Flight Design Research Articles

Stratospheric airship trajectory planning in wind field using deep reinforcement learning

Stratospheric airships, with their long endurance, high flight altitude, and large payload capacity, show promise in earth observation and mobile internet applications. However, challenges arise due to their low flight speed, limited maneuverability and energy constraints when planning trajectories in dynamic wind fields. This paper proposes a deep reinforcement learning-based method for trajectory planning of stratospheric airships. The model considers the motion characteristics of stratospheric airships and environmental factors like wind fields and solar radiation. The soft actor-critic (SAC) algorithm is utilized to assess the effectiveness of the method in various scenarios. A comparison between time-optimized and energy-optimized trajectories reveals that time-optimized trajectories are smoother with a higher speed, while energy-optimized trajectories can save up to 10% energy by utilizing wind fields and solar energy absorption. Overall, the deep reinforcement learning approach proves effective in trajectory planning for stratospheric airships in deterministic and dynamic wind fields, offering valuable insights for flight design and optimization.

Multi-disciplinary optimization of single-stage hybrid rockets for lunar ascent

This study aims to determine the optimal design and ascent trajectory for a single-stage hybrid rocket in the context of a lunar ascent mission, with the objective of reaching a 100 km circular orbit on the Moon equatorial plane. A multi-disciplinary optimization problem is formulated, integrating flight design variables and launch vehicle design variables to achieve the best mission scenario. A zero-dimensional internal ballistics model is employed to estimate key parameters such as thrust, mass flow rate, and gross mass of the hybrid rocket, while a three-degree of freedom dynamical model is utilized to simulate the ascent trajectory. The resulting integrated optimization problem is solved using an in-house heuristic algorithm that combines particle swarm and genetic algorithms. Two propellant combinations, liquid oxygen/paraffin-wax and hydrogen peroxide (90%)/high-density polyethylene, are evaluated, considering both their performance in the integrated system and the feasibility of the proposed mission. After conducting a sensitivity analysis to investigate the influence of particle count in the optimization process, results for both propellant combinations are presented. While paraffin and oxygen provide the highest payload ratio, hydrogen peroxide and polyethylene entail a more feasible and flexible design for a lunar mission.

Investigation into Camera Calibration Flight Paths for UAV-Based Corridor Surveys

Abstract. There is increasing adoption of cost-effective nonmetric camera-equipped unmanned aerial vehicles due to the perceived benefits of timesaving, ease of use, and the accuracy of the digital elevation models that can be produced using structure from motion software. The introduction of systematic elevation errors, doming and bowing, has been evidenced by several authors, and various methods have been identified to reduce these errors. This paper aims to analyse the impact of flight plans on these systematic errors using the especially challenging case of a corridor survey. Two sites were flown for the survey using a DJI Zenmuse. The first site, a car park, was utilised for on-the-job pre-calibration of the camera and consisted of several orbit flights and a double grip flight. Subsequently, an adjacent road (a corridor survey overall 428 m long) was also surveyed at 60 m and 80 m heights using varying flight configurations. This study confirms that pre-calibrating the camera's IOPs significantly reduces the root mean squared elevation error (from 0.268 m to 0.034 m) compared to self-calibrated IOPs using the corridor flights. The impact of flight design on elevation errors confirms a single flight path's risk and the benefits of two or more flight paths, including a point-of-interest orbit flight.

Banana Plant Waste Rotary Dryer Design and Simulation Using 3D Computer Aided Design

This research determines the optimal rotary dryer design for banana waste drying with Biot number. When banana waste is adequately dried, it can be repurposed into valuable resources. Based on the proposed banana plant waste rotary dryer, drying efficiency is significantly improved compared to conventional dryers as attributed to design calculations and simulation. Here, the design process involves the three-dimensional (3D) computer-aided design of individual parts, subassemblies, and main assembly, accompanied by detailed illustration drawings, and optimization of rotary dryer flight design. Biot number is crucial in the design calculations of the diameter and length of the dryer. The Design of Experiments (DoE) and computational fluid dynamics simulations are also used. Proper drying, facilitated by the proposed rotary dryer, enables efficient repurposing of banana waste into animal feed, biofuel, bioplastics, and other nanotechnology applications, contributing to sustainable waste management practices and a promising solution to environmental challenges.

