scholarly journals GPC-Based Gust Response Alleviation for Aircraft Model Adapting to Various Flow Velocities in the Wind Tunnel

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Yuting Dai ◽  
Chao Yang
Keyword(s):  
Wind Tunnel ◽  
Wind Tunnel Test ◽  
Open Loop ◽  
Ar Model ◽  
Aircraft Model ◽  
Input Amplitude ◽  
Aeroelastic Model ◽  
Wing Tip ◽  
Gust Response ◽  
Flow Velocities

A unified autoregressive (AR) model is identified, based on the wind tunnel test data of open-loop gust response for an aircraft model. The identified AR model can be adapted to various flow velocities in the wind tunnel test. Due to the lack of discrete gust input measurement, a second-order polynomial function is used to approximate the gust input amplitude by flow velocity. Afterwards, with the identified online aeroelastic model, the modified generalized predictive control (GPC) theory is applied to alleviate wing tip acceleration induced by sinusoidal gust. Finally, the alleviation effects of gust response at different flow velocities are estimated based on the comparison of simulated closed-loop acceleration with experimental open-loop one. The comparison indicates that, after gust response alleviation, the wing tip acceleration can be reduced up to 20% at the tested velocities ranging from 12 m/s to 24 m/s. Demonstratively, the unified control law can be adapted to varying wind tunnel velocities and gust frequencies. It does not need to be altered at different test conditions, which will save the idle time.

Wind Tunnel Test and the Analysis of Buffeting Performance of Free-Standing Tower of Cable-Stayed Bridge under Yaw Wind

2012 ◽  
Vol 532-533 ◽  
pp. 215-219
Author(s):  
Guo Hui Zhao ◽  
Yu Li ◽  
Hua Bai
Keyword(s):  
Wind Speed ◽  
Wind Tunnel ◽  
Wind Tunnel Test ◽  
Free Standing ◽  
Buffeting Response ◽  
Cable Stayed Bridge ◽  
Aeroelastic Model ◽  
Navigation Channel ◽  
Yaw Angle

The buffeting performance of free-standing tower of JiangHai Navigation Channel Bridge, a cable-stayed bridge, under yaw wind is investigated by means of wind tunnel test of aeroelastic model. It is found that the variation of buffeting response of free-standing tower with wind yaw angle is not monotonous. The lateral buffeting response on the top of the free-standing tower reach their minimal values and maximal values at around 150°and 180°of wind yaw angle respectively and the longitudinal buffeting response attain their maximal values at around 90°of wind yaw angle. Also, at the 2/3 height of the tower the lateral buffeting response and torsional buffeting response get their minimal values at around 150°of wind yaw angle, and at around 180°achieve the maximal values. It is also seen that, the buffeting response changes with the wind speed at a conic curve approximately.

Wind Tunnel Test of Honeycomb in Improving Flow Quality

2013 ◽  
Vol 774-776 ◽  
pp. 275-278
Author(s):  
Chun Guang Li ◽  
Yang Liu ◽  
John.C.K. Cheung
Keyword(s):  
Wind Tunnel ◽  
Cell Size ◽  
Turbulence Intensity ◽  
Wind Tunnel Test ◽  
Open Loop ◽  
Incoming Flow ◽  
Flow Quality ◽  
The Mean ◽  
Square Cells ◽  
Change Tendency

The function of honeycomb with different length and width in improving flow quality were studied in the course of building a new small section open loop wind tunnel. Instantaneous velocities of turbulent flow in the tunnel were measured by cobra probe. The focus of this study was put on the effect of the honeycomb in attenuating the total turbulence intensity including the free-turbulence carried by the incoming flow and the turbulence generated by the square cells themselves. The change tendency of the mean wind velocity and the total turbulence characteristics in the decay area have been studied by varying the length to cell size ratio L/D, and ratio of distance between the square cells and the measuring position to cell size X/D.

scholarly journals Gust Load Alleviation including Geometric Nonlinearities Based on Dynamic Linearization of Structural ROM

2019 ◽  
Vol 2019 ◽  
pp. 1-20
Author(s):  
Chao An ◽  
Chao Yang ◽  
Changchuan Xie ◽  
Yang Meng
Keyword(s):  
Wind Tunnel ◽  
Wind Tunnel Test ◽  
Kernel Functions ◽  
Structural Deformation ◽  
Control Technique ◽  
Feedback Signal ◽  
Response Analysis ◽  
Geometric Nonlinearities ◽  
Gust Load Alleviation ◽  
Gust Response

