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The purpose of this paper is to analyze the stability of aeroelastic systems using a novel reduced order aeroelastic model.

The proposed aeroelastic model is a reduced-order model constructed based on the aerodynamic model identification using the generalized aerodynamic force response and the unsteady boundary element method in various excitation frequency values. Due to the low computational cost and acceptable accuracy of the boundary element method, this method is selected to determine the unsteady time response of the aerodynamic model. Regarding the structural model, the elastic mode shapes of the shell are used.

Three case studies are investigated by the proposed model. In the first place, a typical two-dimensional section is introduced as a means of verification by approximating the Theodorsen function. As the second test case, the flutter speed of Advisory Group for Aerospace Research and Development 445.6 wing with 45° sweep angle is determined and compared with the experimental test results in the literature. Finally, a complete aircraft is considered to demonstrate the capability of the proposed model in handling complex configurations.

The paper introduces an algorithm to construct an aeroelastic model applicable to any unsteady aerodynamic model including experimental models and modal structural models in the implicit and reduced order form. In other words, the main advantage of the proposed method, further to its simplicity and low computational effort, which can be used as a means of real-time aeroelastic simulation, is its ability to provide aerodynamic and structural models in implicit and reduced order forms.

The purpose of this paper is to propose a new aerodynamic parameter estimation methodology based on neural network and output error method, while the output error method is improved based on particle swarm algorithm.

Firstly, the algorithm approximates the dynamic characteristics of aircraft based on feedforward neural network. Neural network is trained by extreme learning machine, and the trained network can predict the aircraft response at (k + 1)th instant given the measured flight data at kth instant. Secondly, particle swarm optimization is used to enhance the convergence of Levenberg–Marquardt (LM) algorithm, and the improved LM method is used to substitute for the Gauss Newton algorithm in output error method. Finally, the trained neural network is combined with the improved output error method to estimate aerodynamic derivatives.

Neither depending on the initial guess of the parameters to be estimated nor requiring numerical integration of the aircraft motion equation, the proposed algorithm can be used for unstable aircraft and is successfully applied to extract aerodynamic derivatives from both simulated and real flight data.

The proposed method requires iterative calculation and can only identify parameters offline.

The proposed method is successfully applied to estimate aircraft aerodynamic parameters and can also be used as a new algorithm for other optimization problems.

In this study, the output error method is improved to reduce the dependence on the initial value of parameters and expand its application scope. It is applied in aircraft aerodynamic parameter identification together with neural network.

The purpose of this paper is to present a novel method to design and manufacture rapid prototyping (RP) lightweight photopolymer‐resin models for wind‐tunnel tests. This method can ensure the structural configuration similarity considering model deformation under aerodynamic loads.

Photopolymer‐resin based on RP technique was used to fabricate DLR‐F4 models. Testing in a subsonic and transonic wind tunnel was carried out and the test results were compared to analyze performance predictions.

RP photopolymer‐resin wind‐tunnel models fabricated by the design methods yielded satisfactory aerodynamic performance. The methods can decrease the model's weight and prevent resonance occurrence among the models, wind‐tunnel, and support system, shorten the processing period, and lead to decrease in manufacturing period and cost.

Stiffness shortage of the thin components, such as wing tip, often leads to deformation occurrence under aerodynamic loads in transonic wind‐tunnel tests, which has significant influence on aerodynamic characteristics of the test models. Therefore, model deformation should be taken into account in the design process.

This design and manufacture method, aerodynamic and structural combination design and structural optimization, can obtain RP lightweight photopolymer‐resin wind‐tunnel models for satisfactory aerodynamic performance, which makes RP techniques more practical for manufacturing transonic wind‐tunnel test models, considering deformation induced by aerodynamic forces such as lift force. The methods also present an inexpensive way to test and evaluate preliminary aircraft designs, in both academia and industry.

The purpose of this paper is to investigate the estimation methodology with a highly generalized cost-effective single hidden layer neural network.

