Stages Of Flight Research Articles

Virtual reality application in pilotage training: a comparative analysis of real flights

Virtual reality technology has been in a development trend since 1966 when it was used as a flight simulator. Since this technology emerged as a training area, has been used in the public sector for 25 years. According to the purpose of study, three main flight stages are determined. These are take-off stage, controlling air movements in traffic pattern, approach and landing stage. External and internal controls, engine start, taxi and take-off tasks are analysed under take-off stage. Climb, ascending, and cruise flight, low and normal bank turns, turns in climb and descent, speed altitude tracking tasks are analysed under controlling air movements in traffic pattern. Triangulation tracking, approach pattern, landing, and leaving the runway, taxiing tasks are analysed under approach and landing stage. Forty one pilotage students are analysed, and the findings showed a statistical difference between VR and real flight performances in Speed Altitude Tracking, Approach Pattern tasks that real flight scores were relatively higher. Additionally, a statistical difference was found between VR and Real Flight Performances related to Approach and Landing stage different from two other stages. To summarize, a significant similarity in terms of grades between VR and real flight experience was found excluding two tasks.

Fault-tolerant hierarchical energy management system for an electrical power system on more-electric aircraft

The concept of More-Electric Aircraft (MEA) has the potential to improve the environmental, economic, and reliability performance in the energy and transportation sectors. To achieve this potential, it has become a tendency to develop complex architectures of Electrical Power Systems (EPSs) for MEA to supply increasing electrical power demands. Moreover, a reliable and intelligent Energy Management System (EMS) is critical to coordinate the various EPS subsystems to ensure safe and efficient flight, following the real-time EPS operating requirements and safety criteria, while reducing the operating costs for all flight stages. This paper presents a fault-tolerant hierarchical EMS, for an innovative multi-converter-based aircraft EPS, to configure the system, ensure power distribution, and manage energy storage in multiple faulty scenarios over different time scales. There are two levels in this EMS: The High Level (HL) is based on Model Predictive Control (MPC), formulated by Mixed-Integer-Linear-Programming (MILP), to optimise the long-term EPS performance while considering future predictions; The Low Level (LL) adopts deterministic rules to cope with load changes and fault occurrences over the short term, during the HL sample intervals, with a faster clock. In particular, the LL controller contains four modes: to either cooperate with the HL online MPC or to operate independently, in either EPS normal or faulty conditions. The proposed EMS is evaluated in two cases, firstly considering load deviations in a normal operating scenario, and then considering behaviour in fault scenarios. The results indicate that the proposed EMS successfully reduces the EPS operational costs while ensuring quick responses to dynamic changes with either EPS component faults or EMS internal faults.

Blood Proteome Study to Assess the Regulation of Angiogenesis in Cosmonauts After the End of the Flight

A study of blood samples of 18 cosmonauts who had long flights as members of Russian crews of the International Space Station was performed using the method of quantitative proteomics based on mass spectrometry. The study was focused on elucidation of possible connection of proteome changes under the influence of space flight (SF) factors with the processes of angiogenesis. The analysis was performed with a targeted panel of 125 labeled 13C/15N peptides using chromatography-mass spectrometry with multiple reaction monitoring (LC/MRM-MS). A total of 125 different proteins were quantitatively characterized. Among them, a group of 61 proteins involved in the processes of angiogenesis and its regulation was found. Bioinformatic methods showed that the isolated angiogenesis proteins were participants of 13 biological processes, including lymphangiogenesis. Significant changes of protein level in blood after landing, in relation to preflight samples, were observed in 7 cases. The results have shown that the elimination of gravity (microgravity), space radiation and overloads of the final stage of flight have a combined effect on the processes of angiogenesis, which is manifested by changes in proteomic composition on 1 day after the completion of long-term CP.

