Actual Flight Research Articles

Airfoil Friction Drag Reduction with Net Power Savings Using Pulsed-Direct-Current Plasma Actuation

This paper reports the results of experiments in which flush-mounted pulsed-direct-current plasma actuator arrays were used to achieve skin-friction drag reduction on a NACA 63012A airfoil at a zero attack angle over the Mach number range of corresponding to a chord Reynolds number range of . The objective of the experiments was to document both the level of drag reduction and the net power savings achievable over this Mach number range. The arrays were designed to produce a spanwise array of opposed wall jets confined to the turbulent boundary-layer buffer region. These served to intervene in the autonomous near-wall mechanism that produces buffer-layer streamwise vorticity and is largely responsible for high levels of friction drag. It was demonstrated that the actuator array produces unprecedented levels of friction drag reduction with significant net power savings. Perhaps most interesting was the observation that the actuator authority has to be reduced for increased Mach numbers in order to keep the wall jets confined to the turbulent boundary-layer buffer region. This gave rise to a net power savings that scaled as . Unlike many previous experiments with plasma actuators, these results show that this form of flow control would not be authority limited in actual flight applications.

Feasibility Study of Operation Volume Design Concept for Integration of Aircraft Flying Under Visual Flight Rules Based on Actual Flights

Segregation through operation volumes can enable safe and efficient low altitude airspace usage by various aircraft types, both manned and unmanned. Current traditional aircraft flying under visual flight rules (VFR) are not required to adhere to a strict flight plan and share their flight intentions, but their integration in high-density environment will require better strategic trajectory prediction. This paper proposes VFR trajectory modeling based on mission type and typical flight characteristics. The idea is illustrated with a reconnaissance mission mimicking landmark (highway) tracking to check for post-disaster damages. Results from a flight campaign with an experimental helicopter conducted in 2020 verify the assumptions posed at trajectory modeling and identify the degree of uncertainties necessary to determine the buffers around each trajectory and therefore design operation volumes. The same mission-based trajectory modeling and operation volume design approach can be applied to further missions and vehicles, which makes it transferable to the needs of advanced air mobility as well, especially addressing dense operations.

Optimising Airport Ground Resource Allocation for Multiple Aircraft Using Machine Learning-Based Arrival Time Prediction

Managing aircraft turnaround is a complex process due to various factors, including passenger handling. Airport ground handling, resource planning, optimal manpower, and equipment utilisation are some cost-cutting strategies, particularly for airlines and ground handling service teams. Scheduled aircraft arrival and departure times are critical aspects of the entire ground management and passenger handling process. This research aimed to optimise airport ground resource allocation for multiple aircraft using machine learning-based prediction methodologies to enhance the prediction of aircraft arrival time, an uncontrollable variable. Our proposed models include a multiple linear regression (MLR) model and a multilayer perceptron (MLP)-based model, both of which are used for predicting round-trip arrival times. Additionally, we developed a MLP-based model for multiclass classification of arrival delays based on departure time and delay from the same airport. Under normal weather conditions and operational scenarios, the models were able to predict round-trip arrival times with a root mean squared error of 8 min for each origin–destination pair and classify arrival delays with an average accuracy of 93.5%. Our findings suggest that machine learning-based approaches can be used to predict round-trip arrival times based on the departure time from the same airport, and thereby accurately estimate the number of actual flight movements per hour well in advance. This predictability enables optimised ground resource planning for multiple aircraft based on constrained airport resource deployment and utilisation.

