D and DD-drop layup optimization of aircraft wing panels under multi-load case design environment. (15th September 2020)

• Record Type: Journal Article
• Authors: Shrivastava, Sachin; Sharma, Naresh; Tsai, Stephen W.; Mohite, P.M.
• Is Part Of: Composite structures. Volume 248(2020)
• Publication Date: 2020-09-15
• Subjects: DD-drop -- Composite wing-box optimization -- Unit circle failure criterion -- Mid-plane symmetry -- Laminate homogenization; Composite construction -- Periodicals; Composites -- Périodiques; 624.18
• DOI: 10.1016/j.compstruct.2020.112518
• Languages: English
• ISSNs: 0263-8223

Abstract

Abstract: The aerospace industry is on a perpetual drive to optimize structures with developments in modeling and analysis capabilities. The traditionally used laminates with 0 °, 90 °, ± 45 ° orientations are called Legacy QUAD Laminates (LQL). The recent discovery of Trace of an orthotropic stress tensor A allows reduction of design variables by the replacement of LQL with equivalent stiffness DD 1 (double-double) laminate having self-repeating orientations in a set of ± ϕ / ± ψ . The optimized LQL structures are with mid-plane symmetry, excessive ply-migrations, and variability in ply-orientations, which make the manufacturing process cumbersome. On the other hand, DD-laminates are simplified, thinner and free from mid-plane symmetry, thus enable ten-fold reduction in production resources. The present study, an artificial intelligent (AI) genetic-algorithm based stochastic optimizer replaces LQL with DD-laminates, which follows DD-drop design for mass optimization. The optimization algorithm works with unit-circle failure, buckling mode, and wing-tip deflection design criteria and derives optimal-wing with lowest mass, well suited for design requirements in multiple design load-case. The application of algorithm shows 68–70% mass reduction to an initial full-length ply wing-box model of LQL. The minimization of ply-migrations by D/DD-drop optimization yields structures with better resistance for delamination and well suited for automated production.