Reinforcement Design for Composite Laminate with Large Cutout by a Genetic Algorithm Method

2013 ◽  
Vol 631-632 ◽  
pp. 754-758
Author(s):  
Zhong Lei Sun ◽  
Mei Ying Zhao ◽  
Li Long Luo

A dual-zone reinforcement ply stacking sequence optimization method used for comosite laminate with large cutout is present. The optimization method utilized a new Genetic Algorithm. The new Genetic Algorithm introduced a new strategy which can improve the efficiency of the traditional Genetic Algorithm and overcome the shortages of the worse convergency and prematurity of the Simple Genetic Algorithm. In the new Genetic Algorithm, the selection probability and the mutation probability are self-adaptive. Compared with the Simple Genetic Algorithm, the new Genetic Algorithm method shows good consistency, fast convergency and practical feasibility. By using the new Genetic Algorithm, the reinforcement ply stacking sequence optimization method got reasonable symmetric and balance stacking sequence which could meet the design requirements.

2019 ◽  
Vol 2019 ◽  
pp. 1-14 ◽  
Author(s):  
Bingbing San ◽  
Zhi Xiao ◽  
Ye Qiu

A simultaneous shape and stacking sequence optimization algorithm is presented for laminated composite free-form shells, by which the coupled effect of shape and stacking sequence can be considered. The optimization objective is determined as maximizing fundamental natural frequency to obtain largest stiffness of shells. Nonuniform rational B-spline (NURBS) is employed to represent free-form geometrical shapes. The coordinates of NURBS control points and fiber orientations are set up as continuous and discrete optimization variables, respectively, and optimized simultaneously. To improve the efficiency of the mixed continuous-discrete optimization, multi-island genetic algorithm (MIGA) is employed to search for the global result. Through several numerical examples, the performance of the proposed approach is demonstrated in comparison with the two-phase optimization method; the effect of boundary conditions and the setup of control points on optimal results are investigated, respectively.


2013 ◽  
Vol 48 (4) ◽  
pp. 795-805 ◽  
Author(s):  
Shenyan Chen ◽  
Zhiwei Lin ◽  
Haichao An ◽  
Hai Huang ◽  
Changduk Kong

Sign in / Sign up

Export Citation Format

Share Document