TY - JOUR
T1 - Buckling resistance of grid-stiffened carbon-fiber thin-shell structures
AU - Shi, S.
AU - Sun, Z.
AU - Ren, M.
AU - Chen, H.
AU - Hu, Xiao
PY - 2013
Y1 - 2013
N2 - Critical local and global buckling loads of grid-stiffened carbon-fiber thin-shell structures, such as advanced grid-stiffened (AGS) conical shells relevant to aviation and aerospace applications, under uniform external transverse pressure were determined analytically using an equivalent stiffness model considering the influence of non-uniform grid distribution and the minimum potential energy principle. Experiments and finite-elements analysis have been carried out to assess the reliability of this analytical model. To maximize the buckling resistance for optimal design of the AGS conical shells, a hybrid genetic algorithm combining the genetic approach with a simulated annealing algorithm was developed, which considers the characteristics of multi-constraints and mixed discrete-continuous design variables. Comparisons between the benchmark results from the traditional genetic algorithm and simulated annealing algorithm confirmed the validity and efficiency of the hybrid genetic algorithms. Numerical examples show that the local-buckling constraint is a key factor for weight optimization of the AGS carbon-fiber conical. © 2012 Elsevier Ltd. All rights reserved.
AB - Critical local and global buckling loads of grid-stiffened carbon-fiber thin-shell structures, such as advanced grid-stiffened (AGS) conical shells relevant to aviation and aerospace applications, under uniform external transverse pressure were determined analytically using an equivalent stiffness model considering the influence of non-uniform grid distribution and the minimum potential energy principle. Experiments and finite-elements analysis have been carried out to assess the reliability of this analytical model. To maximize the buckling resistance for optimal design of the AGS conical shells, a hybrid genetic algorithm combining the genetic approach with a simulated annealing algorithm was developed, which considers the characteristics of multi-constraints and mixed discrete-continuous design variables. Comparisons between the benchmark results from the traditional genetic algorithm and simulated annealing algorithm confirmed the validity and efficiency of the hybrid genetic algorithms. Numerical examples show that the local-buckling constraint is a key factor for weight optimization of the AGS carbon-fiber conical. © 2012 Elsevier Ltd. All rights reserved.
U2 - 10.1016/j.compositesb.2012.09.052
DO - 10.1016/j.compositesb.2012.09.052
M3 - Article
SN - 1359-8368
VL - 45
SP - 888
EP - 896
JO - Composites Part B: Engineering
JF - Composites Part B: Engineering
IS - 1
ER -