Behavior Of Aircraft Research Articles

Aerodynamic Nonlinearity Effects on Flight Dynamics of a Very Flexible Flying Wing

High-aspect-ratio (AR) wings are the prominent feature of very flexible aircraft, and greater AR designs are being explored for enhanced flight efficiency in civil aviation. However, the impact of higher flexibility on the aeroelastic behavior of fixed-wing aircraft still needs to be fully understood. This paper assesses the effects of aerodynamic nonlinearities from flow separation on the maneuvering and gust response of a high-aspect-ratio flying wing using low-order models. Three aerodynamic formulations are evaluated: a linear model without stall effects, a piecewise linear model with steady-stall characteristics, and a nonlinear model accounting for dynamic-stall phenomena. All models perform similarly during maneuvering oscillations near stall conditions, but the dynamic-stall model foresees flight dynamic instabilities poststall, which are not seen in other models given the same maneuver input. Under a limited number of discrete and continuous gust disturbances, the model without stall effects behaves nonconservatively, whereas the steady-stall model is more conservative compared to the dynamic-stall model, with respect to the prediction of flight instabilities. These outcomes highlight the importance of accounting for aerodynamic nonlinearities in understanding the flight dynamics of very flexible aircraft under moderate-to-high angle-of-attack excitations.

Airspace Constrained Free-Flight Analysis: Implications for Uncrewed Air Traffic Management

This paper provides a study of free-flight air traffic behaviour in increasingly constrained airspace environments. Traffic assumes three different free-flight operational constructs with airspace constraints considered as restricted (no-fly) regions. Simulations combine path planning and Monte Carlo techniques to qualitatively analyse emergent traffic behaviour and quantitatively assess spatial–temporal airspace conflict as the airspace constraints vary. Findings indicate that airspace constraints have a much stronger influence on aircraft behaviour than the free-flight operational construct, with any benefits of free flight rapidly diminishing as the airspace becomes more constrained. We conclude that structured traffic route (or network) designs and associated risk modelling approaches should be considered for safe and efficient traffic management of highly constrained and congested (or dense) airspace. This work therefore provides evidence to inform new airspace design and management initiatives, including low-altitude uncrewed traffic.

Digital Twin Framework for Aircraft Lifecycle Management Based on Data-Driven Models

This paper presents a comprehensive framework for implementing digital twins in aircraft lifecycle management, with a focus on using data-driven models to enhance decision-making and operational efficiency. The proposed framework integrates cutting-edge technologies such as IoT sensors, big data analytics, machine learning, 6G communication, and cloud computing to create a robust digital twin ecosystem. This paper explores the key components of the framework, including lifecycle phases, new technologies, and models for digital twins. It discusses the challenges of creating accurate digital twins during aircraft operation and maintenance and proposes solutions using emerging technologies. The framework incorporates physics-based, data-driven, and hybrid models to simulate and predict aircraft behavior. Supporting components like data management, federated learning, and analytics tools enable seamless integration and operation. This paper also examines decision-making models, a knowledge-driven approach, limitations of current implementations, and future research directions. This holistic framework aims to transform fragmented aircraft data into comprehensive, real-time digital representations that can enhance safety, efficiency, and sustainability throughout the aircraft lifecycle.

Nonlinear Surrogate Model Design for Aerodynamic Dataset Generation Based on Artificial Neural Networks

In this work we construct a surrogate model using artificial neural networks (ANN) to predict the steady-state behavior of an unmanned combat aircraft. We employ various strategies to improve the model’s accuracy, including the consideration of design tolerances, creating independent surrogate models for the different flow regimes and encoding non-numeric input features. We also explore alternative machine learning models, albeit they demonstrated a lower reliability than ANNs. Two scenarios are considered for the target variable: one focusing solely on predicting the pitching moment coefficient, and the other incorporating the roll moment coefficient as well. We investigate different methods for handling multiple targets, finding that constructing a single model with multiple outputs consistently outperforms developing separate models for each target variable. Overall, the ANN provides predictions that show excellent agreement with the experimental data, demonstrating its effectiveness and reliability in aerodynamic modeling.

