Airfoil Aeroelastic Flutter Analysis Based on Modified Leishman-Beddoes Model at Low Mach Number

An aeroelastic model for airfoil with a third-order stiffness in both pitch and plunge degree of freedom (DOF) and the modified Leishman–Beddoes (LB) model were built and validated. The nonintrusive polynomial chaos expansion (PCE) based on tensor product is applied to quantify the uncertainty of aerodynamic and structure parameters on the aerodynamic force and aeroelastic behavior. The uncertain limit cycle oscillation (LCO) and bifurcation are simulated in the time domain with the stochastic PCE method. Bifurcation diagrams with uncertainties were quantified. The Monte Carlo simulation (MCS) is also applied for comparison. From the current work, it can be concluded that the nonintrusive polynomial chaos expansion can give an acceptable accuracy and have a much higher calculation efficiency than MCS. For aerodynamic model, uncertainties of aerodynamic parameters affect the aerodynamic force significantly at the stage from separation to stall at upstroke and at the stage from stall to reattach at return. For aeroelastic model, both uncertainties of aerodynamic parameters and structure parameters impact bifurcation position. Structure uncertainty of parameters is more sensitive for bifurcation. When the nonlinear stall flutter and bifurcation are concerned, more attention should be paid to the separation process of aerodynamics and parameters about pitch DOF in structure.

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“…The result of present work was compared with the result of experiment and the result of Song [31], which are shown in Figures 4 and 5.…”

Section: Validation For Lco Analysismentioning

confidence: 94%

Bifurcation Analysis with Aerodynamic-Structure Uncertainties by the Nonintrusive PCE Method

Wang

Dai

Yang

2017

International Journal of Aerospace Engineering

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“…It should be noted that for parameters with physical meaning, the optimization range of these parameters will be given according to the conclusions of some literatures such as Ref. [25,54] to meet the physical meaning.…”

Section: Parameter Identification Methodologymentioning

confidence: 99%

“…6 International Journal of Aerospace Engineering where P 9 is the parameter to be identified related to the airfoil, α min is the initial angle at which the airflow readheres to the airfoil when the angle of attack decreases, V x and V xr are the shape functions of the lift coefficient generated by the "overshoot." The expression is as follows [54]:…”

Section: Nonlinear Correction Model Based On Flow Separationmentioning

confidence: 99%

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

Shi

Wan

et al. 2021

International Journal of Aerospace Engineering

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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.

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Low‐Speed Aerodynamic Nonlinearities

2017

Introduction to Nonlinear Aeroelasticity

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Airfoil Aeroelastic Flutter Analysis Based on Modified Leishman-Beddoes Model at Low Mach Number

Cited by 8 publications

References 11 publications

Bifurcation Analysis with Aerodynamic-Structure Uncertainties by the Nonintrusive PCE Method

Bifurcation Analysis with Aerodynamic-Structure Uncertainties by the Nonintrusive PCE Method

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

Low‐Speed Aerodynamic Nonlinearities

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