Multi-level variable concurrent optimization framework for damping coated hybrid composites

Damping-coated hybrid laminates can be designed with various parameters to modify the local or overall per-formance, such as fiber volume, fiber orientation, stacking sequence, and material layout, which leads to opti-mization problems with design variables from different levels. It is not easy to fit the requirements of the new generation aerospace structures by optimizing variables separately. This paper proposes a multi-level variable concurrent optimization framework. First, the analysis model is constructed, where the fiber laminate is modeled with multiple patches. Then, the candidate material library of hybrid composites is established. Next, variables from different levels are unified into a single optimization process, and the concurrent optimization base on the Discrete Material Optimization (DMO) and the Solid Isotropic Material with Penalization (SIMP) methods is performed. Finally, the result is post-processed to obtain a fully 0/1 discrete design. An illustrative example of a plate is presented. The result shows a 10.5% and 57.1% advantage over the conventional design and a 10.6% and 13.7% advantage over the sequential optimization with the same constraint. It can be concluded that the pro-posed optimization framework is promising in utilizing the material capability by allocating material adaptively and considering the coupling effect between different components sufficiently.

Automated summary

This paper proposes a multi-level variable concurrent optimization framework to optimize the performance of damping-coated hybrid laminates in aerospace structures. The framework unifies variables from different levels and utilizes the material capability by allocating material adaptively. The result shows advantages over conventional and sequential optimization methods.