Transfer-Learning-Enhanced Regression Generative Adversarial Networks for Optimal eVTOL Takeoff Trajectory Prediction

Electric vertical takeoff and landing (eVTOL) aircraft represent a crucial aviation technology to transform future transportation systems. The unique characteristics of eVTOL aircraft include reduced noise, low pollutant emission, efficient operating cost, and flexible maneuverability, which in the meantime pose critical challenges to advanced power retention techniques. Thus, optimal takeoff trajectory design is essential due to immense power demands during eVTOL takeoffs. Conventional design optimizations, however, adopt high-fidelity simulation models in an iterative manner resulting in a computationally intensive mechanism. In this work, we implement a surrogate-enabled inverse mapping optimization architecture, i.e., directly predicting optimal designs from design requirements (including flight conditions and design constraints). A trained inverse mapping surrogate performs real-time optimal eVTOL takeoff trajectory predictions with no need for running optimizations; however, one training sample requires one design optimization in this inverse mapping setup. The excessive training cost of inverse mapping and the characteristics of optimal eVTOL takeoff trajectories necessitate the development of the regression generative adversarial network (regGAN) surrogate. We propose to further enhance regGAN predictive performance through the transfer learning (TL) technique, creating a scheme termed regGAN-TL. In particular, the proposed regGAN-TL scheme leverages the generative adversarial network (GAN) architecture consisting of a generator network and a discriminator network, with a combined loss of the mean squared error (MSE) and binary cross-entropy (BC) losses, for regression tasks. In this work, the generator employs design requirements as input and produces optimal takeoff trajectory profiles, while the discriminator differentiates the generated profiles and real optimal profiles in the training set. The combined loss facilitates the generator training in the dual aspects: the MSE loss targets minimum differences between generated profiles and training counterparts, while the BC loss drives the generated profiles to share analogous patterns with the training set. We demonstrated the utility of regGAN-TL on optimal takeoff trajectory designs for the Airbus A3 Vahana and compared its performance against representative surrogates, including the multi-output Gaussian process, the conditional GAN, and the vanilla regGAN. Results showed that regGAN-TL reached the 99.5% generalization accuracy threshold with only 200 training samples while the best reference surrogate required 400 samples. The 50% reduction in training expense and reduced standard deviations of generalization accuracy achieved by regGAN-TL confirmed its outstanding predictive performance and broad engineering application potential.

Systematic review and best practices for drone remote sensing of invasive plants

Abstract Drones have emerged as a cost‐effective solution to detect and map plant invasions, offering researchers and land managers flexibility in flight design, sensors and data collection schedules. A systematic review of trends in drone‐based image collection, data processing and analytical approaches is needed to advance the science of invasive species monitoring and management and improve scalability and replicability. We systematically reviewed studies using drones for plant invasion research to identify knowledge gaps, best practices and a path toward advancing the science of invasive plant monitoring and management. We devised a database of 33 standardized reporting parameters, coded each study to those parameters, calculated descriptive statistics and synthesized how these technologies are being implemented and used. Trends show a general increase in studies since 2009 with a bias toward temperate regions in North America and Europe. Most studies have focused on testing the validity of a machine learning or deep learning image classification technique with fewer studies focused on monitoring or modelling spread. Very few studies used drones for assessing ecosystem dynamics and impacts such as determining environmental drivers or tracking re‐emergence after disturbance. Overall, we noted a lack of standardized reporting on field survey design, flight design, drone systems, image processing and analyses, which hinders replicability and scalability of approaches. Based on these findings, we develop a standard framework for drone applications in invasive species monitoring to foster cross‐study comparability and reproducibility. We suggest several areas for advancing the use of drones in invasive plant studies including (1) utilizing standardized reporting frameworks to facilitate scientific research practices, (2) integrating drone data with satellite imagery to scale up relationships over larger areas, (3) using drones as an alternative to in‐person ground surveys and (4) leveraging drones to assess community trait shifts tied to plant fitness and reproduction.