This paper describes a framework for an active control technique applied to gust load alleviation (GLA) of a flexible wing, including geometric nonlinearities. Nonlinear structure reduced order model (ROM) and nonplanar double-lattice method (DLM) are used for structural and aerodynamic modeling. The structural modeling method presented herein describes stiffness nonlinearities in polynomial formulation. Nonlinear stiffness can be derived by stepwise regression. Inertia terms are constant with linear approximation. Boundary conditions and kernel functions in the nonplanar DLM are determined by structural deformation to reflect a nonlinear effect. However, the governing equation is still linear. A state-space equation is established in a dynamic linearized system around the prescribed static equilibrium state after nonlinear static aeroelastic analysis. Gust response analysis can be conducted subsequently. For GLA analysis, a classic proportional-integral-derivative (PID) controller treats a servo as an actuator and acceleration as the feedback signal. Moreover, a wind tunnel test has been completed and the effectiveness of the control technology is validated. A remote-controlled (RC) model servo is chosen in the wind tunnel test. Numerical simulation results of gust response analysis reach agreement with test results. Furthermore, the control system gives GLA efficacy of vertical acceleration and root bending moment with the reduction rate being over 20%. The method described in this paper is suitable for gust response analysis and control strategy design for large flexible wings.

scholarly journals Design and Optimization of an Aeroservoelastic Wind Tunnel Model

Fluids ◽  
2020 ◽  
Vol 5 (1) ◽  
pp. 35 ◽  
Author(s):  
Johannes K. S. Dillinger ◽  
Yasser M. Meddaikar ◽  
Jannis Lübker ◽  
Manuel Pusch ◽  
Thiemo Kier
Keyword(s):  
Finite Element ◽  
Wind Tunnel ◽  
Wind Tunnel Test ◽  
Objective Functions ◽  
Dynamic Identification ◽  
Wind Tunnel Model ◽  
Design And Optimization ◽  
Aeroelastic Model ◽  
Tunnel Model ◽  
Gust Load Alleviation

Through the combination of passive and active load alleviation techniques, this paper presents the design, optimization, manufacturing, and update of a flexible composite wind tunnel model. In a first step, starting from the specification of an adequate wing and trailing edge flap geometry, passive, static aeroelastic stiffness optimizations for various objective functions have been performed. The second optimization step comprised a discretization of the continuous stiffness distributions, resulting in manufacturable stacking sequences. In order to determine which of the objective functions investigated in the passive structural optimization most efficiently complemented the projected active control schemes, the condensed modal finite element models were integrated in an aeroelastic model, involving a dedicated gust load alleviation controller. The most promising design was selected for manufacturing. The finite element representation could be updated to conform to the measured eigenfrequencies, based on the dynamic identification of the model. Eventually, a wind tunnel test campaign was conducted in November 2018 and results have been examined in separate reports.

Experimental Study of the Nonlinear Torsional Flutter of a Long-Span Suspension Bridge with a Double-Deck Truss Girder

2021 ◽  
pp. 2150102
Author(s):  
Ming Li ◽  
Yanguo Sun ◽  
Yongfu Lei ◽  
Haili Liao ◽  
Mingshui Li
Keyword(s):  
Wind Tunnel ◽  
Model Test ◽  
Wind Tunnel Test ◽  
Suspension Bridge ◽  
Suspension Bridges ◽  
Nonlinear Flutter ◽  
Long Span ◽  
Aeroelastic Model ◽  
Flutter Analysis ◽  
Section Model

The purpose of this study is to investigate the nonlinear torsional flutter of a long-span suspension bridge with a double-deck truss girder. First, the characteristics of nonlinear flutter are studied using the section model in the wind tunnel test. Different aerodynamic measures, e.g. upper and lower stabilizers and horizontal flaps, are applied to improve the flutter performance of the double-deck truss girder. Then, the full bridge aeroelastic model is tested in the wind tunnel to further examine the flutter performance of the bridge with the optimal truss girder. Finally, three-dimensional (3D) flutter analysis is performed to study the static wind-induced effects on the nonlinear flutter of the long-span suspension bridge. The results show that single-degree-of-freedom torsional limit cycle oscillations occur at large amplitudes for the double-deck truss section at the attack angles of [Formula: see text] and [Formula: see text]. The upper and lower stabilizers installed on the upper and lower decks, respectively, and the flaps installed near the bottoms of the sidewalks can all effectively alleviate the torsional flutter responses. Meanwhile, it is found that the torsional flutter responses of the truss girder in the aeroelastic model test are much smaller than those in the section model test. The 3D flutter analysis demonstrates that the large discrepancies between the flutter responses of the two model experiments can be attributed to the additional attack angle caused by the static wind-induced displacements. This finding highlights the importance and necessity of considering the static wind-induced effects in the flutter design of long-span suspension bridges.

