Data-Based Prediction of Unsteady Aerodynamic Forces Induced by Free-Stream Turbulence-Reference-Cited by-同舟云学术

Data-Based Prediction of Unsteady Aerodynamic Forces Induced by Free-Stream Turbulence

Published:2022-11 Issue:6 Volume:35 Page:
ISSN:0893-1321
Container-title:Journal of Aerospace Engineering
language:en
Short-container-title:J. Aerosp. Eng.

Author:

Nash James¹,Sun Qiangqiang²,Xu Dong³,Zhang Wenqiang⁴,Xiao Dandan⁵^ORCID

Affiliation:

1. Student, Faculty of Engineering, Univ. of Nottingham, Nottingham NG7 2RD, UK.

2. Postdoctoral Researcher, Faculty of Engineering, Univ. of Nottingham, Nottingham NG7 2RD, UK.

3. Student, School of Mechatronical Engineering, Beijing Institute of Technology, Beijing 100081, China.

4. Associate Professor, School of Mechatronical Engineering, Beijing Institute of Technology, Beijing 100081, China.

5. Assistant Professor, School of Aerospace Engineering, Beijing Institute of Technology, Beijing 100081, China (corresponding author). ORCID: .

Publisher

American Society of Civil Engineers (ASCE)

Subject

Mechanical Engineering,Aerospace Engineering,General Materials Science,Civil and Structural Engineering

Link

https://ascelibrary.org/doi/pdf/10.1061/%28ASCE%29AS.1943-5525.0001503

Reference20 articles.

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2. Ba L. J. and R. Caruana. 2013. “Do deep nets really need to be deep?” Preprint submitted December 21 2013. https://arxiv.org/abs/1312.6184.

3. Barny H. 2012. “DELICAT-demonstration of LIDAR based clear air turbulence detection.” In Proc. Innovation for Sustainable Aviation in a Global Environment: Proc. Sixth European Aeronautics Days 30. Amsterdam Netherlands: IOS Press.

4. Machine Learning for Fluid Mechanics

5. Demuth, H., and M. Beale. 2002. Neural network toolbox for use with MATLAB. 4th ed. Natick, MA: MathWorks Inc.

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