The dynamic behavior and nonlinear characteristics of aircraft landing gear retraction mechanism considering atmospheric corrosion

Atmospheric corrosion poses a significant challenge for the components of aircraft exposed to prolonged harsh weather conditions, critically impacting the safety property of aircraft landing gear retraction mechanism (ALGRM). This paper focuses on the ALGRM of a specific aircraft type, presenting a new modeling and analysis approach to assess the influence of atmospheric corrosion on dynamic behavior and nonlinear characteristics of mechanism. Initially, the dynamic model of ALGRM incorporating clearance joints is established using Lagrangian method. Numerical solutions are then obtained using the Runge-Kutta method. Subsequently, COMSOL simulation software is employed to simulate the corrosion morphology of the bearing under atmospheric corrosion, integrating the corroded bearing surfaces into the dynamic model of the mechanism. Finally, the study investigates the effects of corrosion time and different bearing materials on the dynamic behavior and nonlinear characteristics of ALGRM considering atmospheric corrosion. The results indicate that as corrosion time increases, the degradation of the dynamic behavior of ALGRM becomes more pronounced, and there are significant variations for corrosion morphology of bearing made of different materials under atmospheric corrosion. The findings of this study contribute to a broader understanding of the complex interactions between the dynamic behavior of aircraft and environmental degradation, providing some insights for designing ALGRM that are more durable and adaptable to atmospheric corrosion environments.

Интеллектуальная поддержка экипажа при выводе гражданского воздушного судна из сложного пространственного положения

<p>A new approach to development of the mathematical and software tools for synthesis of the control actions recovering an aircraft from a difficult spatial position is presented, using the sufficient accumulated empirical data. When calculating control actions, an aircraft behavior pattern, which is relevant to the flight situation arisen and containing information about piloting by a qualified crew, is in use. Synthesized actions can be employed within newly created autopilots when performing difficult flight modes or used to correct control influences performed by an average or low-skilled pilot in real time.</p>

A Python Toolbox for Data-Driven Aerodynamic Modeling Using Sparse Gaussian Processes

In aerodynamics, characterizing the aerodynamic behavior of aircraft typically requires a large number of observation data points. Real experiments can generate thousands of data points with suitable accuracy, but they are time-consuming and resource-intensive. Consequently, conducting real experiments at new input configurations might be impractical. To address this challenge, data-driven surrogate models have emerged as a cost-effective and time-efficient alternative. They provide simplified mathematical representations that approximate the output of interest. Models based on Gaussian Processes (GPs) have gained popularity in aerodynamics due to their ability to provide accurate predictions and quantify uncertainty while maintaining tractable execution times. To handle large datasets, sparse approximations of GPs have been further investigated to reduce the computational complexity of exact inference. In this paper, we revisit and adapt two classic sparse methods for GPs to address the specific requirements frequently encountered in aerodynamic applications. We compare different strategies for choosing the inducing inputs, which significantly impact the complexity reduction. We formally integrate our implementations into the open-source Python toolbox SMT, enabling the use of sparse methods across the GP regression pipeline. We demonstrate the performance of our Sparse GP (SGP) developments in a comprehensive 1D analytic example as well as in a real wind tunnel application with thousands of training data points.

Platform and simulator with three degrees of freedom for testing quadcopters

This study aims to design a test platform for quadcopters, which allows the execution of all rotational movements and prevents translational movements without affecting the dynamics of the system. The methodological approach involves both simulation and the construction of the test platform. Two simulators are developed: (i) a linear simulator, used to assist in determining control parameters, and (ii) a nonlinear simulator, used to model the nonlinearity inherent to the rotational behavior of aircraft. In addition, the control system for the quadcopter is implemented, utilizing proportional, integral, and derivative control principles. By conducting seven experiments on the test platform and in the nonlinear simulator, the obtained results are compared in order to validate the proposed methodology. The mean discrepancy observed between the mean absolute difference obtained by the test platform and by the nonlinear simulator for the angle ϕ was 0.85°, for the angle θ was 2.77°, and for the angle ψ was 4.66°. When analyzed separately, the mean absolute errors for the angles, using the nonlinear simulator and the test platform, showed differences below 2% in almost all evaluated experiments. The developed test platform preserves the rotational dynamics of the quadcopter as desired, closely approaching the results obtained by the nonlinear simulator. Consequently, this platform can be used to carry out practical tests in a controlled environment.