Recent Applications of System Identification Techniques at IPEV

This paper presents an overview of the system identification techniques developed and applied at the Flight Test and Research Institute during the last decade. System identification techniques have been used extensively to obtain aerodynamic models for a flight-test simulator, which was developed in house and specifically tailored for flight-test instruction and preparation for actual test flights. The methods applied were mostly the output error for data compatibility check and equation error in the time domain for model structure selection and parameter estimation. The most relevant applications are summarized in this paper, including identification of a high angle of attack model with compressibility effects for a jet trainer; estimation of drag polars at high subsonic regime for a jet fighter; identification of aerodynamic model in real-time for a propeller-driven fighter; application of flight-path reconstruction techniques to spin tests, in order to correct errors in the air data sensors; and identification of power effects on the longitudinal stability of a propeller-driven trainer. The examples show that system identification has become crucial to 1) obtain accurate aerodynamic models for training in the flight-test simulator and 2) develop more efficient flight-test techniques.

Behavioral Indicator-Based Initial Flight Training Competency Assessment Model

Ensuring training safety is paramount to flight schools. In response to the inadequacy of traditional flight training assessment for comprehensive quantitative evaluation of cadet competency, an initial flight training competency assessment standard based on behavioral indicators was developed and optimized using the VENN model. Firstly, the Assessor Score Measurement Form (ASMF) was constructed according to the requirements of the Training Evaluation Worksheet specification, such as typical subjects, observations, and completion criteria. Secondly, based on the basic principles of the experience of the flight expert and the Competency-Based Training and Assessment (CBTA), a matrix of correlations between the observations and each competency-based behavioral indicator was created to construct a competency assessment matrix. In addition, a two-dimensional model for representing competency items characterized by behavioral indicators was established and an optimization model for competency assessment criteria was constructed. Finally, through combining actual flight training data, the proposed method was validated in the flight screening check phase. The results show that the optimized flight training competency assessment scheme can be well quantified and matched to real instructor ratings with an accuracy of 84%. The assessment worksheet, the assessment matrix, and the VENN competency rating model can be adapted to the different teaching requirements of each flight phase, achieving a perfect match between the behavioral indicators and the competency items, which is highly versatile. The proposed model can more accurately reflect the core competencies of flight trainees, enable quantitative assessment of behavioral indicators and competency items, and provide support for subsequent training of trainees.

Potential-Field-RRT: A Path-Planning Algorithm for UAVs Based on Potential-Field-Oriented Greedy Strategy to Extend Random Tree

This paper proposes a random tree algorithm based on a potential field oriented greedy strategy for the path planning of unmanned aerial vehicles (UAVs). Potential-field-RRT (PF-RRT) discards the defect of traditional artificial potential field (APF) algorithms that are prone to fall into local errors, and introduces potential fields as an aid to the expansion process of random trees. It reasonably triggers a greedy strategy based on the principle of field strength descending gradient optimization, accelerating the process of random tree expansion to a better region and reducing path search time. Compared with other optimization algorithms that improve the sampling method to reduce the search time of the random tree, PF-RRT takes full advantage of the potential field without limiting the arbitrariness of random tree expansion. Secondly, the path construction process is based on the principle of triangle inequality for the root node of the new node to improve the quality of the path in one iteration. Simulation experiments of the algorithm comparison show that the algorithm has the advantages of fast acquisition of high-quality initial path solutions and fast optimal convergence in the path search process. Compared with the original algorithm, obtaining the initial solution using PF-RRT can reduce the time loss by 20% to 70% and improve the path quality by about 25%. In addition, the feasibility of PF-RRT for UAV path planning is demonstrated by actual flight test experiments at the end of the experiment.

Development and Evaluation of an Enhanced Virtual Reality Flight Simulation Tool for Airships