Environmental sustainability performance of US airlines: implications of financial performance and technical efficiency

Air transportation significantly contributes to global CO2 emissions. The US Aviation Climate Action Plan introduced in November 2021 aims to decarbonize the aviation sector by 2050. Aligned with this initiative, our study applies Data Envelopment Analysis and fixed-effect panel regression to empirically explore how financial performance and technical efficiency impact Environmental Sustainability Performance (ESP) in the airline industry. We curated panel data of nine US passenger airlines from 2010 to 2019 to examine three key areas: the impact of financial performance on environmental sustainability performance, the influence of efficiency on environmental sustainability performance, and the relationship between flight stage length and environmental sustainability performance. Our findings indicate that improved Financial Performance, higher technical efficiency, and longer stage lengths positively contribute to enhanced environmental sustainability performance. Our study provides valuable insights for managers and policymakers, emphasizing the pivotal role of financial stability in achieving environmental goals within the airline industry. It underscores the intricate connection between economic viability and sustainability, offering guidance for policymakers seeking to balance financial success with environmental goals.

Intelligent control algorithms to ensure the flight safety of aerospace vehicles

An overview of the architectures, functions and algorithms of aircraft-type aerospace vehicles equipped with fly-by-wire (FBW) digital integrated control systems (ICS) is given. The ICS has a hierarchical architecture, including the primary, backup and emergency control systems with a sophisticated control reconfiguration logic in the event of failures. Digital control computers have dissimilar redundancy of equipment and software. At the atmospheric flight stage, integrator control laws provide the specified control characteristics, flight envelope protection, automatic trim of vehicle and crew workload alleviation. Further integration of manual and automatic control, implementation of the control philosophy as a continuation of the pilot's actions, more intellectual control system and human-machine interface, use of multiple control surfaces to ensure optimal vehicle configuration and alleviate structural loading together with basic control functions are considered as promising areas for ICS improvement.

Proteome of Dried Blood Spots of Cosmonauts during a 6-Month Flight

For successful exploration of near space, construction of planetary bases and exploration of the Solar System planets, it is necessary to fill the gaps in understanding the molecular mechanisms of the human body response to space flight (SF) conditions. Subsequently, this will make it possible to get closer to the discovery of potential molecular targets for protection against adverse processes occurring in the body under the influence of SF conditions. The aim of the work was to assess the effect of a 6-month space flight on the proteome of dried blood spots of cosmonauts. As a result of proteomic analysis, processes with highly and moderately enriched proteins were identified. Among them, processes with reliable dynamics were identified on the 7th day of SF, as well as on the 3rd and 6th months of flight: these are clusters of energy processes, presentation of molecules on the membrane, initiation of immune defense, proteostasis and metabolism. Biological processes were identified in which the representation of proteins decreased most significantly, which was reflected in a weakening of activity in the presentation of molecules on the membrane, the initiation of immune defense, as well as in the mechanisms of proteostasis in the acute period of adaptation to the factors of the initial stage of flight. It has been shown that there is a close interaction with proteins of the cytoskeleton organization that disappear or reappear in the dried blood spots proteome during flight, and that relate to processes whose activity significantly decreased during SF (immune system, proteostasis, metabolism).

An estimation method for vision-based autonomous landing system for fixed wing aircraft

In this paper, we propose a vision-based estimation method for autonomous landing of fixed-wing aircraft for Advanced Air Mobility. The concept of autonomous flight with minimal human intervention has gained significant interest with a particular focus on autonomous landing. The goal is to overcome the limitations of existing instrument landing systems and reduce reliance on GNSS during aircraft landing. The proposed system leverages the following techniques for high-performance and real-time operations in various real-world environments and during all stages of landing. A deep learning segmentation model was directly learned, created, and used for robust runway recognition performance against environmental changes around the runway. Algorithms were designed to adapt to different flight stages considering the varying information offered by image data when the aircraft is in mid-air and on the ground. The relative lateral position from the aircraft to the runway was estimated using bird’s-eye-view conversion and inverse projection techniques instead of conventional perspective-n-point methods for reducing the recognition error occurring from the conversion between 2D image and 3D world. Finally, the mixed-precision technique was used for the segmentation model to improve inference speed and ensure real-time operation in real-world deployment. Estimation stability and reliability were improved by using a Kalman Filter to cope with sensor uncertainties caused by the real-world flight environment. Consequently, we show that the average error in the lateral position estimation by the proposed method is comparable to the accuracy of a single GNSS and demonstrate successful autonomous landing of our test aircraft with a set of flight tests.

