Search results

This paper aims to describe the concept of morphing tailless aircraft with discontinuous skin and its preliminary kinematic solution. Project assumptions, next steps and expected results are briefly presented.

Multidisciplinary numerical optimization will be used to determine control allocation for wing segments rotation. Wing demonstrator will be fabricated and tested in wind tunnel. Results will be used in construction of flying model and design of its control system. Flight data of morphing demonstrator and reference aircraft will result in comparative analysis of both technologies.

Proposed design combines advantages of wing morphing without complications of wing’s structure elastic deformation. Better performance, stability and maneuverability is expected due to wing’s construction which is entirely composed of unconnected wing segments. Independent control of each segment allows for free modeling of spanwise lift force distribution.

Nonlinear multipoint distribution of wing twist as the only mechanism for control and flight performance optimization has never been studied or constructed. Planned wind tunnel investigation of such complex aerodynamic structure has not been previously published and will be an original contribution to the development of aviation and in particular to the aerodynamics of wing with discontinuous skin.

This paper aims to improve the radial basis fuction mesh morphing method. During a shape optimization based on computational fluid dynamic (CFD) solvers, the mesh has to be changed. Two possible strategies are re-meshing or morphing. The morphing one is advantageous because it preserves the mesh connectivity, but it must be constrained.

RBF mesh deformation is one of the most robust and accurate morphing method. Using a greedy algorithm, the computational cost of the method is reduced. To evaluate the morphing performances, a rib shape optimization is performed using the NSGA-II algorithm coupled to kriging metamodels based on CFD. The morphing method is then compared to a re-meshing strategy.

The authors propose a method, based on Schur complement, to speed-up the greedy process. By using the information of the previous iteration, smaller linear systems are solved and time is saved. The optimization results highlight the interest of using a morphing-based metamodel regarding the resolution time and the accuracy of the interpolated solutions.

A new method based on Schur complement is addressed to speed-up the greedy algorithm and successfully applied to a shape optimization.

The purpose of this paper is to improve autonomous flight performance of a fixed-wing unmanned aerial vehicle (UAV) via simultaneous morphing wingtip and control system design conducted with optimization, computational fluid dynamics (CFD) and machine learning approaches.

The main wing of the UAV is redesigned with morphing wingtips capable of dihedral angle alteration by means of folding. Aircraft dynamic model is derived as equations depending only on wingtip dihedral angle via Nonlinear Least Squares regression machine learning algorithm. Data for the regression analyses are obtained by numerical (i.e. CFD) and analytical approaches. Simultaneous perturbation stochastic approximation (SPSA) is incorporated into the design process to determine the optimal wingtip dihedral angle and proportional-integral-derivative (PID) coefficients of the control system that maximizes autonomous flight performance. The performance is defined in terms of trajectory tracking quality parameters of rise time, settling time and overshoot. Obtained optimal design parameters are applied in flight simulations to test both longitudinal and lateral reference trajectory tracking.

Longitudinal and lateral autonomous flight performances of the UAV are improved by redesigning the main wing with morphing wingtips and simultaneous estimation of PID coefficients and wingtip dihedral angle with SPSA optimization.

This paper originally discusses the simultaneous design of innovative morphing wingtip and UAV flight control system for autonomous flight performance improvement. The proposed simultaneous design idea is conducted with the SPSA optimization and a machine learning algorithm as a novel approach.

Numerical simulation of icing has become a standard. Once the iced shape is known, however, the analyst needs to update the computational fluid dynamics (CFD) grid. This paper aims to propose a method to update the numerical mesh with ice profiles.

The present paper concerns a novel and fast radial basis functions (RBF) mesh morphing technique to efficiently and accurately perform ice accretion simulations on industrial models in the aviation sector. This method can be linked to CFD analyses to dynamically reproduce the ice growth.

To verify the consistency of the proposed approach, one of the most challenging ice profile selected in the LEWICE manual was replicated and simulated through CFD. To showcase the effectiveness of this technique, predefined ice profiles were automatically applied on two-dimensional (2D) and three-dimensional (3D) cases using both commercial and open-source CFD solvers.

If ice accreted shapes are available, the meshless characteristic of the proposed approach enables its coupling with the CFD solvers currently supported by the RBF4AERO platform including OpenFOAM, SU2 and ANSYS Fluent. The advantages provided by the use of RBF are the high performance and reliability, due to the fast application of mesh smoothing and the accuracy in controlling surface mesh nodes.