scholarly journals Application of the HPCMP CREATETM-AV Kestrel to an Integrated Propeller Prediction

Aerospace ◽  
2020 ◽  
Vol 7 (12) ◽  
pp. 177
Author(s):  
Pooneh Aref ◽  
Mehdi Ghoreyshi ◽  
Adam Jirasek ◽  
Jürgen Seidel
Keyword(s):  
Experimental Data ◽  
Wind Tunnel ◽  
Wind Tunnel Test ◽  
Test Case ◽  
Simulation Tools ◽  
Electric Aircraft ◽  
Computational Resources ◽  
Adaptive Cartesian Grid ◽  
Low Speed Wind Tunnel ◽  
Wing Tip

This article presents the results of a computational investigation of an integrated propeller test case using the HPCMP CREATETM-AV Kestrel simulation tools. There is a renewed interest in propeller-driven aircraft for unmanned aerial vehicles, electric aircraft, and flying taxies. Computational resources can significantly accelerate the generation of aerodynamic models for these vehicles and reduce the development cost if the prediction tools can accurately predict the aircraft/propeller aerodynamic interactions. Unfortunately, limited propeller experimental data are available to validate computational methods. An American Institute of Aeronautics and Astronautics (AIAA) workshop was therefore established to address this problem. The objective of this workshop was to generate an open access-powered wind tunnel test database for computational validation of propeller effects on the wing aerodynamics, specifically for wing-tip-mounted propellers. The propeller selected for the workshop has four blades and a diameter of 16.2 in. The wing has a root and tip chord of 11.6 and 8.6 in, respectively. Two different simulation approaches were used: one using a single grid including wind tunnel walls and the second using a subset grid overset to an adaptive Cartesian grid that fills the space between the near-body grid and wind tunnel walls. The predictions of both approaches have been compared with available experimental data from the Lockheed Martin low-speed wind tunnel to investigate the grid resolution required for accurate prediction of flowfield data. The results show a good agreement for all tested conditions. The measured and predicted data show that wing aerodynamic performance is improved by the spinning tip-mounted propeller.

scholarly journals Gust response analysis and wind tunnel test for a high-aspect ratio wing

2016 ◽  
Vol 29 (1) ◽  
pp. 91-103 ◽  
Author(s):  
Yi Liu ◽  
Changchuan Xie ◽  
Chao Yang ◽  
Jialin Cheng
Keyword(s):  
Wind Tunnel ◽  
Aspect Ratio ◽  
High Aspect Ratio ◽  
Wind Tunnel Test ◽  
Response Analysis ◽  
Gust Response

scholarly journals A Novel Classification Method for Flutter Signals Based on the CNN and STFT

2019 ◽  
Vol 2019 ◽  
pp. 1-8 ◽  
Author(s):  
Shiqiang Duan ◽  
Hua Zheng ◽  
Junhao Liu
Keyword(s):  
Signal Processing ◽  
Deep Learning ◽  
Wind Tunnel ◽  
Learning Algorithm ◽  
Wind Tunnel Test ◽  
Structural Response ◽  
Classification Method ◽  
Time Frequency ◽  
Deep Learning Algorithm ◽  
Aeroelastic Model

Necessary model calculation simplifications, uncertainty in actual wind tunnel test, and data acquisition system error altogether lead to error between a set of actual experimental results and a set of theoretical design results; wind tunnel test flutter data can be utilized to feedback this error. In this study, a signal processing method was established to use the structural response signals from an aeroelastic model to classify flutter signals via deep learning algorithm. This novel flutter signal processing and classification method works by combining a convolutional neural network (CNN) with time-frequency analysis. Flutter characteristics are revealed in both time and frequency domains, which are harmonic or divergent in the time series; the flutter model energy is singular and significantly increases in the frequency view, so the features of the time-frequency diagram can be extracted from the dataset-trained CNN model. As the foundation of the subsequent deep learning algorithm, the datasets are placed into a collection of time-frequency diagrams calculated by short-time Fourier transform (STFT) and labeled with two artificial states, flutter or no flutter, depending on the source of the signal measured from a wind tunnel test on the aeroelastic model. After preprocessing, a cross-validation schedule is implemented to update (and optimize) CNN parameters though the trained dataset. The trained models were compared against test datasets to validate their reliability and robustness. Our results indicate that the accuracy rate of test datasets reaches 90%. The trained models can effectively and automatically distinguish whether or not there is flutter in the measured signals.

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