A real-time flight simulation tool is proposed using a virtual reality head-mounted display (VR-HMD) for remotely piloted airships operating in beyond-line-of-sight (BLOS) conditions. In particular, the VR-HMD was developed for stratospheric airships flying at low/high altitudes. The proposed flight simulation tool uses the corresponding aerodynamics characteristics of the airship, the buoyancy effect, mass balance, added mass, propulsion contributions and ground reactions in the FlightGear Flight Simulator (FGFS). The VR headset was connected to the FGFS along with the radio controller containing the real-time orientation/state of each button, which is also simulated to provide better situational awareness, and a head-up display (HUD) that was developed to provide the required flight data. In this work, a system was developed to connect the FGFS and the VR-capable graphics engine Unity to a PC and a wireless VR-HMD in real time with minimal lag between data transmission. A balance was found for FGFS to write to a CSV file at a period of 0.01 s. For Unity, the file was read every frame, which translates to around 0.0167 s (60 Hz). A test procedure was also conducted with a similar rating technique based on the NASA TLX questionnaire, which identifies the pilot’s available mental capacity when completing an assigned task to assure the comfortability of the proposed VR-HMD. Accordingly, a comparison was made for the aircraft control using the desktop simulator and the VR-HMD tool. The results showed that the current iteration of the system is ideal to train pilots on using similar systems in a safe and immersive environment. Furthermore, such an advanced portable system may even increase the situational awareness of pilots and allow them to complete a sizeable portion of actual flight tests with the same data transmission procedures in simulation. The VR-HMD flight simulator was also conceived to express the ground control station (GCS) concept and transmit flight information as well as the point of view (POV) visuals in real-time using the real environment broadcast using an onboard camera.

Combustion characteristics of a supersonic combustor model for a JAXA flight experiment

JAXA is conducting a flight-ground test comparison program to clarify the “facility effect” on hypersonic aerodynamics and combustion phenomena and to develop a CFD tool for predicting flight data from ground test data. The aim is a flight experiment to obtain data on aerodynamic heating and supersonic combustion under actual flight conditions and to validate the CFD tool using flight data and the corresponding ground test data. This study aimed at determining a flow-path geometry and a fuel injector configuration for a supersonic combustor suitable for clarifying the influence of the different test flow compositions between flight and ground test conditions on combustion. The candidate configurations proposed by the CFD study were evaluated by direct-connect combustion tests using ethylene fuel. The results showed that a combustor flow was symmetric when the fuel equivalence ratio was low and asymmetric when the equivalence ratio and the pressure in the combustor were high. Because an asymmetric flow is unsuitable for validating CFD based on steady RANS, the total equivalence ratio was limited to 0.44. The combustor model uses two-stage fuel injectors and cavity flame holders to combust ethylene fuel. The depth of the cavity flame holder had little influence on combustion. However, the number of injection holes for the injector located downstream of the cavity affected the combustor pressure. The combustor flow-path design was finalized based on the combustion test results. In addition, an ethylene fuel ignition method using pilot hydrogen injection, adopted for the flight experiment, was also demonstrated successfully.

UAV High-Voltage Power Transmission Line Autonomous Correction Inspection System Based on Object Detection

With the development of technology, unmanned aerial vehicles (UAVs) are playing an increasingly important role in the inspection of high-voltage power transmission line. The traditional inspection method relies on the operator to manually control the drone for inspection. Although many companies are using real-time dynamic carrier phase differencing technology to achieve high-precision positioning of UAVs, when UAVs fly autonomously at high altitudes to photograph specific objects, the objects tend to deviate from the center of the picture. To address this error, in this paper, an autonomous UAV inspection system based on object detection is designed. (1) To detect inspection objects, the corresponding dataset is established on the basis of the UAV autonomous inspection task. (2) To obtain the position information of the target object, a lightweight object detector based on the YOLOX network model is designed. First, the backbone is replaced with MobileNetv3. Next, in the neck structure, the Ghost module is introduced and depthwise convolution is applied instead of normal convolution. Then, to embed the location information into the channel attention, coordinate attention is introduced after the output feature layer of the backbone, enabling the lightweight network to operate on a larger area of focus. Finally, to improve the accuracy of the bounding box regression, the α-DIOU loss function is introduced. (3) To obtain the best image acquisition position, the results of object detection combined with the real-time status of the UAV are used. (4) To enable the UAV to complete the final corrections, position control and altitude control are used. Compared to the original YOLOX tiny, the new model improves the mAP_0.5:0.95 metric by about 2 percentage points, with a significant reduction in the number of parameters and computation, while running at 56 FPS on Nvidia NX. This system can effectively solve the problem of the target deviating from the center of the picture when the UAV takes pictures during a high-altitude autonomous inspection, verified by many actual flight experiments.