As far as authors’ knowledge is concerned, this is the first time in scientific literature that RBF are proposed to handle icing simulations. Due to the meshless characteristic of the RBF mesh morphing, the proposed approach is cross solver and can be used for both 2D and 3D geometries.

The purpose of this paper is to present a new model which combines the non-equidistant GM(1,1) model with GCHM_WBO (generalized contra-harmonic mean (GCHM); weakening buffer operator (WBO)). The authors use the model to solve the deadlock that for a large number of non-equidistant corrosion rate, it is difficult to establish a reasonable prediction model and improve the prediction accuracy.

This research consists of three parts: non-equidistant GM(1,1) model, GCHM_WBO operator, and the optimization of morphing parameter (contained in GCHM, control the intensity of the weakening operator). The methodology is explained as follows. First, the authors built a non-equidistant GM(1,1) model with GCHM_WBO weakened data, of which morphing parameter was randomly selected. Next, the authors calculated the error between prediction data of model and the real data, and adjusted the morphing parameter according to the error and property of GCHM. Then, the authors generated a new non-equidistant GM(1,1) based on new morphing parameter, and repeated the previous step until the termination condition was satisfied. Finally, the model with appropriate morphing parameter was used to implement the prediction of new data.

This paper finds a property of GCHM, which is a monotonic increasing function of morphing parameter in some specific conditions. Based on the property and the fixed point axiom of WBO, an algorithm was designed to search an appropriate morphing parameter. The appropriate morphing parameter was implemented for the purpose of improving the accuracy of the model. The model was applied to predict the corrosion rate of six steels at Guangzhou experimental station. The results showed that the proposed method can get more accuracy in prediction capability compared to the models with the original data and AWBO weakened data. The method is applicable to long-term forecasts in case of data scarcity.

Corrosion will cause huge economic loss to a country; therefore, it is important to judge the remaining useful life of a material or equipment; the foundation for judgement of which is the prediction of material corrosion rate. However, the prediction of corrosion rate is very difficult because of corrosion data’s features, such as small sample size, non-equidistant, etc. The proposed method can be used to implement long-term forecast of corrosion data with only one sample and non-equidistant samples.

This paper presented a model which combines the non-equidistant GM(1,1) model with GCHM_WBO to handle the problem of long-term forecasting of corrosion data. In the modelling process, the proposed morphing parameter searched through algorithm can improve the prediction accuracy of the model. Therefore, the model can provide effective and reliable result when data are of a small sample size and non-equidistant.

The purpose of this paper is to improve autonomous flight performance of an unmanned aerial vehicle (UAV) having actively sweep angle morphing wing using simultaneous UAV and flight control system (FCS) design.

An UAV is remanufactured in the ISTE Unmanned Aerial Vehicle Laboratory. Its wing sweep angle can vary actively during flight. FCS parameters and wing sweep angle are simultaneously designed to optimize autonomous flight performance index using a stochastic optimization method called as simultaneous perturbation stochastic approximation (SPSA). Results obtained are applied for flight simulations.

Using simultaneous design process of an UAV having actively sweep angle morphing wing and FCS design, autonomous flight performance index is maximized.

Authorization of Directorate General of Civil Aviation in Turkey is crucial for real-time UAV flights.

Simultaneous UAV having actively sweep angle morphing wing and FCS design process is so beneficial for recovering UAV autonomous flight performance index.

Simultaneous UAV having actively sweep angle morphing wing and FCS design process achieves confidence, high autonomous performance index and simple service demands of UAV operators.

Composing a novel approach to improve autonomous flight performance index (e.g. less settling and rise time, less overshoot meanwhile trajectory tracking) of an UAV and creating an original procedure carrying out simultaneous UAV having actively sweep angle morphing wing and FCS design idea.

It may appear rash to claim that an information retrieval system is ‘intelligent’, even if such claims are made within the limited context of artificial intelligence; nevertheless, such a claim is implicit in the MORPHS acronym: minicomputer operated retrieval (partially heuristic) system. What is a heuristic system? Heuristics are systems where the instigator is less than completely certain about the outcome of material fed into them. This is not the type of behaviour most would expect from a computer system, where provided the program has been written correctly, the software and hardware are functioning correctly, and the limits of the system are not exceeded, results are highly predictable.

This study aims to optimize autonomous performance (i.e. both longitudinal and lateral) and endurance of the quadrotor type aerial vehicle simultaneously depending on the autopilot gain coefficients and battery weight.

