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

A methodology to generate design allowables of composite laminates using machine learning

“…These laminates are composed of plies of two orientations and are defined as [±φ/ ±ψ] n or [+φ/ +ψ/ −φ/ −ψ] n , where n is the number of repetitions. This bi-angle approach to laminate design results in stronger laminates with higher resistance to microcracking and delamination and in other advantages such as faster layup, simpler design and easier tapering through single ply drops [35,46]. DD-sublaminate lay-ups can be fully described by two parameters, φ and ψ, which can vary continuously from 0 • to 90 • .…”

Double–Double: New Family of Composite Laminates

“…It is therefore straightforward to have equal strength for the entire structure by making every point in the structure have R 1 or as close to it as possible. Weight savings in the order of 50% by tapering DD laminates were found [7,8]. This is not so with quad, because the sublaminates of quad are too thick and heterogeneous.…”

A data-driven Bayesian optimisation framework for the design and stacking sequence selection of increased notched strength laminates

“…Due to the relatively low computation time required to compute lamination parameters using Eqs. (5)(6), it is trivial to consider sample sizes in the order of 10 7 and return a set of stiness-matched ply orientations within seconds on a standard desktop PC.…”