The aerodynamic parameter estimation is a challenging research area of aircraft system identification, which finds various applications such as flight control law design and flight simulators. With the availability of the large database, the data-driven methods have gained attention, which is primarily based on the nonlinear function approximation using artificial neural networks. A novel single hidden layer feed-forward neural network (FFNN) known as extreme learning machine (ELM), which overcomes the issues such as learning rate, number of epochs, local minima, generalization performance and computational cost, as encountered in the conventional gradient learning-based FFNN has been used for the nonlinear modeling of the aerodynamic forces and moments. A mathematical formulation based on the partial differentiation is proposed to estimate the aerodynamic parameters.

The real flight data of longitudinal and lateral-directional motion have been considered to estimate their respective aerodynamic parameters using the proposed methodology. The efficacy of the estimates is verified with the results obtained through the conventional parameter estimation methods such as the equation-error method and filter-error method.

The present study is an outcome of the research conducted on ELM for the estimation of aerodynamic parameters from the real flight data. The proposed method is capable to estimate the parameters in the presence of noise.

This paper aims to guide the implementation of noise reduction measures in hoistway and reduce the aerodynamic noise generated by elevator operation, this paper aims to propose an aerodynamic noise analysis method that can solve the flow field in hoistway.

A turbulence-acoustic model solving the flow field in a hoistway and a numerical wind hoistway model of the ultra-high-speed elevator were established by using large eddy simulation (LES) and Curle acoustic theory.

The characteristics of pulsating flow field and aerodynamic noise around ultra-high-speed elevator are analyzed. The asymmetric characteristics of the flow field could be observed using the turbulent kinetic energy and the instantaneous vortexes in the wind hoistway model. Vortex shedding, air flow separation and recombination around the car were the key factors for aerodynamic noise generation. The sound pressure level was approximately linear to the logarithm of car speed. The increase of car deflection angle in a certain range would reduce the peak frequency of wake noise and increase the sound pressure level (SPL) value.

This paper provides important guidance for researches studying the aerodynamic noise in the hoistway and the technical personnel that look for the reduction measures, which greatly improves the shortcomings in the numerical simulation of the aerodynamic noise of the hoistway.

The 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.

In 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.

The 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.

As 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.

This 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.

The purpose of this work is to apply and compare surrogate-assisted and multi-fidelity, multi-objective optimization (MOO) algorithms to simulation-based aerodynamic design exploration.

The three algorithms for multi-objective aerodynamic optimization compared in this work are the combination of evolutionary algorithms, design space reduction and surrogate models, the multi-fidelity point-by-point Pareto set identification and the multi-fidelity sequential domain patching (SDP) Pareto set identification. The algorithms are applied to three cases, namely, an analytical test case, the design of transonic airfoil shapes and the design of subsonic wing shapes, and are evaluated based on the resulting best possible trade-offs and the computational overhead.

The results show that all three algorithms yield comparable best possible trade-offs for all the test cases. For the aerodynamic test cases, the multi-fidelity Pareto set identification algorithms outperform the surrogate-assisted evolutionary algorithm by up to 50 per cent in terms of cost. Furthermore, the point-by-point algorithm is around 27 per cent more efficient than the SDP algorithm.

The novelty of this work includes the first applications of the SDP algorithm to multi-fidelity aerodynamic design exploration, the first comparison of these multi-fidelity MOO algorithms and new results of a complex simulation-based multi-objective aerodynamic design of subsonic wing shapes involving two conflicting criteria, several nonlinear constraints and over ten design variables.

The purpose of this paper is to investigate the aeroelastic behavior of a supersonic flight vehicle flying at moderate angles of attack using global analytic nonlinear aerodynamic model.

Aeroelastic behavior of a supersonic flight vehicle flying at moderate angles of attack is considered, using nonlinear aerodynamics and linear elastodynamics and structural models. Normal force distribution coefficient over the length of the vehicle and pitching moment coefficient are the main aerodynamic parameters used in the aeroelastic modeling. It is very important to have closed form analytical relations for these coefficients in the model. They are generated using global nonlinear multivariate orthogonal modeling functions in this work. Angle of attack and length of the vehicle are selected as independent variables in the first step. Local variation of angle of attack is applied to the analytical model and due to its variation along the body of the vehicle, equations of motion are finalized. Mach number is added to the independent variables to investigate its role on instability of the vehicle and the modified model is compared with the previous one in the next step. Thrust effect on the aeroelastic stability of the vehicle is analyzed at final stage.