Combining Multi-View UAV Photogrammetry, Thermal Imaging, and Computer Vision Can Derive Cost-Effective Ecological Indicators for Habitat Assessment

Recent developments in Unmanned Aircraft Vehicles (UAVs), thermal imaging, and Auto-machine learning (AutoML) have shown high potential for precise wildlife surveys but have rarely been studied for habitat assessment. Here, we propose a framework that leverages these advanced techniques to achieve cost-effective habitat quality assessment from the perspective of actual wildlife community usage. The framework exploits vision intelligence hidden in the UAV thermal images and AutoML methods to achieve cost-effective wildlife distribution mapping, and then derives wildlife use indicators to imply habitat quality variance. We conducted UAV-based thermal wildlife surveys at three wetlands in the Rainwater Basin, Nebraska. Experiments were set to examine the optimal protocols, including various flight designs (61 and 122 m), feature types, and AutoML. The results showed that UAV images collected at 61 m with a spatial resolution of 7.5 cm, combined with Faster R-CNN, returned the optimal wildlife mapping (more than 90% accuracy). Results also indicated that the vision intelligence exploited can effectively transfer the redundant AutoML adaptation cycles into a fully automatic process (with around 33 times efficiency improvement for data labeling), facilitating cost-effective AutoML adaptation. Eventually, the derived ecological indicators can explain the wildlife use status well, reflecting potential within- and between-habitat quality variance.

Integration of Electronic Displays on Fixed Wing Transport Aircraft: A Vionics Certification

Electronic Flight Display System certification can present wide challenges in showing compliance with many existing regulatory requirements. This paper provides a guidance for manufacturers, system integrators and airworthiness authorities for the design, integration, and approval of electronic flight displays for fixed wing transport aircraft. Discussion on various existing standards available for aircraft electronic displays with their means of compliance at various stages of system certification has been presented in this paper. Detailed failure hazards associated with the failure of display functions are also provided in the paper.

A Real-Time Measurement Model of Attention-Allocation Level and Its Application in Simulated SPO Task

Most human-caused flight accidents can be attributed to a pilot’s attention deficit and monitoring errors. Accordingly, pilots’ attention allocation is strongly related to their task performance. This study is aimed at analyzing pilots’ fixation characteristics and attention-allocation levels. First, we proposed a model for measuring attention-allocation level based on the salience, effort, expectancy, and value (SEEV) model. Second, a low-fidelity single-pilot operation (SPO) cockpit environment was constructed, and 20 pilots were recruited for an experiment to compare their fixation characteristics between SPO and double-pilot operation (DPO) scenarios. The results showed slight differences in the attention levels allocated by SPO and DPO pilots under a scenario of one-engine failure. It concluded that Human-centered flight deck design can enhance a pilot’s attention allocation level. These findings can be used to optimize future flight deck designing and flight training for improving pilot’s task performance.

Fault Tolerance Controller Design for the Safety Flight of the Quadcopter: Theory and Implementation

Fault Tolerance Controller Design for the Safety Flight of the Quadcopter: Theory and Implementation

