Data-Driven Full-Field Prediction of Rotorcraft Fuselage Using Measurable Acceleration Response

  • Kim, Hyeongmo; 
  • Kim, Hyejin; 
  • Jeong, Inho; 
  • Kang, Woo-Ram; 
  • Lee, Hakjin; 
  • 외 1명
Citations

WEB OF SCIENCE

5
Citations

SCOPUS

4

초록

This paper presents a study aimed at predicting the full-field acceleration response of a rotorcraft fuselage. The prediction was achieved from the acceleration response observed at a limited sensor location on the rotorcraft. Moreover, the prediction was realized through a framework that used a data-driven model order reduction and long-short-term memory artificial neural network. To validate the performance of the proposed framework, a rotor/fuselage one-way coupled analysis was performed by considering a fuselage with a utility helicopter configuration and a platform rotorcraft. As a result, the efficiency and accuracy of the full-field prediction performance were confirmed by comparing with the finite element solutions.

키워드

Rotorcrafts; Aircraft Components and Structure; Finite Element Analysis; Artificial Neural Network; Acceleration Sensors; Helicopters; Reduced Order Modelling; Proper Orthogonal Decomposition; Mechanical and Structural Vibrations; Cylindrical Shell Structures; ACTIVE CONTROL; PLACEMENT
제목
Data-Driven Full-Field Prediction of Rotorcraft Fuselage Using Measurable Acceleration Response
저자
Kim, Hyeongmo; Kim, Hyejin; Jeong, Inho; Kang, Woo-Ram; Lee, Hakjin; Cho, Haeseong
DOI
10.2514/1.J064408
발행일
2025-04
유형
Article
저널명
AIAA Journal
권
63
호
4
페이지
1490 ~ 1501