کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
793629 | 1466599 | 2014 | 19 صفحه PDF | دانلود رایگان |
![عکس صفحه اول مقاله: Nonlinear aeroelastic reduced order modeling by recurrent neural networks Nonlinear aeroelastic reduced order modeling by recurrent neural networks](/preview/png/793629.png)
The paper develops a reduction scheme based on the identification of continuous time recursive neural networks from input–output data obtained through high fidelity simulations of a nonlinear aerodynamic model at hand. The training of network synaptic weights is accomplished either with standard or automatic differentiation integration techniques. Particular emphasis is given to using such a reduced system in the determination of aeroelastic limit cycles. The related solutions are obtained with the adoption of two different approaches: one trivially producing a limit cycle through time marching simulations, and the other solving a periodic boundary value problem through a direct periodic time collocation with unknown period. The presented formulations are verified for a typical section and the BACT wing.
Journal: Journal of Fluids and Structures - Volume 48, July 2014, Pages 103–121