Unsteady Aerodynamic Model Research Articles

Unsteady aerodynamic reduced-order modeling based on machine learning across multiple airfoils

Computational-fluid-dynamics-based prediction of unsteady aerodynamics is an essential research topic in the design of aircraft, which usually requires very high computational cost. Therefore, developing efficient and accurate reduced-order models (ROMs) for unsteady aerodynamics is important. With recent progress in modeling unsteady aerodynamics for a fixed configuration, there is a need of developing reduced-order models across multiple geometrical shapes. In this work, the long short-term memory (LSTM) network, a traditional model in machine learning for modeling time-dependent dynamics, is utilized to construct the unsteady aerodynamic reduced-order model, which takes into account the variation of airfoil geometry. The proposed approach is illustrated by some NACA 6-series airfoils under pitching and plunging motions in the transonic flow, where the geometrical parametrization is based on the maximum camber and thickness. Results show that the model can accurately capture the unsteady aerodynamics for varying shape parameters. Finally, as a proof of concept, the constructed ROM is applied to uncertainty and sensitivity analysis with respect to the variation of geometry parameters.

Verification of a Body Freedom Flutter Numerical Simulation Method Based on Main Influence Parameters

The body freedom flutter characteristics of an airfoil and a fly wing aircraft model were calculated based on a CFD method for the Navier–Stokes equations. Firstly, a rigid elastic coupling dynamic model of a two-dimensional airfoil with a free–free boundary condition was derived in an inertial frame and decoupled by rigid body mode and elastic mode. In the fluid–solid coupling method, the rigid body was trimmed by subtracting the generalized steady aerodynamic force from the structural dynamic equation. The flutter characteristics were predicted by the variable stiffness method at a fixed Mach number and flight altitude. Finally, validation of the predicted body freedom flutter characteristics was performed through a comparison of theoretical solutions based on a Theodorsen unsteady aerodynamic model for airfoil and experimental results for a fly wing aircraft model. The mechanism of the influence of the bending mode stiffness and the position of the center of gravity on the body freedom flutter characteristics were briefly analyzed.

Parametric whirl flutter study using different modelling approaches

This paper demonstrates the importance of assessing the whirl flutter stability of propeller configurations with a detailed aeroelastic model instead of local pylon models. Especially with the growing use of electric motors for propulsion in air taxis and commuter aircraft whirl flutter becomes an important mode of instability. These configurations often include propeller which are powered by lightweight electric motors and located at remote locations, e.g. the wing tip. This gives rise to an aeroelastic instability called whirl flutter, involving the gyroscopic whirl modes of the engine. The driving parameters for this instability are the dynamics of the mounting structure. Using a generic whirl flutter model of a propeller at the tip of a lifting surface, parameter studies on the flutter stability are carried out. The aeroelastic model consists of a dynamic MSC.Nastran beam model coupled with the unsteady ZAERO ZONA6 aerodynamic model and strip theory for the propeller aerodynamics. The parameter studies focus on the influence of different substructures (ranging from local engine mount stiffness to global aircraft dynamics) on the aeroelastic stability of the propeller. The results show a strong influence of the level of detail of the aeroelastic model on the flutter behaviour. The coupling with the lifting surface is of major importance, as it can stabilise the whirl flutter mode. Including wing unsteady aerodynamics into the analysis can also change the whirl flutter behaviour. This stresses the importance of including whirl flutter in the aeroelastic stability analysis on aircraft level.

Combined selection of the dynamic model and modeling error in nonlinear aeroelastic systems using Bayesian Inference

We report a Bayesian framework for concurrent selection of physics-based models and (modeling) error models. We investigate the use of colored noise to capture the mismatch between the predictions of calibrated models and observational data that cannot be explained by measurement error alone within the context of Bayesian estimation for stochastic ordinary differential equations. Proposed models are characterized by the average data-fit, a measure of how well a model fits the measurements, and the model complexity measured using the Kullback–Leibler divergence. The use of a more complex error models increases the average data-fit but also increases the complexity of the combined model, possibly over-fitting the data. Bayesian model selection is used to find the optimal physical model as well as the optimal error model. The optimal model is defined using the evidence, where the average data-fit is balanced by the complexity of the model. The effect of colored noise process is illustrated using a nonlinear aeroelastic oscillator representing a rigid NACA0012 airfoil undergoing limit cycle oscillations due to complex fluid–structure interactions. Several quasi-steady and unsteady aerodynamic models are proposed with colored noise or white noise for the model error. The use of colored noise improves the predictive capabilities of simpler models.