Improved self-adaptive turbulence eddy simulation for complex flows and stall prediction using high-order schemes

It is challenging to apply numerical simulations to accurately predict the stall behavior of aircraft equipped with high-lift devices. Simulations with Reynolds-Averaged NavierStokes (RANS) models suffer from lack of the reliability at high angles of attack with separated and reattached boundary layers, whereas wall-resolved Large Eddy Simulations (LES) of wall-bounded flows at high Reynolds numbers currently costs too much computational resources. A new unified hybrid turbulence modeling approach, denoted the Self-Adaptive Turbulence Eddy Simulation (SATES), is proposed and applied for complex turbulent flows combining with high-order numerical scheme of the Weighted Compact Nonlinear Scheme (WCNS) in the present study. It enables a seamless evolution from unsteady RANS to LES and finally approaches Direct Numerical Simulation (DNS) depending on the turbulent scales. In the framework of SATES, a new SATES-σ model with an adaptive model coefficient is developed by extending the underlying LES mode based on an enhanced sub-grid-scale model of the σ-model. The new SATES-σ is first examined in two benchmark cases of channel flow and flow past a square cylinder. Then, it is validated in supercritical flow past a circular cylinder to assess the performance of turbulent models. The results show significant improvements over the previous SATES and IDDES in the predictions of boundary layer flow. Finally, successful application is achieved in the accurate prediction of the stall of the MD-30P30N airfoil at a Reynolds number of 9×106 with wide angles of attack. The simulation results show good agreement with experimental results for surface pressure even for the challenging cases of 21 and 23 deg angles of attack. Again, the SATES-σ shows better results than the previous SATES and IDDES. The presented method has considerable potential for the challenging stall predictions.

Liquid Hydrogen Storage Tank Virtual Crashworthiness Design Exploration for Civil Aircraft

Civil aviation industry is researching for alternative fuel energy sources to substitute current hydrocarbon-based aviation fuels. Carbon free emissions flights could be achieved with fuels like Hydrogen either through combustion or via electricity producing fuel cells. It is of great importance to explore the airframe designs to house Hydrogen in its cryogenic liquified state. The objective of the study herein was to provide a conceptual qualitative analysis related to the crashworthiness behaviour of civil aircraft carrying liquid Hydrogen fuel storage tanks. The design parameters of interest were the storage tank location in the airframe, the structural energy absorption following crash landing scenarios and the structural deformation of the structure surrounding the tanks, penetrating the survival space of the occupants. Several structural design arrangements were proposed and compared. Simulation results indicated that the optimal location for the fuel storage greatly depends on the actual aircraft layout as well as on the future civil aircraft airworthiness requirements that are still under development for that type of fuel energy source.

Aircraft Behavior Recognition on Trajectory Data with a Multimodal Approach

Moving traces are essential data for target detection and associated behavior recognition. Previous studies have used time–location sequences, route maps, or tracking videos to establish mathematical recognition models for behavior recognition. The multimodal approach has seldom been considered because of the limited modality of sensing data. With the rapid development of natural language processing and computer vision, the multimodal model has become a possible choice to process multisource data. In this study, we have proposed a mathematical model for aircraft behavior recognition with joint data manners. The feature abstraction, cross-modal fusion, and classification layers are included in the proposed model for obtaining multiscale features and analyzing multimanner information. Attention has been placed on providing self- and cross-relation assessments on the spatiotemporal and geographic data related to a moving object. We have adopted both a feedforward network and a softmax function to form the classifier. Moreover, we have enabled a modality-increasing phase, combining longitude and latitude sequences with related geographic maps to avoid monotonous data. We have collected an aircraft trajectory dataset of longitude and latitude sequences for experimental validation. We have demonstrated the excellent behavior recognition performance of the proposed model joint with the modality-increasing phase. As a result, our proposed methodology reached the highest accuracy of 95.8% among all the adopted methods, demonstrating the effectiveness and feasibility of trajectory-based behavior recognition.