Risk assessment method for civil aircraft approach and landing at high plateau based on QAR data

Civil aircraft approach and landing at high altitude is a high-risk stage of plateau flight. In order to effectively implement the risk identification and grade judgment of approach and landing at high altitude, an LSTM-DNN deep learning risk assessment method based on variable fuzzy recognition with weights removed is proposed. This method is first based on the high-altitude flight data recorded by the quick access recorder (QAR), and draws on the civil aircraft flight quality monitoring project specification (FOQA) consultation notice and industry QAR monitoring standards. Combined with the indicator importance analysis and Delphi expert survey, five key monitoring items are extracted as the risk assessment indicators of civil aircraft approach and landing at high altitude, including large heading change during landing, low track, large descent rate during 2000-1000 ft approach, vertical acceleration at touchdown, and large descent rate during 500-50ft approach. Then, in order to overcome the subjective bias of the evaluation indicator weight, the weight of the evaluation indicator is determined by the weight removal method, and the risk grade membership function is constructed based on the variable fuzzy recognition method. Finally, a risk assessment model for civil aircraft approach and landing at high altitude based on LSTM-DNN is established. Taking the Chengdu-Lhasa approach and landing segment as an example, the QAR data was extracted to train and test the risk assessment model, and the results were compared with those of Logistic multivariate regression, support vector machine (SVM) and other evaluation methods. The results show that the average recognition rate of the LSTM-DNN deep learning model based on variable fuzzy recognition with weights removed reaches 94.18%, and the highest can reach 94.79%, which verifies the objective effectiveness of the risk assessment method.

Формування траєкторії керованих літальних апаратів

Currently, there is an increased interest in the creation of flight control systems for unmanned aerial vehicles, which, taking into account real conditions, would ensure its trajectory and thereby determine the effectiveness of the use of the aerial vehicle. Aircraft navigation, in particular ballistic cruise missiles, requires the formation of high-precision control in order to achieve both final results and local optimization tasks at each of the flight stages: take-off, departure to set trajectories, maneuvering, etc. The development of admissible control and its optimization by computer-mathematical methods of modeling and optimization is a time-consuming process and requires significant expenditures of various types of resources. An element of the effectiveness of such a mathematical apparatus for guaranteeing and increasing the reliability and effectiveness in achieving the set goal is the speed of calculations, which, in turn, requires the simplification of the mathematical model by obtaining functional dependencies for calculating the flight trajectory, avoiding complex mathematical calculations. The complete working model for calculating the desired trajectory of the aircraft will be determined by the specified control functions and will be provided by a system of partial differential equations with time, and the necessary parameters for calculating all aerodynamic forces and moments are tabular data in most cases. A mathematical model for solving the task of forecasting navigation for such complex controlled systems is proposed to be carried out using two coordinate systems: starting and speed. Moreover, all calculations of the velocity vector, which depends on the net effect of three aerodynamic forces acting on the aircraft, should be carried out in the speed coordinate system, and coordinate control of the flight along the entire dynamic trajectory should be determined in the starting system

ДОСЛІДЖЕННЯ ТА АЛГОРИТМИ ІНТЕГРОВАНОГО КЕРУВАННЯ ГРУПОЮ БЕЗПІЛОТНИХ ЛІТАЛЬНИХ АПАРАТІВ

The main prospects for the group use of unmanned aerial vehicles (UAVs) were analyzed, the problems were identified, and the stages of its solution were proposed. The basic algorithms are analyzed, which are designed to achieve joint and coordinated actions of all elements of the system of integrated control of a group of UAVs, and are used in most approaches to ensure stable interaction between system components. The analysis of the most common mathematical models for controlling groups of UAVs was carried out, in particular: the Reynolds cohesion model, the artificial potential field model, and the leader-following model. The peculiarities of the operation of these models, common and distinctive features, advantages and disadvantages are determined. Based on the considered models and basic interaction algorithms, the algorithms of the components of the UAV group control system are proposed, and the sequence of actions during the interaction between the system components is also described. The main details of UAV group control algorithms are considered. The main aspects of the interaction of the system elements are given, which include messages of various categories used at different stages of the system's operation, in particular: synchronizing messages; group-wide control messages for managing the group as a whole; messages for correcting the flight of a specific UAV; notification of the transfer of statistical information for flight correction; notification of the launch and coordination of the task execution by a specific UAV. The use of joint messages for group management is described, which allows you to relieve the transmission channel, because the flight trajectories are calculated by each UAV individually, according to predetermined criteria. The main stages of the system's operation, the peculiarities of their implementation, the sequence of message transmission in each stage, as well as the basic details of the operation of some system components are described. Block diagrams are provided to display the process of system operation at various stages of flight, with a detailed description of the steps of system operation. The process of collecting statistical data from UAVs for dynamic flight adjustment of the group is described.