Nonlinear Unsteady Aerodynamics Reduced Order Model of Airfoils Based on Algorithm Fusion and Multifidelity Framework

A reduced order modeling method based on algorithm fusion and multifidelity framework for nonlinear unsteady aerodynamics is proposed to obtain a low-cost and high-precision unsteady aerodynamic model. This method integrates the traditional algorithm, intelligent algorithm, and multifidelity data fusion algorithm. In this method, the traditional algorithm is based on separated flow theory, the intelligent algorithm refers to the nonlinear autoregressive (NARX) method, and the multifidelity data fusion algorithm uses different fidelity data for aerodynamic modeling, which can shorten the time cost of data acquisition. In the process of modeling, firstly, a multifidelity model with NARX description provides a general intelligent algorithm framework for unsteady aerodynamics. Then, based on the separated flow theory, the correction equation from low-fidelity model to high-fidelity result is constructed, and the cuckoo algorithm based on chaos optimization is used to identify the parameters. In order to verify the effectiveness of the method, an unsteady aerodynamic model of NACA0012 airfoil is established. Three kinds of data with low, medium, and high fidelity are used for modeling. The low-fidelity and medium-fidelity data is obtained from the CFD-Euler solver and CFD-RANS solver, respectively, while the high-fidelity data comes from the experimental results. Then, the model is established, and its prediction of unsteady aerodynamic coefficients is in good agreement with the CFD results and the experimental data. After that, the model is applied to a two-dimensional aeroelastic system, and the bifurcation and limit cycle response analysis are compared with the experimental results, which further shows that the model can accurately capture the main flow characteristics in the flow range of low speed and high angle of attack. In addition, the convergence of the model is studied; the accuracy and generalization ability as well as applicability scope of the model are compared with other aerodynamic models and finally discussed.

Assessment of flight dynamic and static aeroelastic behaviors for jet transport aircraft subjected to instantaneous high g-loads

PurposeThe purpose of this paper is to present a quick inspection method based on the post-flight data to examine static aeroelastic behavior for transport aircraft subjected to instantaneous high g-loads.Design/methodology/approachIn the present study, the numerical approach of static aeroelasticity and two verified cases will be presented. The non-linear unsteady aerodynamic models are established through flight data mining and the fuzzy-logic modeling of artificial intelligence techniques based on post-flight data. The first and second derivatives of flight dynamic and static aeroelastic behaviors, respectively, are then estimated by using these aerodynamic models.FindingsThe flight dynamic and static aeroelastic behaviors with instantaneous high g-load for the two transports will be analyzed and make a comparison study. The circumstance of turbulence encounter of the new twin-jet is much serious than that of four-jet transport aircraft, but the characteristic of stability and controllability for the new twin-jet is better than those of the four-jet transport aircraft; the new twin-jet transport is also shown to have very small aeroelastic effects. The static aeroelastic behaviors for the two different types can be assessed by using this method.Practical implicationsAs the present study uses the flight data stored in a quick access recorder, an intrusive structural inspection of the post-flight can be avoided. A tentative conclusion is to prove that this method can be adapted to examine the static aeroelastic effects for transport aircraft of different weights, different sizes and different service years in tracking static aeroelastic behavior of existing different types of aircraft. In future research, one can consider to have more issues of other types of aircraft with high composite structure weight.Originality/valueThis method can be used to assist airlines to monitor the variations of flight dynamic and static aeroelastic behaviors as a complementary tool for management to improve aviation safety, operation and operational efficiency.

