T–S fuzzy model. By a hierarchical dynamical parameter clustering, the number and premise variables of fuzzy rules are optimized, which keeps the engine's prime and representative dynamics. For each fuzzy rule, a global stability-guaranteed method is developed for the identification of the consequent uncertain dynamic model. The resulting stable T–S fuzzy model accurately approximates the actual engine dynamics in the operation space. Based on this fuzzy model, a new robust control is constructed with hierarchical compensators. The control parameters take advantage of the fuzzy blend of engine prime dynamics and uncertainty thresholds. Extensive hardware-in-loop (HIL) experimental tests in the flight envelope and a flight task cycle demonstrate the effectiveness and real-time performance of the proposed control. The settling times and overshoots of engine response are suppressed to be under 2.5 s and 10%, respectively. [ABSTRACT FROM AUTHOR]

AbstractUnmanned aerial vehicles (UAVs) play a pivotal role in modern society which requires lightweight yet robust structures to fulfill increasingly complex tasks. This study presents a cost-effective prototyping approach to assess the structural integrity of control surfaces within the innovative Coaxial Unmanned Aerial Vehicle version 3.0 (MCR UAV v3.0). Integrating a hybrid design with coaxial propulsion for vertical stabilization and yaw control, the MCR UAV v3.0 incorporates control surfaces (ailerons) to manage roll and pitch movements during flight. The design process relies on a comprehensive understanding of material mechanical properties, particularly polylactic acid (PLA) specimens fabricated via fused deposition modeling (FDM) with varying infill percentages and building angles. A novel fluid-structure interaction method is developed in order to analyze four control surface topologies: concave (A), optimized concave (B), convex (C), and optimized convex (D). Findings reveal that the optimized design significantly improves stress distribution in the fuselage-control surface interface while reducing aileron weight by approximately 70%. Subsequently, a functional UAV prototype incorporating optimized ailerons is manufactured. Flight tests affirm the efficacy of the ailerons in controlling roll and pitch motions. This work significantly contributes by introducing the novel MCR UAV v3.0 and conducting a comprehensive assessment of fuselage-control surface structural stability, offering insights into enhanced UAV design and performance for diverse applications. [ABSTRACT FROM AUTHOR]

In this work, typical design, production, and testing procedures for a small unmanned helicopter are explained and performed. In doing so, preliminary sizing of the helicopter and three main disciplines are conducted: aerodynamic analytical and numerical simulations, power calculations, and structure analysis assessment. First, a thorough survey is implemented to obtain the trends for the maximum take-off weight versus some design constraints such as rotor diameter, motor power, payload, and empty weight. Performance calculation results are obtained to figure out all aspects that correspond to the specified mission. The designed rotor geometry along with the aerodynamic characteristics and flight performance variables is then validated using the blade element theory and numerical simulations. Second, based on the power curves obtained for different flight regimes, an electric brushless motor is selected. The numerical simulations (Computational Fluid Dynamics) analysis is used to enhance the selection which implies that the motor power should be greater than 5.4 kW to overcome the drag forces. The motor power selection corresponds to a maximum rotor pitch angle of 15∘ and a maximum rotor speed of 1450 RPM. Then, the aerodynamic loads are used as an input for the structural analysis using one-way coupling of fluid–structure interaction (FSI) and consequently designing the internal structure of the blade. Eventually, the internal structure manufactured using carbon fiber-reinforced polymer (CFRP) by applying a combined technique between wet layup and compression molding. The blade is statically tested compared with numerical finite element model results. The fuselage structure along with hub and tail units is manufactured and assembled with the existing on-shelf components to examine the helicopter lift capability with different payloads up to 9 kg. The results show that the detailed design process is significant for manufacturing such blades and the helicopter is capable of lifting off the ground with various payloads depending on the rotor pitch angles (8∘, 12∘, and 15∘) at a constant rotor speed of 1450 RPM. [ABSTRACT FROM AUTHOR]

Determining the guaranteed operational time of helicopter blades is one of the important tasks necessary for successful vehicle use. Flight tests on different modes and special fatigue benches are used to solve such problems. The loads recorded during the flight are applied to ground tests on a bench. The ground fatigue tests of the ultralight helicopter blades have features associated with the influence of the scale factor comparison with the big helicopters. These features are presented in this article as the example of a ground test for a VA115 helicopter blade and a method of recalculating data. The purpose of these tests was to confirm the guaranteed service life of blades and define a reliable method for it. [ABSTRACT FROM AUTHOR]

Advancing the precision of low-gravity liquid propellant mass gauging is a roadmap challenge for NASA and a significant obstacle to expanding human presence in space. We report flight test data for an implementation of a low-gravity liquid propellant mass gauging technology that is both non-invasive and propellant agnostic. The TRIO payload experiment flew twice on the Blue Origin New Shepard suborbital rocket and validated computational models of liquid distribution in microgravity at three different fill levels. The Propellant Refueling and On-orbit Transfer Operations (PROTO) payload experiment also flew twice on New Shepard and acquired mass gauging data before, during, and after a tank drain and fill that simulated in-space propellant transfers. Propellant volume estimates were derived at 1 Hz using the Modal Propellant Gauging (MPG) system. Analytical, semi-empirical, and finite element (FE) model results for predicted mode frequencies are compared to flight data for mode frequencies across a range of fill levels during the simulated propellant transfer. Flight (0-g), ground (1-g) and FEM mode frequencies for both 0- and 1-g are well-predicted by the semi-empirical models for frequency dependence on tank fill level. • Modal Propellant Gauging (MPG) is a non-invasive and propellant agnostic liquid mass gauging technology. • Demonstrated high-accuracy low-gravity mass gauge during liquid transfer between two tanks. • Added mass effect shifts modal frequencies in predictable ways. • Modal Peak Tracking is capable of identifying liquid mass effects in fluid-loaded tanks. [ABSTRACT FROM AUTHOR]