Longitudinal and Lateral-Directional Coupling Effects on Nonlinear Unsteady Aerodynamic Modeling from Flight Data

2002 ◽  
Author(s):  
C. Edward Lan ◽  
Jilu Li ◽  
Waipang Yau ◽  
Jay Brandon
Keyword(s):  
Coupling Effects ◽  
Flight Data ◽  
Aerodynamic Modeling ◽  
Unsteady Aerodynamic ◽  
Directional Coupling

Aircraft Lateral Parameter Estimation from Flight Data with Unsteady Aerodynamic Modeling

1982 ◽  
Vol 19 (3) ◽  
pp. 206-210 ◽  
Author(s):  
William R. Wells ◽  
Siva S. Banda ◽  
David L. Quam
Keyword(s):  
Parameter Estimation ◽  
Flight Data ◽  
Aerodynamic Modeling ◽  
Unsteady Aerodynamic

scholarly journals Real-Time Onboard Global Nonlinear Aerodynamic Modeling from Flight Data

2016 ◽  
Vol 53 (5) ◽  
pp. 1261-1297 ◽  
Author(s):  
Jay M. Brandon ◽  
Eugene A. Morelli
Keyword(s):  
Real Time ◽  
Flight Data ◽  
Aerodynamic Modeling ◽  
Nonlinear Aerodynamic

Surrogate Unsteady Aerodynamic Modeling with Autoencoders and LSTM Networks

2022 ◽  
Author(s):  
Huseyin E. Tekaslan ◽  
Yusuf Demiroglu ◽  
Melike Nikbay
Keyword(s):  
Aerodynamic Modeling ◽  
Unsteady Aerodynamic

Spin Aerodynamic Modeling for a Fixed-Wing Aircraft Using Flight Data

2022 ◽  
Author(s):  
James L. Gresham ◽  
Benjamin M. Simmons ◽  
Jeremy W. Hopwood ◽  
Craig A. Woolsey
Keyword(s):  
Flight Data ◽  
Aerodynamic Modeling

Unsteady aerodynamic modeling and control of the wind turbine with trailing edge flap

2018 ◽  
Vol 10 (6) ◽  
pp. 063304 ◽  
Author(s):  
Wenguang Zhang ◽  
Yifeng Wang ◽  
Ruijie Liu ◽  
Haipeng Liu ◽  
Xu Zhang
Keyword(s):  
Wind Turbine ◽  
Trailing Edge ◽  
Modeling And Control ◽  
Aerodynamic Modeling ◽  
Unsteady Aerodynamic ◽  
Trailing Edge Flap ◽  
And Control

Physical Essence of Stall Phenomena and its WNN-Based Aerodynamic Modeling from Flight Data

2014 ◽  
Vol 602-605 ◽  
pp. 3140-3143
Author(s):  
Xu Sheng Gan ◽  
Xue Qin Tang ◽  
Hai Long Gao
Keyword(s):  
Neural Network ◽  
Wavelet Neural Network ◽  
Flight Data ◽  
Numerical Examples ◽  
Aerodynamic Modeling ◽  
Aerodynamic Model ◽  
Aerodynamic Method ◽  
Physical Essence ◽  
Set Up

To understand the characteristics of aircraft stall for better aerodynamic model, the physical essence of the stall phenomena of aircraft is first introduced, and then a Wavelet Neural Network (WNN) is proposed to set up the stall aerodynamic model. Numerical examples indicates that through the deep cognition of the stall phenomena of aircraft the proposed stall aerodynamic method has a better accuracy than the traditional neural network and is also effective and feasible.

Unsteady aerodynamic modeling and control of pusher and tilt-rotor quadplane configurations

2019 ◽  
Vol 94 ◽  
pp. 105421 ◽  
Author(s):  
Yunus Govdeli ◽  
Sheikh Moheed Bin Muzaffar ◽  
Raunak Raj ◽  
Basman Elhadidi ◽  
Erdal Kayacan
Keyword(s):  
Modeling And Control ◽  
Tilt Rotor ◽  
Aerodynamic Modeling ◽  
Unsteady Aerodynamic ◽  
And Control

Continuous-time state-space unsteady aerodynamic modeling based on boundary element method

2012 ◽  
Vol 36 (5) ◽  
pp. 789-798 ◽  
Author(s):  
Meysam Mohammadi-Amin ◽  
Behzad Ghadiri ◽  
Mostafa M. Abdalla ◽  
Hassan Haddadpour ◽  
Roeland De Breuker
Keyword(s):  
Boundary Element Method ◽  
State Space ◽  
Boundary Element ◽  
Continuous Time ◽  
Aerodynamic Modeling ◽  
Unsteady Aerodynamic ◽  
Element Method
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