Hybrid Learning Approach to Sensor Fault Detection with Flight Test Data

Data-driven algorithms are developed to fully automate sensor fault detection in systems governed by underlying physics, with a particular focus on the flight test setting. The proposed machine learning method uses a time series of typical behavior to approximate the evolution of measurements of interest by a linear time-invariant system. Given additional data from related sensors, a Kalman observer is used to maintain a separate real-time estimate of the measurement of interest. Sustained deviation between the measurements and the estimate is used to detect anomalous behavior. A decision tree, informed by integrating other sensor measurement values, is used to determine the amount of deviation required to identify a sensor fault. The method is validated by applying it to three test systems exhibiting various types of sensor faults: commercial flight test data, an unsteady aerodynamics model with dynamic stall, and a model for longitudinal flight dynamics forced by atmospheric turbulence. In the latter two cases, fault detection was tested for several prototypical failure modes. The combination of a learned dynamic model with the automated decision tree accurately detects sensor faults in each case.

Longitudinal aerodynamic modeling and verification for air-launch-to-orbit system during stage separation

The stage separation is one of key issues for air-launch-to-orbit system. In this process, the elastic deformation of carrier causes periodic pulsation in interference aerodynamics and may lead to modal coupling and dynamics instability of spacecraft. The dynamic responses and stability of the two vehicles should be considered carefully. The CFD-based dynamic simulation method has high accuracy but requires large computation cost. In this study, a new reduced-order modeling method is developed, which is for unsteady aerodynamics of the air-launch-to-orbit system with considering the elastic deformations of carrier. Based on the physical mechanism of interference aerodynamics factors, the model input parameters are decoupled and the modeling difficulty is reduced. By coupling the unsteady aerodynamic model, structural dynamics equations and rigid body dynamic equations, the longitudinal dynamic responses of air-launch-to-orbit system during stage separation are simulated. Through comparison, those results have good agreement with traditional CFD-based method, and the simulation efficiency of new method is improved greatly. The new modeling method is applicable to the air-launch-to-orbit system and can provide guidance for similar engineering issues.

Aerodynamic surrogate model based on deep long short-term memory network: An application on high-lift device control

An unsteady aerodynamic surrogate model based on the deep LSTM (long short-term memory) network is proposed for predicting unsteady aerodynamic coefficients. Deflection angles and deflection velocities of control surfaces are introduced to input values of the surrogate model to enhance the capability of identifying different motion states so that accumulative error can be controlled. Longitudinal stability is extremely important for flight safety while few studies have worked on unsteady aerodynamics of airfoils/wings with moving high-lift device (HLD) motion. Longitudinal static margin sequence of the HLD extending process is studied, and nonlinearity and hysteresis of coefficients in HLD motion are validated. The surrogate model is then applied in HLD motion control with the particle swarm optimization (PSO) method. Additionally, the results are then performed in three-dimensional aircraft HLD control. Validation computations show that longitudinal stability of optimized configuration is promoted with lift coefficient unchanged.

Unsteady aero-elastic analysis of a composite wing containing an edge crack

This paper deals with the investigation of the influence of edge surface crack on the flutter behavior of unidirectional fiber-reinforced composite wing subjected to unsteady aerodynamic loads. The cracked wing is modeled as a two-interconnected Euler–Bernoulli beam at the crack location, where the related crack is modeled using continuity conditions and the local flexibility matrix concept. The components of this matrix are extracted from the theory of linear fracture mechanics. The formulation takes into account the effects of bending-torsion coupling due to the unbalanced laminates and offset of the center of gravity inherent to composite structures. The fundamental modes of intact and cracked cantilevered beams, derived from the free vibration analysis by the dynamic stiffness matrix, are used in Galerkin's method. The modified shape functions are developed to reflect the crack effect in the aeroelastic analysis, wherein an unsteady aerodynamic model based on strip theory is employed. By a combination of structure and aerodynamic formulations and using the modified mode shapes and applying a new iteration algorithm, the flutter boundary is determined. Also, the procedure has been evaluated by solving the number of problems available in the literature. Then effects of various parameters, such as the fiber angle, the crack location, the crack length, and the aerodynamic model, on the flutter boundary are analyzed and a detailed discussion will be addressed. It was found that these parameters can have a positive or negative influence on the flutter behavior of the structure.

