Optimization of imperfection-insensitive continuous tow sheared rocket launch structures

Geometric imperfection sensitivity is the largest influencing factor that limits the design of thin-walled monocoque cylinders. Current generation cylindrical architectures, such as those found in rocket launch vehicles, rely on the use of sandwich or blade-stiffened structures to reduce the imperfection sensitivity of the cylinder. Whilst much research has focused on the creation of new knockdown factors that relate to the modern architectures used, this paper focuses on reducing the imperfection sensitivity of a monocoque cylinder from a design perspective. Variable-angle composites that steer the fibers in curvilinear paths offer an opportunity to design structural load paths. By steering the fibers, the effective area over which geometric imperfections influence the buckling behavior of the cylinder is reduced. This diminishes the imperfection sensitivity of thin-walled cylinders undergoing axial compression. Continuous Tow Shearing (CTS) is one such variable-angle manufacturing technique. It does not cause common in-process manufacturing defects associated with Automated Fiber Placement, such as fiber wrinkling or fiber buckling. In addition, there is a shearing anglethickness coupling that results in local thickness build-ups, which, whilst potentially increasing the mass of the structure, enable embedded stiffeners to be created by shearing the tows. Three genetic algorithm (GA) optimizations are carried out to maximize the imperfect massspecific buckling load to investigate the efficacy of CTS and tow-steered designs in reducing imperfection sensitivity. The first optimization considers idealistic manufacturing capabilities with a random geometric imperfection. The second and third optimizations consider current manufacturing capabilities and are compared against one another to analyze the use of a evolutionary hybrid GA and a probabilistic, reliability-based GA. In all three optimizations, the optimum laminate from the GA demonstrates imperfection insensitivity.