Reduced-Order Model with an Artificial Neural Network for Aerostructural Design Optimization-Reference-Cited by-同舟云学术

Reduced-Order Model with an Artificial Neural Network for Aerostructural Design Optimization

Published:2013-07 Issue:4 Volume:50 Page:1106-1116
ISSN:0021-8669
Container-title:Journal of Aircraft
language:en
Short-container-title:Journal of Aircraft

Author:

Park Kyung Hyun¹,Jun Sang Ook²,Baek Sung Min³,Cho Maeng Hyo¹,Yee Kwan Jung⁴,Lee Dong Ho⁵

Affiliation:

1. School of Mechanical and Aerospace Engineering, Seoul National University, Seoul 151-742, Republic of Korea

2. Samsung Electro-Mechanics, Suwon-si, Gyeonggi-do 443-743, Republic of Korea

3. Construction Equipment System Research Department, Hyundai Heavy Industries, Ulsan 682-792, Republic of Korea

4. Department of Aerospace Engineering, Pusan National University, Busan 609-735, Republic of Korea

5. School of Mechanical and Aerospace Engineering and Institute of Advanced Aerospace Technology, Seoul National University, Seoul 151-742, Republic of Korea

Publisher

American Institute of Aeronautics and Astronautics (AIAA)

Subject

Aerospace Engineering

Link

http://arc.aiaa.org/doi/pdf/10.2514/1.C032062

Reference30 articles.

1. Reduced-order modeling: new approaches for computational physics

2. LuciaD. J. “Reduced Order Modelling for High Speed Flows With Moving Shocks,” Ph.D. Dissertation, Air Force Inst. of Technology, School of Engineering and Management, Wright-Patterson Air Force Base, Ohio, 2001.

3. Proper orthogonal decomposition

4. Efficient Reduced-Order System Identification for Linear Systems with Multiple Inputs

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