Attitude control of a moving mass-actuated fixed-wing UAV based on LADRC

This paper concerns attitude control of a moving mass-actuated fixed-wing unmanned aerial vehicle (MFUAV). Unlike conventional roll motion of UAV, which is controlled by ailerons, this MFUAV uses the movement of mass block inside the wing to generate roll moment. It is difficult to design a suitable attitude controller for it due to the strong non-linearity and coupling of the MFUAV dynamics. Linear active disturbance rejection control (LADRC) proved to be a simple and effective alternative to conventional PID control. LADRC is able to eliminate disturbances with the help of extended state observer (ESO) and does not depend on the accurate mathematical models of particular systems. Finally, simulation results show that the attitude tracking control of MFUAV is well achieved with robustness. This shows that the designed method is easy to adapt and implement during the actual flight of the MFUAV.

An advanced warning model of airplane hard landing based on Adaboost

This paper breaks through the limitation of establishing early warning logic in the time dimension of the previous hard landing early warning model. In this research, flight altitude has been set as the scale of the corresponding early warning logic. According to the specific characteristics of the original flight parameter data set, the data preprocessing methods have been studied. The application of oversampling and frequency compression methods effectively solved the problems of different sample size and multi-frequency flight parameters in the original data set. On this basis, the method of ensemble learning is used to establish the early warning model of aircraft hard landing based on Adaboost. Further, the model is optimized to ensure the accuracy and generalization ability of the early warning model. Verified by the case study of the actual flight parameter data of Airbus A320 aircraft, the early warning model can realize high-precision prediction of hard landing events, which is of great significance for the improvement of the landing safety level of the aircraft in constructing both.

Trajectory planning and prescribed performance tracking control based on fractional-order observers for unmanned helicopters with unmeasurable states

The trajectory planning and tracking control problem is studied in this paper based on prescribed performance method (PPM) for the small-scale unmanned autonomous helicopter (UAH) with wind-gust disturbances (WGDs) and unmeasurable states. For the purpose, the nonlinear model with flapping dynamics is established, and the transformation performance function is used to ensure that the errors of trajectory tracking satisfy the corresponding performance. A fractional-order observer is designed for unmeasurable states to estimate the flapping angles in actual flight, and the fractional-order extended state observer (ESO) is constructed to estimate the WGDs, respectively. On the basis of PPM and the designed observers, the fractional-order theory-based backstepping trajectory tracking control scheme is developed for the UAH system, and the three-dimensional trajectory is planned by the improved wolf pack algorithm. Then the stability of the entire system is proven through strict theoretical analysis. Finally, the simulation analysis on the UAH is presented to demonstrate the efficiency of the designed method.

AB-INITIO PILOTS’ PERSPECTIVES ON THE USE OF SIMULATION IN THE AVIATION ENGLISH COURSE

Flying is costly, time-consuming, dependent on weather and maintenance, and sometimes simply does not match with schedules well. When flying a real aircraft is not a feasible or even preferable for one reason or another, a flight simulator could be remedy. Using a flight simulator to improve ab-initio pilots’ knowledge and abilities may make their flying experience more effective and enjoyable. In this respect, this study aims to enhance aviation training through simulation-based learning and develop an understanding of how prospective pilots perceive the innovative approach of simulation integration in Aviation English courses. The X-Plane version 11 was used in conjunction with an introductory course in Aviation English and provided a substitute for an actual flight test experience at an aeronautical university. The sampling consisted of 20 tertiary level students enrolled in the Aviation English course. After the intervention, randomly selected 7 students were interviewed to gain insights into their perceptions about the use of simulation.