Comprehensive Analysis of Aircraft Dynamics Stability with SCSim: Integration and Assessment

This research presents a comprehensive analysis of the dynamic stability of aircraft using modules of the software named SCSim (Stability and Control Simulation Tool), which is dedicated to the analysis of aircraft stability and control. The stability of an aircraft can be examined in two directions: longitudinal and lateral. The ability to determine an aircraft's limits and handling qualities depends on its stability. This study report demonstrates a complete dynamic stability analysis using SCSim with aerodynamic input data from the commercial software Advanced Aircraft Analysis (AAA). SCSim is implemented within a common framework in MATLAB, adapted from a MATHCAD script, providing an easier way to enter user-defined input data, and introducing a set of new features. The study is divided into three main parts, each based on an analysis of stability. First, static stability is examined to understand how the system behaves when it is in equilibrium. Then, dynamic stability is assessed to understand how the system reacts to perturbations and disturbances. Finally, handling qualities systematically assess the dynamic modes of the aircraft's behavior and establish the levels of handling qualities. In this paper, a generic model of a propeller-driven aircraft is used for the study due to the availability of flight parameters, geometric, and aerodynamic data. The obtained results demonstrate the capabilities of the Stability and Control Simulation Tool (SCSim) in designing and analysing an aircraft's stability under various flight conditions and configurations, with validation using AAA.

Numerical study of the tire hydroplaning behavior of aircraft on grooved concrete pavement.

Safe operation is crucial for civil aviation, and reducing the risk of aircraft tire hydroplaning is essential for civil aviation safety. Here, a new 3D aircraft tire-grooved (smooth) wet pavement model based on the coupled Eulerian-Lagrangian (CEL) algorithm for the A320 aircraft was developed, and the effect of the ground contact area of an aircraft tire on the hydrodynamic pressure and support force of the tire under smooth and grooved wet pavement conditions was investigated. The results indicate that at the same taxiing speed, the ground contact area of the aircraft tire under the grooved wet-pavement condition is reduced by 19.8% compared to the smoothed wet-pavement condition, which is reduced by 6.2%. Similar patterns are observed for the hydrodynamic pressure and the critical hydrodynamic speed during landing and taking-off procedures, with upper and lower limited values obtained through the simulation results. Additionally, the predicted correction factor of the hydroplaning speed at different water film thicknesses is compared with those values obtained via the NASA formula. A comparison shows that the NASA formula underestimates the critical hydroplaning speed during the landing procedure. The corresponding correction factor will be less than 1.0 when the water film thickness reaches a critical value of 7.66 mm.

An improved composite impact damage model and bird-striking damage analysis with smoothed particle hydrodynamics-finite element method

An improved impact damage model is proposed, which can be used to analyze the progressive failure behavior of fiber-reinforced composites. The model is constructed based on the 3D Hashin failure criterion. However, the difference is that the strain component along the thickness direction in the matrix energy evolution model is introduced, and the effects of and on impact damage are added. Rigid-body and bird-body impact problems are studied, which validates the accuracy of the numerical model by comparison with experiments. A 3D numerical model of light aircraft fuel tank impact is constructed, and the SPH-FEM coupling method is used to predict the bird strike failure problem. The structural damage and impact behavior of a light aircraft fuel tank under impact loading are analyzed. The results show that, under different impact energies, the damage to the matrix is more serious and expands along the fiber direction, and the structure presents different damage forms. This paper provides an effective research model for the study of drop shock and the airworthiness of composite fuel tanks.

Data-Driven Model to Predict Aircraft Vibration Environment

Vibration levels that onboard equipment must be able to withstand throughout their lives for correct operation are mainly determined experimentally because predicting the dynamic behavior of a complete aircraft requires computational means and methods that are currently difficult to implement. We present a data-driven methodology that leverages flight-test accelerometer data to produce a predictive model. This model, based on an ensemble of artificial neural networks, performs a multioutput multivariate regression to estimate vibration spectra from a set of aircraft general parameters without having to characterize excitation sources. The model is compared with baseline models over two protocols, which are 1) standard training and testing as well as 2) extrapolation to high dynamic pressures, in order to assess physical consistency. Although the first protocol shows that all models can produce results accurate enough for this context, the second protocol shows that only the ensemble model is able to correctly extrapolate the energy. Using the Shapley additive explanations method, also known as SHAP, we show that these results can be explained by the ability of our model to identify the dynamic pressure as the core feature used in the extrapolation protocol. The proposed model can be used in multiple applications, such as anomaly detection and vibration flight envelope opening.