Expansion wave-reinforced initiation of the oblique detonation wave

Efficient initiation of oblique detonation waves (ODWs) is crucial for optimizing the performance of oblique detonation wave engines. A novel approach is proposed for enhancing ODW initiation through expansion waves in this research. Validation of the expansion wave-reinforced initiation method is conducted via numerical simulations employing multi-species reactive Euler equations and a pressure-dependent reaction mechanism. Results demonstrate a significant reduction in the initiation length of ODWs with the addition of an expansion wave ahead of the wedge, contrasting with the absence of detonation wave initiation on a wedge lacking an expansion wave. A theoretical model, based on expansion wave and shock wave relations, along with constant volume combustion theory, elucidates the underlying mechanism of reinforcement. The model reveals that crossing the expansion wave elevates the fluid's Mach number and locally enlarges the flow deflection angle on the wedge surface, without altering the wedge's structure. Furthermore, post-shock temperature increases and pressure decreases compared to the wedge not encountering an expansion wave. The heightened temperature predominantly triggers ODW initiation, thus reinforcing the process. Theoretical analyses indicate the reinforcement's greater efficacy at lower inflow temperatures and lower inflow Mach numbers, suggesting the expansion wave's suitability for initiation in the early flight stages of an aircraft equipped with oblique detonation wave engines.

Rapid and Near-Analytical Planning Method for Entry Trajectory under Time and Full-State Constraints

A rapid trajectory-planning method based on an analytical predictor–corrector design of drag acceleration profile and a bank-reversal logic based on double-stage adaptive adjustment is proposed to solve the entry issue under time and full-state constraints. First, an analytical predictor–corrector algorithm is used to design the profile parameters to satisfy the terminal of altitude, velocity, range, time, and flight-path angle constraints. Subsequently, an adaptive lateral planning algorithm based on heading adjustment and maintenance is proposed to achieve the flight stage adaptive division and determination of the bank-reversal point, thereby satisfying the terminal position and heading angle constraints. Concurrently, a rapid quantification method is proposed for the adjustable capacity boundary of the terminal heading angle. On this basis, a range-and-time correction strategy is designed to achieve high precision and the rapid generation of a three-degree-of-freedom entry trajectory under large-scale lateral maneuvering. The simulation results demonstrated that compared with the existing methods, the proposed method can adaptively divide flight stages, ensuring better multitask applicability and higher computational efficiency.

Research of integrated spiral maneuvering and guidance based on virtual target

To address the issue of interception, maneuvering, and precise guidance during the final stage of gliding flight, a study was conducted on the design of integrated maneuvering and guidance using a spiral trajectory as the focus. Firstly, the spiral trajectory was decomposed into an optimal reference trajectory considering the glide angle constraint and a relative motion trajectory. Then, virtual circular moving targets were introduced to meet the requirements of spiral maneuvering and virtual trajectory moving targets were introduced to ensure trajectory convergence, based on the task division of different flight stages. Finally, the guidance rate of the reference trajectory was designed based on optimal control theory, and the guidance rate of the spiral maneuver was designed based on pure proportional guidance. Simulation results show that this guidance method can enable the vehicle to perform active spiral maneuvers, and control the landing deviation and impact angle deviation to within 2.5 m and 1 degree, respectively.