It is shown that for the vehicles having simple configurations and low length to diameter ratios flying at low angles of attack, assuming normal force distribution coefficient linear relative to α is reasonable. It is concluded that vehicle's velocity and thrust has not great effect on its divergence dynamic pressure.

Based on the constructed model, a simulation code is generated to investigate the aeroelastic behavior of the vehicle. The resultant code is verified by investigating the static aeroelastic stability margin of the vehicle presented in the references. Mach number effect on the aeroelastic behavior of the vehicle is considered using modified aerodynamic model and is compared with the results. Data base for identifying aerodynamic coefficients is conducted using CFD code.

This paper aims to present the results of aerodynamic calculation of the aircraft in tandem wing configuration called VTOL. A presented vehicle combines the capabilities of the classic aircraft and helicopters. The aircraft is equipped with two pairs of tilt-rotors mounted on the tips of the front and the rear wing. The main goal of the presented research was to find the aerodynamic impact of both pairs of tilt-rotors on aerodynamic coefficients of the aircraft. Moreover, the rotors impact on the static stability of the aircraft was investigated too.

The CFD analysis was made for the complete aircraft in the tandem wing configuration. The computation was performed for the model of aircraft which was equipped with the four sub-models of the front and rear rotors. They were modeled as the actuator discs. This method allows for computing the aerodynamic impact of rotating components on the aircraft body. All aerodynamic analysis was made by the MGAERO software. The numerical code of the software was based on the Euler flow model. The used numerical method allows for the quick computation of very complex model of aircraft with a satisfied accuracy.

The result obtained by computation includes the aerodynamic coefficients which described the impact of the tilt rotors on the aircraft aerodynamic. The influence of the angle of attack, sideslip angle and the change of rotor tilt angle was investigated. Evaluation of the influence was made by the stability margin analysis and the selected stability derivatives computation.

Presented results could be very useful in the computation of dynamic stability of unconventional aircraft. Moreover, results could be helpful during designing the aircraft in the tandem wing configuration.

This paper presents the aerodynamic analysis of the unconventional configuration of the aircraft which combines the tandem wing feature with the tilt-rotor advantages. The impact of disturbance generated by the front and rear rotors on the flow around the aircraft was investigated. Moreover, the impact of rotors configuration on the aircraft static stability was found too.

Flight simulators are one of the noticeable breakthroughs in aerospace engineering. One of the main compartments of flight simulators is its control loading system (CLS). The CLS functions as a generator of virtual aerodynamic control-loads over control columns of a simulator. This paper aims to present the design of a high-fidelity six six degrees of freedom (6DOF) nonlinear CLS for the Boeing-747 aircraft simulator.

An introduction to CLS for flight motion simulators are first recapitulated. Afterward, the commanding devices are explained through schematics available in an engineering sense. This paper then presents in detail, the active control loading strategy and hardware design for the CLS, while also introducing the aerodynamic model structure. The satisfactory computer numerical simulations are presented before the paper ends up in concluding remarks.

The multiple input multiple output (MIMO) 6DOF nonlinear CLS for Boeing-747 flight simulator has been successfully developed. The outcome of computer simulations in real-time verifies practicality of the design strategy. The research presented in this paper could be a simple roadmap for prototyping high-fidelity 6DOF nonlinear CLS for flight motion simulators.

The available control architecture and hardware technologies cannot enable a high-fidelity load realization in a CLS. The existing research has not yet presented a 6DOF nonlinear MIMO CLS architecture along with the underlying controller setup for a high-fidelity load realization. In this paper, the design of a high-fidelity 6DOF nonlinear MIMO CLS for flight simulator of a large transport aircraft has been accomplished.