Dynamic Response of Offshore Wind Turbine on 3×3 Barge Array Floating Platform under Extreme Sea Conditions

Offshore wind farm construction is nowadays state of the art in the wind power generation technology. However, deep water areas with huge amount of wind energy require innovative floating platforms to arrange and install wind turbines in order to harness wind energy and generate electricity. The conventional floating offshore wind turbine system is typically in the state of force imbalance due to the unique sway characteristics caused by the unfixed foundation and the high center of gravity of the platform. Therefore, a floating wind farm for 3×3 barge array platforms with shared mooring system is presented here to increase stability for floating platform. The NREL 5 MW wind turbine and ITI Energy barge reference model is taken as a basis for this work. Furthermore, the unsteady aerodynamic load solution model of the floating wind turbine is established considering the tip loss, hub loss and dynamic stall correction based on the blade element momentum (BEM) theory. The second development of AQWA is realized by FORTRAN programming language, and aerodynamic — hydrodynamic — Mooring coupled dynamics model is established to realize the algorithm solution of the model. Finally, the 6 degrees of freedom (DOF) dynamic response of single barge platform and barge array under extreme sea condition considering the coupling effect of wind and wave were observed and investigated in detail. The research results validate the feasibility of establishing barge array floating wind farm, and provide theoretical basis for further research on new floating wind farm.

Flutter Optimization of a Wing–Engine System with Passive and Active Control Approaches

In the present study, the flutter performance of a composite thin-walled beam wing–engine system is optimized by implementing two different control approaches: 1) passive open-loop and 2) active closed-loop control. Sequential quadratic programming and genetic algorithm methods are applied in the optimization process. In the passive control method, variable stiffness is acquired by constructing laminates of thin-walled beam with curvilinear fibers having prescribed paths. The goal is to exploit the desirable fiber paths with improved flutter performance to determine an optimized wing–engine aeroelastic configuration. In the active control strategy, piezo-composite actuators and the linear quadratic Gaussian algorithm are used to improve the flutter characteristics. A novel optimization strategy based on the total energy of the aeroelastic system is introduced and applied in both passive and active control strategies. The minimum total aeroelastic energy is an indication of ideal optimization variables, which leads to optimum flutter performance. The governing equations are formulated based on Librescu’s thin-walled beam theory and Hamilton’s principle. An unsteady aerodynamic model based on incompressible indicial aerodynamics is applied. The governing equations of motion are solved using a Ritz-based solution methodology. Numerical results demonstrate a 16 and 46% improvement in the flutter speed of the wing–engine system using the proposed passive and active control approaches, respectively. The presented results provide valuable information concerning the design of advanced lightweight and high-aspect-ratio aircraft wings with mounted engines in terms of favorable aeroelastic performance characteristics.

Study on the Intelligent Modeling of the Blade Aerodynamic Force in Compressors Based on Machine Learning

In order to obtain the aerodynamic loads of the vibrating blades efficiently, the eXterme Gradient Boosting (XGBoost) algorithm in machine learning was adopted to establish a three-dimensional unsteady aerodynamic force reduction model. First, the database for the unsteady aerodynamic response during the blade vibration was acquired through the numerical simulation of flow field. Then the obtained data set was trained by the XGBoost algorithm to set up the intelligent model of unsteady aerodynamic force for the three-dimensional blade. Afterwards, the aerodynamic load could be gained at any spatial location during blade vibration. To evaluate and verify the reliability of the intelligent model for the blade aerodynamic load, the prediction results of the machine learning model were compared with the results of Computation Fluid Dynamics (CFD). The determination coefficient R2 and the Root Mean Square Error (RMSE) were introduced as the model evaluation indicators. The results show that the prediction results based on the machine learning model are in good agreement with the CFD results, and the calculation efficiency is significantly improved. The results also indicate that the aerodynamic intelligent model based on the machine learning method is worthy of further study in evaluating the blade vibration stability.