Optimization of Power Prediction of BP Network with Improved Pelican Algorithm

Abstract In view of the large fluctuation of photovoltaic output power affected by different weather, accurate prediction of photovoltaic output power is particularly important for the safe and stable operation of power system. Firstly, the pelican optimization algorithm ( POA ) is improved in the following three aspects : adding Circle chaotic map to make the population evenly distributed, introducing mutation factor to expand the search range of pelican when approaching prey, adding adaptive weight and firefly disturbance to avoid falling into local optimum in the water surface flight stage ; then, in order to improve the prediction accuracy of BP algorithm, the improved pelican algorithm ( IPOA ) is used to optimize the weights and thresholds of BP neural network, and the IPOA-BP photovoltaic power prediction model is built to improve the accuracy of power prediction. Finally, this paper tests the prediction performance of IPOA-BP, POA-BP and basic BP power prediction models in sunny, cloudy and rainy days through experiments. The experimental results demonstrate that the IPOA-BP prediction model outperforms both the POA-BP and traditional BP neural network models under various weather conditions.

Dual-stage control method for continuous hopping on the surface of small celestial bodies

Surface movement exploration techniques are an important approach to further the understanding of small celestial bodies. Hopping movement is employed to take advantage of the weak gravitational field of small celestial bodies, facilitating long-distance mobility of the rover. The rover exhibits a strong attitude-orbit coupling characteristic during the hopping movement. Different contact attitudes contribute to the challenge of determining the rebound trajectory, rendering it difficult for the rover to maintain continuous movement towards the target position along the nominal trajectory. In this paper, a dual-stage control method for continuous surface hopping movement is developed, wherein the control is applied separately during the flight stage and the collision stage. During the flight stage, applying attitude control enables the rover to establish contact with the surface in a specific attitude, ensuring accuracy in movement direction and creating favorable conditions for the control process in the collision stage. The flywheel is controlled in the collision stage to correct the state change and energy loss due to the collision, enabling the rover to attain the desired hopping state. Considering the energy consumption of the rover, the minimum hopping velocity sequence and angular velocity sequence are designed based on the hopping angle and heading angle. The intricacies and uncertainties inherent in the surface environment of small celestial bodies pose challenges for the rover during hopping and flying. In response to the issue, a finite-time adaptive sliding-mode control law is devised. The control law facilitates the rapid adjustment of the rover to the target attitude in flight, demonstrating strong robustness. In addition, by integrating the changes in contact point velocity with the impulse contact model, the accuracy of the rover's rebound state updates is enhanced. Finally, a set of simulations is performed, and simulation results indicate that the dual-stage control method can achieve a final landing position error of less than 0.2 m for a continuously hopping. The finite-time adaptive sliding-mode control law can stabilize the rover's attitude within 10 s. Conducting 500 Monte Carlo simulations of the continuously hopping rover in three small celestial body surface simulation environments shows that the position endpoint error is within 0.3 m.

NUMERICAL RESEARCH OF THE INFLUENCE OF CONTROL RUDDERS ON THE AERODYNAMIC CHARACTERISTICS OF THE K110 SU SUBORBITAL ROCKET

Abstract. Aerodynamic research plays an important role in the development and design of aircraft. In particular, such studies can evaluate the characteristics of suborbital rockets in terms of maximum range, altitude and speed, determine the stability and controllability properties, and assess the mechanical loads acting on structural elements. An important aspect of aerodynamic analysis is the determination of aerodynamic forces and torques. This paper investigates and analyzes the aerodynamic characteristics of the K110 SU ultralight class suborbital rocket, taking into account the effect of control rudder deflection. The study was carried out by means of numerical modeling methods based on the Navier-Stokes equations using the SST k-ω turbulence model. The features of the flow around the surface of the rocket body in subsonic, transonic, and supersonic modes at the deviation of the control surfaces in the range of ±10° are analyzed. The data on the main aerodynamic characteristics of the rocket depending on the flight speed and the angle of deflection of the control surfaces were obtained. The structure of the flow, namely the vortex structures formed behind the control surfaces of the aerodynamic rudders and their interaction with the rocket stabilizers, is investigated. The obtained results allow for a deeper understanding of how rudder deflection affects the behavior of the rocket in the atmosphere at the stages of flight from subsonic to supersonic speeds and will be used to further develop the control system of the K110 SU ultralight rocket and optimize its aerodynamic characteristics. The results will be used in the development and design of the control system of the rocket.