Analysis of a turbofan engine using a parametric loop

PurposeIn this study, the performance analysis of the split flow turbofan engine with afterburners has been examined using the parametric cycle analysis method. The purpose of this study is to examine how engine performance is impacted by design parameters and flight ambient values and to develop a software in this context.Design/methodology/approachSoftware has been developed using the open-source PYTHON programming language to perform performance analysis. Mach number, compressor/fan pressure ratio, bypass ratio and density were used as parameters. The effects of these variables on engine performance parameters were investigated.FindingsParametric cycle analysis has been calculated for different flight conditions in the range of 0–2 M and 0–15,000 m altitude for turbofan engines. With this study, basic data were obtained to optimize according to targeted flight conditions.Practical implicationsAs a result of the performance analysis, the association between the flight conditions and design parameters of engine were determined. A software has been developed that can be used in the design of supersonic gas turbine engines for fast and easy simulation of the design parameters.Originality/valueThe variables used in the literature have been analyzed, and the results of the studies have been incorporated into the developed software, which can be used in innovative engine design. Software is capable to be developed further with the integration of new algorithms and models.

Mechanical strength of the aircraft control chains in certain unusual cases

The paper focuses on certain specific occurrences involving sports aircraft and their mechanical flight control chains. Usually the flight controls and their control chains are subject of thorough checking procedures, but frequently such details are not observed or are easily ignored during the maintenance and airframe checking processes. The authors aim to provide information enabling proper training of flight crews, technical, and design staff/ personnel, allowing the avoidance of severe occurrences/ events caused by failures of the mechanical control chains. The analysis focuses on lighter aircraft, such as sports aircraft, which have full mechanical control chains.

Contact heat transfer analysis in flighted rotary drums

Flights are used to improve the mixing of the material and the heat and mass transfer within rotary drums. They lift particles out of the bulk bed and throw them as curtains into the passing gas phase of the drum. This also affects the contact area and contact heat transfer between the rotating drum and the particles. In this study, the contact heat transfer is experimentally investigated in an indirectly heated rotary drum with flights. To determine the heat transfer coefficient, the drum is heated to 350 °C in batch mode with both ends of the rotary drum insulated to avoid axial gas flow. During heating, the temperature profiles of the gas, the particles and the flight and drum walls are measured. Based on the energy balances of the particles, the contact heat transfer coefficient is determined. Glass beads with particle diameters of 0.7 to 4 mm, expanded clay and steel beads (4 mm each) are used as test materials. Operational (rotational speed, filling degree) and flight design parameters (number of flights, flight length ratio) are varied. Models for calculating the contact heat transfer coefficient in flighted rotary drums cannot be found in the literature. In order to show the effect of installations, the measured values are compared with an existing contact heat transfer model for unflighted rotary kilns. This shows good qualitative agreement for most of the parameters investigated. However, most measured values exceed the model values, which indicates a positive effect of flights on the contact heat transfer.

Визначення програми керування кутом тангажа твердопаливного ракетно-го об’єкта

This paper analyzes the trends in the improvement of the performance characteristics of guided missiles with solid-propellant sustainer engines and identifies the features and requirements for flight trajectories, design parameters, and control programs. Within the framework of the optimal control theory, the comprehensive problem of simultaneous optimization of a missile’s design parameters and control systems is formulated. An approach to the formation of missile flight control programs in the form of polynomials is developed further, thus making it possible to reduce the optimal control theory problem to a simpler problem of nonlinear mathematical simulation. The proposed approach to control program development is used at the initial design stage to form a wide range of guided missile trajectories. Use is made of a methodology for the ballistic and aeroballistic flight range optimization of the design parameters and flight control programs of a canard missile. The missile flight range depends essentially on the values of the design and trajectory parameters and control programs chosen for optimization. Because of this, the optimization of the chosen parameters (maybe, other parameters too) in the solution of specific target problems seems to be the indispensable initial stage of missile design. For the considered missile trajectories with a vertical launch where the Mach number takes different values, optimal programs of pitch time variation that maximize the flight range are determined. The analysis of the optimization results for different trajectories shows that the optimal program in active flight with a vertical launch is the linear time dependence of the pitch angle. The application package developed allows one to determine flight control programs optimal in a given class of functions and advisable design parameters and basic performance characteristics of guided missiles for various aerodynamic designs and flight schemes as early as at the initial design stage to an accuracy required for design studies. This makes it possible to analyze design alternatives, thus improving the quality of solution of problems arising at the initial design stage and reducing the time and the cost of design work on new missiles.

