Investigation of single and multicell honeycomb reinforced shape memory polymer composites: Shape optimization and experimental characterization

Abstract

Honeycomb materials as reinforcements for shape memory polymers have been considered for their commercial availability, ease of geometric tailoring, and high in-plane stiffnesses. The design optimization of these honeycomb cells remains an open field of research, with many approaches taken in formulating the structural optimization problems. This investigation focuses on implementing a shape variable parametrization of the honeycomb to study the possible value of both cell asymmetry and spatially varying cell geometries in multicell networks. A unit cell finite element model framework was developed to predict the in-plane elastic properties of these composites, and two design objectives were selected to be optimized. Pareto fronts were estimated for multiple loading cases and cell wall material models, and experimental results were collected for model validation. The optimization results find that these composites can achieve a large range of performances, with maximum moduli as high as 17.2 GPa. Large asymmetry is found in the optimized cell geometries, and relationships are identified between loading cases and for different wall materials. Furthermore, the experimental results validate the finite element model predictions, with relative errors as low as 20% for the predicted maximum modulus and 2% for the modulus ratio.