D and DD-drop layup optimization of aircraft wing panels under multi-load case design environment

The aerospace industry is on a perpetual drive to optimize structures with developments in modeling and anal-ysis capabilities. The traditionally used laminates with 0 degrees, 90 degrees, +/- 45 degrees 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 DD1 (double-double) laminate having self -repeating orientations in a set of [+/- 0/ +/- psi]. 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 reduc-tion 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 optimiza-tion 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.