Prediction of Aircraft Dynamic Stability Derivatives Using Time-Spectral Computational Fluid Dynamics

Miyaji, Koji; Yoshida, Yu

doi:10.2322/tjsass.62.291

Cited by 3 publications

(3 citation statements)

References 11 publications

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“…Compared with the harmonic balance method, the operation process of the TSM is carried out in the time domain, avoiding the conversion between the time domain and frequency domain. TSM has been widely applied in various engineering problems of periodic unsteady flow, such as helicopter-rotor-motion and vortex-shedding problems [6].…”

Section: Introductionmentioning

confidence: 99%

High-Efficiency Simulation of Dynamic Stability Derivatives Based on a Particle Swarm Optimization and Long Short-Term Memory Network (PSO-LSTM) Coupling Aerodynamic Model

Cheng,

2023

Applied Sciences

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A new high-efficiency method based on a particle swarm optimization and long short-term memory network is proposed in this study to predict the aerodynamic forces in an unsteady state. Based on the predicted aerodynamic forces, the dynamic derivative is further calculated. Using particle swarm optimization to optimize the hyper-parameters of a neural network, the long short-term memory network prediction model can be constructed according to the known simulating aerodynamic data to predict the aerodynamic performance of aircraft in unknown states. By coupling the least-squares method in an aerodynamic derivative model, the dynamic derivative can be quickly obtained. Unsteady motion of NACA 0012 airfoil was taken as the research example to verify this method, and its longitudinal combined dynamic derivatives were predicted and compared with CFD simulation results. The results show that the dynamic derivatives predicted by the PSO-LSTM method have high accuracy, with an error of no more than 1% compared to CFD, and a 70% improvement in efficiency. The method proposed in this study has good generalization ability and can realize fast and accurate prediction of dynamic derivatives with a small number of samples.

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Section: Introductionmentioning

confidence: 99%

High-Efficiency Simulation of Dynamic Stability Derivatives Based on a Particle Swarm Optimization and Long Short-Term Memory Network (PSO-LSTM) Coupling Aerodynamic Model

Cheng,

2023

Applied Sciences

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“…Later, Murman (2007) used the method to calculate dynamic stability derivatives of aircraft by obtaining the periodic flows for the forced oscillation of the (rigid) aircraft. Furthermore, an efficient TS method with the implicit pseudo-time integration on unstructured grids was developed for the aircraft's dynamic stability (Miyaji and Yoshida, 2019). However, to apply the TS method to flutter problems, both the amplitude and frequency of the oscillation must be obtained from simulations, unlike the prescribed forced motion for the dynamic stability.…”

Section: Introductionmentioning

confidence: 99%

Prediction of transonic 2D wing flutter using the time-spectral computational fluid dynamics

MIYAJI,

TAKEGAWA

2022

JFST

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A new computation method to predict a transonic wing flutter under the limit-cycle oscillation (LCO) is developed using the time spectral (TS) method. The fluid and structural unknowns at a specified time interval in one cycle of the flutter are obtained by steady-state solutions of the aeroelastic TS equations, and thus higher computational efficiency is expected. Determining the frequency is the key for the flutter prediction, and we propose a method of minimizing the residuals of the fluid equation. The time histories of the plunge and pitch are reconstructed by the discrete Fourier transform, and compared with the existing time marching (TM) method. The effects of the number of harmonics in the TS and the time-step size in the TM are examined for the detailed comparison. The frequency, amplitude, and phase differences between the structural vibration modes all well agree between the two methods for a wide range of flutter speed index. Complex flutter boundaries are also predicted. The TS method is faster to reach the LCO than the TM method for the first vibration mode of the flutter. It is slower for the second vibration mode, but the increase in the computation time is much smaller than the reduction in the first mode. In general, the TS method is particularly advantageous for the prediction near flutter boundaries and is useful for aircraft design.

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“…17 Aerodynamic coefficients response upon time after forced excitation could be managed in a computer cluster and important information regarding rate and acceleration derivatives can be obtained with much ease and comfort as compared to the wind tunnel testing. 18,19 Interference effects with the test section walls and the complicated motion inside the wind tunnel test section in dynamic tests are difficult to manage.…”

Section: Introductionmentioning

confidence: 99%

Numerical estimation of longitudinal damping derivatives of a flying wing micro aerial vehicle

Shams

Shah

Shahzad

et al. 2022

Proceedings of the Institution of Mechanical Engineers, Part G:

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Longitudinal damping derivatives, [Formula: see text], of an aerial vehicle is important from an aerodynamic stability point of view. Experimental calculation of longitudinal damping derivatives using wind tunnel is not a cost-effective method; therefore, researchers have developed numerical solutions as an alternative. In this research, the longitudinal damping derivatives of a flying wing micro aerial vehicle (FWMAV) were calculated using numerical simulations by adopting pull-up maneuver and forced harmonic motion in pitch axis. Pull-up maneuver with four steady rotational rates was simulated to obtain pitch rate derivative, C mq. Combined derivative, [Formula: see text], was obtained by simulating forced harmonic motion of FWMAV around a mean angle of attack of 0° with amplitude of oscillation of ± 3° using four reduced frequencies (0.02, 0.03, 0.04, and 0.05). Unstructured surface and volume mesh was used in a spherical domain engulfed inside a large cuboid domain for moving reference frame strategy. Reynolds number taking mean aerodynamic chord as a reference length was 2.33 × 105. Spalart–Allmaras turbulence model was used. Pitch rate derivative, combined derivative, and acceleration derivative were found as − 0.03/rad, − 7.39/rad, and − 7.36/rad, respectively, by the use of a phase method at a reduced frequency of 0.03. During flight dynamic analysis, it was found that [Formula: see text] has a significant contribution on damping in short period mode with no effect on Phugoid mode. The research concluded that for tailless configurations, acceleration derivative [Formula: see text] can exist and can provide necessary damping in the longitudinal flight mode.

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Prediction of Aircraft Dynamic Stability Derivatives Using Time-Spectral Computational Fluid Dynamics

Cited by 3 publications

References 11 publications

High-Efficiency Simulation of Dynamic Stability Derivatives Based on a Particle Swarm Optimization and Long Short-Term Memory Network (PSO-LSTM) Coupling Aerodynamic Model

High-Efficiency Simulation of Dynamic Stability Derivatives Based on a Particle Swarm Optimization and Long Short-Term Memory Network (PSO-LSTM) Coupling Aerodynamic Model

Prediction of transonic 2D wing flutter using the time-spectral computational fluid dynamics

Numerical estimation of longitudinal damping derivatives of a flying wing micro aerial vehicle

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