There are technical applications where structures undergo deformation in the geometrically non-linear domain. This is the case for high-aspect-ratio wings, which may play a more important role in the future aircraft designs. Shape sensing methods can estimate the deflection of these structures during operation, if a direct measurement of the displacements is inconvenient or not possible. For the geometrically nonlinear range, the modal rotation method has been proposed as a candidate suitable for slender structures. The method superposes modal rotation increments of segments along the length of the structure, typically obtained from a finite element model. If the method is applied model-free, based on modal rotations identified from test data, the variability of the modal rotations leads to uncertainty in the displacement estimates. The present study illustrates how displacement output uncertainty can be expressed using linearised propagation formulae, relying on the prerequisite that the modal rotations exhibit a normally distributed and independent scatter around their mean. This uncertainty propagation is investigated in the shape sensing of a high-aspect-ratio wing model, and verification through Monte Carlo simulations demonstrates that the derived expressions accurately propagate the uncertainty from variable modal rotations. Consequently, these expressions can be applied to specific shape sensing tasks in experiments where this variability can be recorded.

Shape sensing techniques allow for the time-efficient reconstruction of displacements based on measured strain data. There are technical applications, where the structure of interest is deformed in the geometrically non-linear domain. In aeronautics, this is the case for high-aspect-ratio wings, which are more frequently found in future designs. Only shape sensing methods that specifically take the non-linearity into account, can deliver appropriate displacement estimates for such application. A shape sensing method based on the linear modal approach can be utilised incrementally to capture the geometric non-linearity; it has therefore been denoted incremental modal method (IMM). This paper presents analytical relations for the uncertainty propagation for the various input quantities of the method, specifically strain mode shapes, displacement mode shapes, and measured strain. Deterministic shape sensing and uncertainty propagation are demonstrated using data obtained with a finite element model of a high-aspect-ratio wing experiencing geometric non-linear deflections in flapwise bending. Virtual strain and acceleration sensors are assumed for this setup, imitating the instrumentation conceivable for experimental work. The results obtained by analytical propagation are compared to Monte Carlo simulations for the purpose of validation. The derived propagation formulas make it possible to follow the evolution of the uncertainties over the number of increments. Given that the variability of the input quantities is known, the number of increments that minimise uncertainties can be determined for a model-free application of the shape sensing. Together with the deterministic estimates provided by an FE model, it is possible to determine the ideal number of increments for a specific shape sensing application in the geometrically non-linear domain.