Rapid reentry trajectory planning based on geometric-dynamic method

For the maneuvering trajectory planning of hypersonic gliding vehicles under complex constraints, the traditional dynamics methods are complex, and difficult to optimize the control variables to maximize the maneuvering potential of the vehicle. Inspired by the path planning method of low-speed unmanned aerial vehicles, a trajectory planning method combining geometry and dynamics is proposed. Firstly, the feasibility of the method is verified theoretically, the coupling point between the two methods is established, and the information transmission process of joint planning is clarified. Secondly, according to the actual flight, the minimum cost function with angle as the parameter is designed, so that the trajectory search process can meet the complex constraints. The simulation shows that under the premise of rapid trajectory planning, the proposed method can more fully control the change of bank angle and reduce the number of flips, which is conducive to the stability of the whole flight process.

Flight data-driven intelligent prediction for fuselage vibration of helicopter

PurposeHelicopter fuselage vibration prediction is important to keep a safety and comfortable flight process. The helicopter vibration mechanism model is difficult to meet of demand for accurate vibration prediction. Thus, the purpose of this paper is to develop an intelligent algorithm for accurate helicopter fuselage vibration analysis.Design/methodology/approachIn this research, a novel weighted variational mode decomposition (VMD)- extreme gradient boosting (xgboost) helicopter fuselage vibration prediction model is proposed. The vibration data is decomposed and reconstructed by the signal clustering results. The vibration response is predicted by xgboost algorithm based on the reconstructed data. The information transfer order between the controllable flight data and flight attitude are analyzed.FindingsThe mean absolute percentage error (MAPE), root mean square error (RMSE) and mean absolute error (MAE) of the proposed weighted VMD-xgboost model are decreased by 6.8%, 31.5% and 32.8% compared with xgboost model. The established weighted VMD-xgboost model has the highest prediction accuracy with the lowest mean MAPE, RMSE and MAE of 4.54%, 0.0162, and 0.0131, respectively. The attitude of horizontal tail and cycle pitch are the key factors to vibration.Originality/valueA novel weighted VMD-xgboost intelligent prediction methods is proposed. The prediction effect of xgboost model is highly improved by using the signal-weighted reconstruction technique. In addition, the data set used is collected from actual helicopter flight process.

Research on operating characteristics of single-spool turbojet enginewith the afterburner AL-21F

The single-spool, single-thread, turbojet engine with afterburner AL-21F has been used on fighter aircraft for a long time, but there are few studies on this engine in Vietnam. This article uses the theoretical approach, calibrates according to the technical description and actual operation, combined with specialised software such as GasTurb and GSP to calculate engine thermodynamic parameters in some actual flight conditions. The obtained results showed that, when the flight speed increases, the specific fuel consumption increases linearly, while the initial engine thrust decreases and reaches the minimum value at M=0.3÷0.5, then continue to increase and reach the maximum at the speed limit. When increasing the height, the speed and regulating spool speed of the engine remain the same, the engine thrust decreases as well as the specific fuel consumption increases. When increasing the rotor rotation speed, the engine thrust increases linearly but the specific fuel consumption decreases gradually and remains almost the same at engine rpm above 85%. The results allowed for a better understanding of the operating process of the AL-21F engine in particular and turbojet engines in general or used to build simulation models operating close to reality.

