TY - JOUR
T1 - Optimization of composite cylinder shell via a data-driven intelligent optimization algorithm
AU - Chen, Ming
AU - Zhang, Xinhu
AU - Shen, Kechun
AU - Pan, Guang
N1 - Publisher Copyright:
© Published under licence by IOP Publishing Ltd.
PY - 2022/2/7
Y1 - 2022/2/7
N2 - While composite material provides huge flexibility for design, the design optimization of composite structure is time consuming with low efficiency. This work combines finite element analysis for composite cylinder shell with a data-driven intelligent optimization algorithm (Bayesian optimization algorithm) and is aimed at maximizing eigenvalue buckling load. Through minimizing number of iterations as a derivative-free global optimization algorithm, Bayesian optimization is versatile and can be further applied to design advanced composite structure with more complicated scenarios, such as complex geometries and load conditions.
AB - While composite material provides huge flexibility for design, the design optimization of composite structure is time consuming with low efficiency. This work combines finite element analysis for composite cylinder shell with a data-driven intelligent optimization algorithm (Bayesian optimization algorithm) and is aimed at maximizing eigenvalue buckling load. Through minimizing number of iterations as a derivative-free global optimization algorithm, Bayesian optimization is versatile and can be further applied to design advanced composite structure with more complicated scenarios, such as complex geometries and load conditions.
UR - http://www.scopus.com/inward/record.url?scp=85124948528&partnerID=8YFLogxK
U2 - 10.1088/1742-6596/2181/1/012019
DO - 10.1088/1742-6596/2181/1/012019
M3 - 会议文章
AN - SCOPUS:85124948528
SN - 1742-6588
VL - 2181
JO - Journal of Physics: Conference Series
JF - Journal of Physics: Conference Series
IS - 1
M1 - 012019
T2 - 2021 International Symposium on Artificial Intelligence and Intelligent Manufacturing, AIIM 2021
Y2 - 26 November 2021 through 28 November 2021
ER -