A 2D-sampling optimization method for buckling layup design of doubly-curved laminated composite shallow shells. (1st October 2022)

• Record Type: Journal Article
• Authors: Jing, Zhao; Li, Xu; Sun, Qin; Liang, Ke; Zhang, Yongjie; Duan, Lei
• Is Part Of: Composite structures. Volume 297(2022)
• Publication Date: 2022-10-01
• Subjects: 2D-sampling optimization method -- Laminated composite shallow shells -- Lamination parameters -- Buckling -- Ritz method -- Higher-order shear deformation theory; Composite construction -- Periodicals; Composites -- Périodiques; 624.18
• DOI: 10.1016/j.compstruct.2022.115934
• Languages: English
• ISSNs: 0263-8223

Abstract

Abstract: A two-dimensional sampling optimization (2DSO) method is presented for buckling layup design of doubly-curved laminated composite shallow shells. The lamination parameters (LP) are utilized to represent distances of stacking sequences in composite laminates. Firstly, random continuous variables are generated that are distributed uniformly in LP design domain. Following that, stacking sequences are determined based on uniformly distributed LP. In terms of these stacking sequences, objective values are calculated, and a few best points are identified. Afterwards, the local sampling optimization is carried out iteratively in the vicinity of the best points until convergence is achieved. Lastly, a sequential permutation search (SPS) or a layerwise optimization approach (LOA) is served as the local optimization solver to target the final optimum. In addition, new Ritz solutions are derived for buckling of moderately thick doubly-curved laminated composite shallow shells using characteristic orthogonal polynomials based on a higher-order shear deformation theory (HSDT). Buckling loads of doubly-curved laminated composite shallow shells with different geometries, under multiple boundary conditions, subjected to different loadings, are optimized. Performances of 2DSO are compared to LOA, SPS, and genetic algorithm (GA), results illustrating that 2DSO outperforms LOA and SPS, and has similar robustness to GA while efficiency is multiplied several times.