Quadrotor design processes are critical to performance. Unmanned aerial vehicle durability is an important performance parameter. One of the factors affecting durability is the battery. Battery weight, energy capacity and discharge rate are important design parameters of the battery. In this study, proper autopilot gain coefficients and battery weight are obtained by using a stochastic optimization method named as simultaneous perturbation stochastic approximation (SPSA). Because there is no direct correlation between battery weight and battery energy density, artificial neural network (ANN) is benefited to obtain battery energy density corresponding to resulted battery weight found from SPSA algorithm. By using the SPSA algorithm optimum performance index is obtained, then obtained data is used for longitudinal and lateral autonomous flight simulations.

With SPSA, the best proportional integrator and derivative (PID) coefficients and battery weight, energy efficiency and endurance were obtained in case of morphing.

It takes a long time to find the most suitable battery values depending on quadrotor endurance. However, this situation can be overcome with the proposed SPSA.

It is very useful to determine quadrotor endurance, PID coefficients and morphing rate using the optimization method.

Determining quadrotor endurance, PID coefficients and morphing rate using the optimization method provides advantages in terms of time, cost and practicality.

The proposed method improves quadrotor endurance. In addition, with the SPSA optimization method and ANN, the parameters required for endurance will be obtained faster and more securely. In addition, the energy density according to the battery weight also contributes to the clean environment and energy efficiency.

A distributed piezoelectric actuator (DPA) improving the deformation performance of wing is proposed. As the power source of morphing wing, the factors affecting the driving performance of DPA were studied.

The DPA is composed of a substrate beam and a certain number of piezoelectric patches pasted on its upper and lower ends. Utilizing the inverse piezoelectric effect of piezoelectric material, the DPA transfers displacement to the wing skin to change its shape. According to the finite element method and piezoelectric constitutive equation, the structure model of DPA was established, and its deformation behavior was analyzed. The accuracy of algorithm was verified by comparison with previous studies.

The results show that the arrangement way, length and thickness of piezoelectric patches, the substrate beam thickness and the applied voltage are the important factors to determine the driving performance of DPA.

This paper can provide theoretical basis and calculation method for the design and application of distributed piezoelectric actuator and morphing wing.

A novel morphing wing drove by DPA is proposed to improve environmental adaptability of aircraft. As the power source achieving wing deformation, the DPA model is established by FEM. Then the factors affecting the driving performance are analyzed. The authors find the centrosymmetric arrangement way of piezoelectric patches is superior to the axisymmetric arrangement, and distribution center of the piezoelectric patches determines the driving performance.

The purpose of this paper is to obtain values that stabilize the lateral and longitudinal flight of the quadrotor for which the morphing amount and the best Proportional-Integral-Derivative (PID) coefficients are determined by using the simultaneous perturbation stochastic approximation (SPSA) optimization algorithm.

Quadrotor consists of body and arms; there are propellers at the ends of the arms to take off and rotors that rotate them. By reducing the angle between mechanism 1 and the rotors with the horizontal plane, the angle between mechanism 2 and the arms, the rotors rise and different configurations are obtained. Conventional multi-rotor aircraft has a fixed fuselage and does not need a tail rotor to change course as helicopters do. The translational and rotational movements are provided by the rotation of the rotors of the aircraft at different speeds by creating moments about the geometric center in 6-degree-of-freedom (DOF) space. These commands sent from the ground are provided by the flight control board in the aircraft. The longitudinal and lateral flight stability and properties of different configurations evaluated by dynamic analysis and simulations in 6 DOF spaces are investigated. An algorithm and PID controller are being developed using SPSA to achieve in-flight position and attitude control of an active deformable aircraft. The results are compared with the results of the literature review and the results of the previous article.

With SPSA, the best PID coefficients were obtained in case of morphing.

The effects of quadrotor arm height and hub angle changes affect flight stability. With the SPSA optimization method presented in this study, the attitude is quickly stabilized.

With the optimization method, the most suitable PID coefficients and angle values for the lateral and longitudinal flight stability of the quadrotor are obtained.

The transition rate and PID coefficients are determined by using the optimization method, which is advantageous in terms of cost and practicality.

With the proposed method, the aircraft can change shape to adapt to different environments, and the parameters required for more stable flight for each situation will be calculated, and this will be obtained more quickly and safely with the SPSA optimization method.