Machine Learning Supporting Enhanced Optimized Spacing Delivery between Consecutive Departing Aircraft

The Optimised Spacing Delivery (further referred to as OSD) tool has the objective of calculating the necessary time spacing between two consecutive departing aircraft in order to fulfil all required spacing and separation constraints. OSD, developed in SESAR 2020 Wave 1 [1] is based on analytical models [2] to predict aircraft trajectory and speed profiles. The use of this tool by Air Traffic Controller supports the safe, consistent and efficient delivery of the required separation or spacing between consecutive departure pairs by providing the time required between departure aircraft pairs via an automated count-down timer to the tower runway controller. In order to improve OSD, this paper introduces the enhanced Optimised Spacing Delivery (further referred to as eOSD) tool which builds on the OSD tool using Machine Learning techniques to make more accurate predictions of aircraft behaviour (e.g. trajectory/climb profile, speed profile) and wind on the initial departure path, so further optimising spacing delivery between consecutive departures. Zurich airport data were used to develop and asses the performance of the eOSD tool compared to the OSD tool.

A Case Study of a Methodological Approach to the Verification of UAV Propeller Performance

Understanding the behaviour of propeller-driven aircraft has been the primary goal of aviation since the brothers Orville and Wilbur Wright. Traction characteristics, which have over time become dominant in the field of aviation in addition to thrust, both examined and analysed, nevertheless represent a sort of oxymoron in modern aviation. In this sense, the authors of the paper present the possibilities of static performance characteristics and vibrations of aircraft propellers through the analysis of low-powered aircraft. The use of low-powered aircraft as “expendable” material is the reality we live in, but ensuring the safety of their use is the primary goal of the researchers who deal with this issue. Accordingly, the authors of this paper present indications of the methodology of testing the blades of low-power aircraft in the atmosphere with an observation that the same indications can be used with aircraft of higher power, as well as with the aircraft on celestial bodies that have not been tested or available. A test bench for the quantification of thrust, torque, and vibration of small unmanned aerial vehicles’ (UAV) vehicle propellers is presented. The obtained results realistically describe the complex behaviour of propellers in operation.

Behaviour of unmanned aircraft in formation

Behaviour of unmanned aircraft in formation

Contributions to data transmission at critical moments on unmanned aerial vehicles

As for unmanned aircraft, the knowledge of the aircraft performance is directly related with the navigation, guidance, and control system programming. Therefore, the measured data in each phase of the flight must be sufficiently precise to obtain a good characterization of aircraft. This article proposes new methods of sending information to ground, which make it possible to know the aircraft behavior accurately, and for this purpose, four contributions have been made for ALO (Avión Ligero de Observación, Spanish acronym for Light Observation Aircraft). Currently, the characterization is based on data obtained at ten samples per second, insufficient to acquire detailed knowledge of what happened during the whole flight of an aircraft. As a result of these contributions, many more samples per second of accelerations and angular velocities are obtained at the most critical moments of the flight, such as takeoff or landing. Among the improvements included are data compression techniques, providing references to locate the measured data in time and identifying labels of each parameter.

Gust response analysis based on a nonlinear structural model and the unsteady aerodynamics of a flexible aircraft

Purpose This study aims to simulate gust effects on the aeroelastic behavior of a flexible aircraft. The dynamic response of the system for different discreet gust excitations is obtained using numerical simulations. Design/methodology/approach Coupled dynamics, including rigid and flexible body coordinates, are considered for modeling the dynamic behavior of the aircraft. Wing is considered flexible and other parts are considered rigid. Wing is modeled with nonlinear Euler Bernoulli beam. Moreover, unsteady aerodynamics based on the Wagner function are used for aerodynamic loading, and the results are compared with those of quasi-steady aerodynamics. Findings Von Kármán continuous gust is applied to this aircraft. In addition, the discrete “1- cosine” gust with different gust lengths is applied to the aircraft, and the maximum and minimum accelerations are computed. It is shown that the nonlinear modeling of the system represents the actual behavior and causes limit cycle oscillation phenomena. Originality/value This methodology can yield a relatively simple dynamic model for high aspect ratio aircrafts to provide insights into the vehicles’ dynamics, which can be available early in the design cycle.