Controller design for transition flight of rotor-driven VTOL fixed-wing UAV based on PID

The field of drones has received a lot of attention in recent years and is developing well. In the process of resource circulation in cities, UAVs play an increasingly important role, such as logistics, monitoring, emergency rescue, etc. However, traditional rotary-wing UAVs and fixed-wing UAVs can be limited in some conditions, such as load, cruising speed and take-off area. Based on the above reasons, this paper designs a rotor-driven VTOL fixed-wing UAV, which combines the vertical take-off and landing of rotor and the fast cruise of fixed-wing UAV and other characteristics. And based on this UAV, for the transition process from hovering state to cruising state, a PID controller is used to control the cruising speed, and then the flight altitude is controlled by a series-level PID controller. The final results show that the cruise speed can be stabilized at about 50km/h within 3 seconds by adjusting the PID parameters without considering the motor speed saturation. In addition, while ensuring the cruise speed reaches convergence quickly, the PID parameters of the acceleration loop, velocity loop and altitude loop can be adjusted separately to control the altitude error of the UAV within 5cm. This study provides a reference for researchers to study the control of rotor-driven UAVs in the transition process.

Novel UAV Flight Designs for Accuracy Optimization of Structure from Motion Data Products

Leveraging low-cost drone technology, specifically the DJI Mini 2, this study presents an innovative method for creating accurate, high-resolution digital surface models (DSMs) to enhance topographic mapping with off-the-shelf components. Our research, conducted near Jena, Germany, introduces two novel flight designs, the “spiral” and “loop” flight designs, devised to mitigate common challenges in structure from motion workflows, such as systematic doming and bowling effects. The analysis, based on height difference products with a lidar-based reference, and curvature estimates, revealed that “loop” and “spiral” flight patterns were successful in substantially reducing these systematic errors. It was observed that the novel flight designs resulted in DSMs with lower curvature values compared to the simple nadir or oblique flight patterns, indicating a significant reduction in distortions. The results imply that the adoption of novel flight designs can lead to substantial improvements in DSM quality, while facilitating shorter flight times and lower computational needs. This work underscores the potential of consumer-grade unoccupied aerial vehicle hardware for scientific applications, especially in remote sensing tasks.

MIT Zero-G outreach initiative: Using experiment design and virtual reality to inspire the next generation of space scientists and engineers

MIT's Space Exploration Initiative offers a course on project development, prototyping, and deployment readiness for parabolic flights, culminating in an annually chartered research flight with Zero-G. MIT's Resource Exploration and Science of our Cosmic Environment (RESOURCE) team participated in the course in the fall of 2021 with a Zero-G flight in May of 2022 testing technology for a virtual reality platform to enable science on Lunar rover exploration missions. In parallel with the scientific effort, the team developed the MIT Zero-G Outreach Initiative (0G-OI), an outreach program to engage with the Cambridge Public School's (CPS) grade 7 classes to teach them about research in microgravity, parabolic flight, and experiment design. The goal of the outreach program is to inspire the next generation of space scientists and engineers using virtual reality.The CPS grade 7 curriculum covers ‘Mysteries of the Universe’ where students consider the role of gravity in the solar system. They also complete a unit on roller coasters in which they learn about key ideas of force, motion, and energy through the context of roller coasters. The 0G-OI Initiative ties these two units together through five videos covering: 1) an overview of the initiative, 2) the basics of parabolic flight and how we perceive gravity, 3) an overview of gravity and its function in the universe, 4) why and what we can study in microgravity and 5) how to design an experiment for microgravity. The students then design their own experiments for microgravity. These are down-selected to the top 5 experiments that are reviewed by an astronaut to select one experiment to fly on the MIT chartered Zero-G parabolic flight. The flight and the experiment are filmed in VR video by the MIT RESOURCE team. Each participating school is provided with an Oculus Quest 2 VR headset and a flight day is held at each school where the students experience the Zero-G flight and see the results of their experiment in an immersive VR environment. Using this initial setup, the 0G-OI can be run annually in parallel with MIT's SEI parabolic flight course.Some key development parameters included keeping the educational videos under 10 min, that having an astronaut select the winning experiment provided incentive and finally, using VR, as this technology is commonly associated with gaming and entertainment. Lessons learned focused on improvements to scheduling and coordination with Zero-G, in-person programming and classroom experience optimization. The 0G-OI aims to develop a lasting relationship with the CPSs and make the exciting experience of parabolic flight and space exploration an accessible experience.