Stealth performance evaluation of helicopter against airborne early warning radar considering trimming control

Airborne pulse Doppler radar is a key threat to the military helicopter, and assessing the stealth performance of helicopter against airborne early warning radar is helpful to the helicopter’s stealth design and operational planning. In this paper, the Shooting and Bouncing Ray (SBR) and Uniform Theory of Diffraction (UTD) based high-frequency algorithms are used to calculate the Radar Cross Section (RCS) of helicopter, and the radar range equations are used to evaluate the stealth performance. In order to account for the effects of rotor flapping motions during actual flight, the aerodynamics model of whole helicopter is established and the attitudes and controls of helicopter at different flight states are trimmed and input into the RCS calculation module. The effects of helicopter flight speed, flying direction and operational environment on radar stealth performance are studied in focus. It is demonstrated by the results that the trimming control does have a great influence of more than 5 dB on the RCS of helicopter, and the introduction of the trim calculation brings the helicopter’s returns calculation closer to the reality. Variations in flight speed lead to the changes in the stealth performance of helicopter against Early Warning Aircraft (EWA), and the helicopter flight speed can be planned according to the operational requirements to minimize exposure distance or exposure time. Variations in flying direction mainly affect the detection properties of helicopter returns, and flying in the same direction with EWA usually gives the helicopter better low-observability than flying head-on. Variations in operational environment mainly affect the radar detection performance and the sensitivity of the detection performance to external factors; the same amount of change in some external factor causes a different amount of change in the helicopter’s detectability in different environments.

An econometric analysis for the determinants of flight speed in the air transport of passengers

Accurately determining an aircraft's flight speed is crucial for optimizing airline performance, as it directly impacts factors such as fuel consumption and emissions. Flying at speeds higher than what is recommended by the manufacturer can result in increased fuel burn. However, flying at slower speeds may lead to longer flight times and competitive disadvantages for airlines as passengers typically prefer shorter travel times. This study empirically investigates the driving forces in the decision-making process of airlines when setting flight speeds to reduce costs while maintaining the quality of service provided to customers. We develop econometric models of planned flight cruise speed and actual mean flight speed. We analyze a vast amount of data, comprising millions of domestic flights within Brazil. Our results allow for policy recommendations that identify opportunities for improvements in airline flight operations optimization, with implications for the environmental footprint of commercial aviation.

Research on Methods of Improving Fuel Efficiency

In recent years, the improvement of aircraft fuel efficiency has been one of the hot topics discussed by scientists. Especially in today's increasingly tense environment of fossil fuels, how to effectively improve the fuel efficiency of aircraft engines is an important scientific problem facing us. The improvement of aircraft fuel efficiency depends not only on high-performance engines, but also on the structural design of the aircraft itself. Therefore, if the aircraft structure can be optimized, it is bound to improve the fuel efficiency of the aircraft and make it have a better flight distance in actual flight. The purpose of this paper is to illustrate ways to reduce emissions while improving fuel efficiency. A small paper airplane experiment is introduced to study the influence of wing area on speed, time, lift, drag and lift drag ratio, so as to further explore the central theme of this paper, including the analysis of many physical models. It also includes many products and ideas that engineers are now designing.

Continuous Low-Thrust Maneuver Planning for Space Gravitational Wave Formation Reconfiguration Based on Improved Particle Swarm Optimization Algorithm

This study proposes a three-spacecraft formation reconfiguration strategy of minimum fuel for space gravitational wave detection missions in the high Earth orbit (105 km). For solving the limitations of measurement and communication in long baseline formations, a control strategy of a virtual formation is applied. The virtual reference spacecraft provides a desired relative state between the satellites, which is then used to control the motion of the physical spacecraft to maintain the desired formation. A linear dynamics model based on relative orbit elements' parameterization is used to describe the relative motion in the virtual formation, which facilitates the inclusion of J2, SRP, and lunisolar third-body gravity effects and provides a direct insight into the relative motion geometry. Considering the actual flight scenarios of gravitational wave formations, a formation reconfiguration strategy based on continuous low thrust is investigated to achieve the desired state at a given time while minimizing interference to the satellite platform. The reconfiguration problem is considered a constrained nonlinear programming problem, and an improved particle swarm algorithm is developed to solve this problem. Finally, the simulation results demonstrate the performance of the proposed method in improving the maneuver sequence distribution and optimizing maneuver consumption.