This paper aims to explore a new technique for structural damage identification using cubic spline interpolation. The method is based on the interpolation of modal rotations measured with shearography, making use of the analytical derivative of the spline to compute the modal curvature, which is known to be very sensitive to damage. As a means of reducing noise and measurement uncertainty propagation to a minimum, an expression for an optimal spatial sampling is derived. Furthermore, a baseline-free damage factor, allied with an optimal sampling, is also introduced. The proposed identification method is validated using experimental data of a beam. Using a damage localisation quality index, a comparison between the present method and one using finite differences is carried out, showing that the differentiation of spline interpolation leads to better damage identifications. The results obtained with the proposed approach show robustness and consistency in the localisations. Additionally, the hurdles of identifying small and multiple damage are tackled with the proposed method, yielding a good performance.

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Life without mobility is inconceivable. To enable this connectivity, one must find a way to progress towards a more sustainable transportation. In the aviation industry, a comprehensive understanding of greening technologies such as electrification of the propulsion system for commercial aircraft is required. A hybrid-electric propulsion concept applied to a regional aircraft is studied in the context of the FutPrInt50 project. To this end, the hybrid-electric propulsive system components are modeled, validated, and evaluated using computational and experimental data presented in the literature. The components are then assembled to construct the three powertrains for the hybrid-electric propulsion systems (Series, Parallel and Turboelectric) and parametric studies are carried out to study the influence of various battery parameters and hybridization factor. The performance results for a simple mission profile are generated. Together with a thermal management system, multi-objective optimization studies for the different architectures are then performed, with the power hybridization factor as the design variable and minimization of total mass and emissions as objective functions.