A robust multiscale concurrent optimization framework, which enables the precise functional-grading of mechanical properties within structures over two-scales, is presented within this paper and applied to a practical aerospace application — the mass minimization of a Goose Neck Hinge. The novelty of this framework lies in the concurrent nature of the response surface which enables the efficient calculation of small-scale mechanical properties during large-scale optimization. The efficacy of this approach permits a large number of design variables to be used in the parameterization of the small-scale without incurring a significant computational expense. The mass minimization of the Goose Neck Hinge constitutes a multi-objective optimization problem, constrained by a single maximum displacement constraint. Optimization of the Goose Neck Hinge was undertaken using both the framework presented within this paper and a density based topology optimization, to understand the relative performance of the multiscale framework to an industry standard method for structural optimization. The optimized multiscale geometry was able to satisfy the maximum displacement constraint using 20% less material than the density based topology optimization. This indicates that this framework has the potential to deliver a new generation of optimized aerospace structures.
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