Aeroelastic model and analysis of an active camber morphing wing

Morphing aircraft structures usually introduce greater compliance into aerodynamic sections, and therefore will affect the aeroelasticity with the potential risk of increased flutter. A low-fidelity model of an active camber morphing wing and its aeroelastic model are developed in order to investigate the potential critical speed by exploiting its chord-wise dimension and flexibility. Such a model may be used for conceptual design, where low fidelity models are used to explore and optimise a wide range of configurations. The morphing camber concept is implemented using a continuous representation of a two-segment structure with a rigid segment and a deformable part. The aeroelastic model is developed based on both steady and unsteady aerodynamic models, so that different parameters can be easily modified to examine changes in the flutter solutions. Of particular interest are the ratio of the morphing segment length to the chord, and its relative stiffness, as such morphing camber is potential operated using the deformable part as a flap. By comparing the results of the quasi-steady and unsteady aerodynamic models, it is shown that the quasi-steady aerodynamic model gives a more conservative prediction of the flutter speed. In addition, responses in phase space are simulated to show the fundamental aeroelastic behaviour of the morphing camber wing. It is also shown that the active compliant segment can be used to stabilise the morphing aircraft by using feedback control. This paper provides a system-level insight through mathematical modelling, parameter analysis and feedback control into dynamics applications of morphing camber.

Nonlinear aeroservoelasticity of aircraft

Advanced flight vehicles have been requiring lightweight structures and the expansion of bandwidth and authority of control systems. Hence, the coupled dynamics of the unsteady aerodynamics, the flexible aircraft structure, and the active control system has been an important research field in dynamics and control. The community of aeronautical technology has paid much attention to the aeroelastic stability and active control of aircraft since 1980s, but made less efforts to study the effects of the aerodynamic and structural nonlinearities, as well as time delays in a control loop, on the aeroservoelastic behaviors of aricraft. The studies of these effects need to model the high-dimensional and parametric-varying dynamic systems with strong aerodynamic/structural nonlinearity, and hence, face with the coupling among unsteady aerodynamics, aircraft structure, and active control system. The cutting-edge problems include how to develop nonlinear aeroservoelastic modeling theory, to reveal the dynamic mechanism behind the induced aeroelastic vibrations and to carry out wind tunnel tests for aeroservoelasticity. This review article surveys the recent advances in reduced modeling of unsteady aerodynamics, nonlinear structural dynamics, design of aeroservoelastic control law, and expremental studies on aeroservoelastic systems, with an emphasis on the researches of the authors’ team in nonlinear aeroservoelasticity. The article also makes a number of suggestions for studies in future.

Multi-disciplinary optimization of variable rotor speed and active blade twist rotorcraft: Trade-off between noise and emissions

The concepts of variable rotor speed and active blade twist are emerging technologies for the next generation of civil rotorcraft. Previous research has focused on the optimum implementation of these technologies for improved fuel economy and environmental impact. Within this work, an integrated approach is deployed to quantify the concurrent reductions in rotor noise and NOx emissions. A relaxation-based free-wake inflow model, coupled with unsteady blade aerodynamics modeling, resolves the flow-field around the main rotor. Aero-acoustic predictions are performed through an acoustic-analogy-based formulation. Gaseous emissions are then predicted via stirred-reactor modeling, coupled with zero-dimensional engine performance analysis method. This strategy is incorporated into a multi-disciplinary genetic algorithm optimization process based on surrogate modeling. Optimal schedules of combined variable rotor speed and active blade twist controls are derived for a twin-engine light helicopter in descent. The accrued schedules suggest NOx reductions between 6% and 21%, simultaneously with source-noise reductions of the order of 2–8 dB, relative to the non-morphing rotor case. The developed strategy constitutes an enabling methodology for the holistic and multi-disciplinary assessment of morphing helicopter rotor configurations.