Assessing the bias and uncertainties in the aircraft mass balance technique for the determination of carbon dioxide emission rates

Urban areas are the major sources of greenhouse gas emissions but also leaders in emission reduction efforts. Appropriate techniques to quantify emissions and any potential reductions over time are necessary to effectively inform these mitigation efforts. The aircraft mass balance experiment (MBE) is an established technique used for such a purpose. In this work, we use a series of 55 MBEs downwind of power plants to assess the technique’s bias and precision. In addition, we investigate what factors drive the absolute error, determined as the absolute difference between observed and reported emission rates, in individual experiments using multilinear regressions. Power plants are required to monitor their carbon dioxide emissions with an hourly resolution, and these publicly available reported emissions can be directly compared to the mass balance estimates as a pseudo-known release. To quantify the bias we calculated the mean error, which was 10 ± 240 Mg·h−1 (1σ), regressed mass balance emission rates against reported emission rates to yield a slope of 0.967 ± 0.062, and compared the sum across all mass balance emission rates, 31,000 ± 1,000 Mg·h−1, to the sum across all reported emissions, 30,660 ± 740 Mg·h−1. All three of these approaches suggest no systematic bias. Then to quantify the precision for individual determinations we calculated the slope of a regression between the standard deviation across repeated MBEs and the corresponding average emission rate, which is 30.7% ± 6.7%. The main drivers of the absolute error were sparse sampling of the plume, poor horizontal and vertical mixing of the plume, and smaller signal-to-noise ratios. Quantifying the capabilities of this technique provides context for previous analyses and allows stakeholders and researchers to make informed decisions when choosing quantification methods. Identifying the factors that drive the absolute error also allows us to adjust flight design to minimize it and potentially improve uncertainty estimates.

Motion Control of a Multipurpose Laboratory Module with the Use of a Propulsion Unit

The motion control of the Nauka Multipurpose Laboratory Module (MLM) during its flight to the International Space Station (ISS) is considered. For maneuvering and angular stabilization, a propulsion system is used as an actuator. In order to ensure simultaneous control of the motion of the center of mass of the spacecraft (SC) and its stabilization with the help of engines at each moment of time, it is necessary to solve the problems of determining the required change in the speed of the SC, choosing the optimal configuration of the engines, and the problem of predicting the motion parameters of the SC. Methods for solving these problems, applied in the development of the control system of the Multipurpose Laboratory Module, are presented. The operability of the described algorithms is confirmed by the results of mathematical modeling on a ground test bench for onboard software and in the course of flight design tests directly during the flight and successful docking on the ISS.

Bayesian optimization for the spanwise oscillation of a gliding flat plate

Bayesian optimization is a powerful tool in the kinematic design of bio-inspired flight, where expensive high-fidelity numerical simulations are required. However, the traditional single acquisition strategy cannot adapt to all design problems, which have various input–output characteristics. The hybrid acquisition strategy improves the robustness by utilizing three types of acquisition functions, and each acquisition function is assigned three different balance parameters. The kinematics of a gliding flat plate that oscillates along the spanwise direction has been optimized to enhance the power efficiency by using the Bayesian optimization method. The power factor under the optimal spanwise oscillation is 1.97 times as large as that without spanwise oscillation, which indicates the good capability of the optimization method for bio-inspired locomotion.