Design of a UAV Trajectory Prediction System Based on Multi-Flight Modes

With the burgeoning impact of artificial intelligence on the traditional UAV industry, the pursuit of autonomous UAV flight has emerged as a focal point of contemporary research. Addressing the imperative for advancing critical technologies in autonomous flight, this paper delves into the realm of UAV flight state recognition and trajectory prediction. Presenting an innovative approach focused on improving the precision of unmanned aerial vehicle (UAV) path forecasting via the identification of flight states, this study demonstrates its efficacy through the implementation of two prediction models. Firstly, UAV flight data acquisition was realized in this paper by the use of multi-sensors. Finally, two models for UAV trajectory prediction were designed based on machine learning methods and classical mathematical prediction methods, respectively, and the results before and after flight pattern recognition are compared. The experimental results show that the prediction error of the UAV trajectory prediction method based on multiple flight modes is smaller than the traditional trajectory prediction method in different flight stages.

Pilot Perceptions of Wire Strikes in Agricultural Aviation Operations.

INTRODUCTION: Agricultural aircraft operations are associated with unique challenges. In particular, these include maintaining awareness of obstacles associated with flight at very low altitudes. Wire strikes are a common cause of accidents in these operations.METHODS: Focus groups were completed during the 2022 Ag Aviation Expo hosted by the National Agricultural Aviation Association with pilots who had experienced wire-strike events (N = 22). The researchers coded the transcripts using a human factors framework.RESULTS: Notably, unplanned "trim passes" were a key stage of flight during wire-strike events. Cognitive risk factors that may have affected their performance included situation awareness, decision-making choices, and pressure to perform. Over half of subjects reported being aware of the wire before collision. Possible prevention strategies include not spraying the field due to safety risks, paying better attention to where they were in the field, and avoiding deviation from the planned route.DISCUSSION: Wire-strike events often occur due to momentary lapses in attention, even when the pilot is already aware of the wire. This study shows that targeted approaches to prevent wire strikes in agricultural aviation operations require addressing a number of cognitive risks and human factors, rather than implementing increased preflight surveillance. These results have implications for preventing future wire-strike accidents based directly on pilot perceptions, both within agricultural operations and general aviation more broadly.Baumgartner HM, DiDomenica R, Hu PT, Thomas S. Pilot perceptions of wire strikes in agricultural aviation operations. Aerosp Med Hum Perform. 2024; 95(6):305-312.

Tuning hydrogen boil-off via inert gas insulation purge in a vapor cooled shielded fuel tank

Vapor cooled polymer composite tanks for liquid hydrogen are a newopportunity for light weight power-system integration into unmanned aerial vehicles. Vapor shielding has the ancillary benefit of pre-conditioning the hydrogen for use by a fuel cell. However, the mass flow rate required by a fuel cell should be matched by the natural boil-off rate of the tank. With limited ability to vary insulation thicknesses, the challenge becomes satisfying the fuel cell consumption in UAVs at different mass flow rates when at varying stages of flight from take-off, cruise, and landing. This paper provides experimental measurements of mass flow rate of hydrogen from the tank considering batch purging with helium or argon in the vapor cool shielded insulation layer. A 5-shell vapor cooled shielded tank is used with two layers of insulation including aerogel, helium or argon, and two vapor channels. A more complete understanding of system-level thermal conductance is determined by mass flow of hydrogen leaving the tank during hypothetical flight.

Hypergravity Impact on Fertility of Apis mellifera carnica Queens – Case Study

The launch is considered the most stressful rocket flight stage due to the hypergravity occurrences. The possibility of using honey bees (Apis mellifera) as the extraterrestrial pollinator depends on their ability to reproduce correctly after experiencing hypergravity. The described study aims to verify the impact of a launching rocket’s acceleration on honey bee queen’s egg-laying behavior. Four artificially inseminated A. mellifera carnica queens were placed in the Human Training Centrifuge and given to the acceleration pattern of the launching Soyuz rocket. Next, the data on the number of food stores, eggs, larvae, and worker and drone pupae were collected from the test and control hives using the modified Liebefeld method. The pilot study results imply that accelerated queen’s egg-laying behavior may change twofold: limiting or maximizing the number of laid eggs, with the control queen egg-laying rate remaining stable for all samples. The number of drone pupae is greater for the test sample colonies, with its earlier appearance in the hive. No impact on overwintering success was observed. Authors indicate limitations of the results and a need to continue the study to verify the occurrence of anomalies potentially related to the examined factor.