Nonlinear aeroservoelastic analysis of a supersonic aircraft with control fin free-play by component mode synthesis technique

To investigate the nonlinear aeroservoelastic behaviors of a three-dimensional supersonic aircraft with control fin free-play, a modeling method based on the component-mode synthesis technique is utilized. The most distinctive feature of this method is that the structural nonlinearity can be expressed explicitly in the reduced-order aeroservoelastic model. The unsteady aerodynamic model with discrete gust loads is formulated using the supersonic lifting surface theory and the minimum state approximation. The results validate the feasibility of the reduced-order aeroelastic model for gust response analysis. A hybrid adaptive feedback control algorithm is proposed for the gust load alleviation by integrating the positive position feedback (PPF) and the filtered-x least-mean-square (FxLMS) algorithm. The comparative study demonstrates that the designed PPF-FxLMS algorithm has a better control performance for the alleviation of the pitch attitude angle induced by the gust loads, and it remains effective in the post-flutter regime. Moreover, the effects of free-play nonlinearity on the dynamic behaviors of the aeroservoelastic system are also studied, and numerical results show that the presence of free-play can lead to a larger peak value of gust response. The nonlinear vibration of the control fin induces the aircraft pitch attitude to produce stable limit cycle oscillations with high frequency, and variation in the free-play magnitude significantly influences the gust responses of the nonlinear aeroservoelastic system.

Classical and Fuzzy Sliding Mode Control for a Nonlinear Aeroelastic System with Unsteady Aerodynamic Model

Classical and Fuzzy Sliding Mode Control for a Nonlinear Aeroelastic System with Unsteady Aerodynamic Model

Aeroelastic stability analysis of aircraft wings with initial curvature

In this study, the aeroelastic instability of a wing with an initial out-of-plane curvature is determined. The structural dynamics of the wing is modelled by using the geometrically exact beam equations, and the aerodynamic loads are determined using an incompressible unsteady aerodynamic model. The wing is considered to have initial out-of-plane curvature, and the effect of the curvature on the flutter velocity and flutter frequency of the wing is determined. Two curved wing cases are considered here. In the first case, the length of the wing is assumed to be constant and therefore, as the wing is curved, the projected area of the wing decreases. In the second case, the wing is assumed to have a constant projected area and therefore different curvature angles result from different wing lengths. When the wing is designed to have an initial out-of-plane curvature, the wing dynamics change, and therefore the aeroelastic stability of the curved wing is also affected. It is shown that as the initial curvature of the wing increases, initially the flutter velocity decreases but then increases, and finally a sudden jump occurs in the flutter velocity due to the change of the coupled modes contributing to flutter. Moreover, the flutter frequency also first decreases as the curvature of the wing increases, and then there is a sudden jump in the frequency, and from this point again the frequency decreases. Finally, results highlighting the importance of the initial curvature and the length of the curved segment on the stability velocity and frequency of the curved wing are presented.

Real-Time Flow Control of Blade Section Using a Hydraulic Transmission System Based on an H-Inf Controller with LMI Design

Vibration and real-time flow control of the 2D blade section of wind turbines with three degrees of freedom (3-DOF), excited by external pitch motion, are investigated based on an H-inf (H∞) controller using linear-matrix-inequality (HIC/LMI) design. The real-time flow control for the purpose of aeroelastic flutter suppression includes not only the driving process of real-time physical equipment, but also the realization of real-time control algorithm in the physical controller. The aeroelastic system combined with pitch motion is controlled by a kind of HIC/LMI algorithm. The real-time external pitch motion is driven by rack-piston cylinder (RPC) using a hydraulic transmission system (HTS). The unsteady aerodynamic loads model is simplified by the HTS system. The HTS is actuated by a proportional-flow valve (PFV) which is controlled by another HIC/LMI algorithm, a novel algorithm for waveform tracking. According to the result of waveform tracking, the input current signal of PFV is realized by the configuration of the controller hardware system and its external circuits. In two types of HIC/LMI algorithms, controller stabilities are affirmed using Lyapunov analyses, and controller values are derived and obtained by using LMI designs. Flutter suppression for divergent and instable displacements is shown, with obvious controlled effects illustrated. An online monitoring experimental platform using hardware-in-the-loop simulation, based on Siemens S7-200 programmable logic controller (PLC) hardware and Kingview detection system, is built to implement pitch motion based on HTS and configure the signal input of PFV in pitch control.