Shape Sensing and Load Reconstruction for Static and Dynamic Applications

Shape Sensing and Load Reconstruction for Static and Dynamic Applications

Minigher, Paolo (TU Delft Aerospace Engineering)

Castro, Saullo G.P. (mentor)
Gundlach, Janto (mentor)

Delft University of Technology

Aerospace Engineering

2022-07-25

The reconstruction of the elastic deformed shape of a structure from strain measurements is a field which has received considerable attention over the years. This work aims to suggest some improvements for wing-like structures trying to limit as much as possible the amount of strain measurements needed. In particular, a simple beam model is proposed based on the framework of the inverse Finite Element Method (iFEM). Then, the performances of iFEM using shell
elements will be enhanced pre-extrapolating the strain field and the results will be compared with another shape sensing method, the so-called Modal Method (MM). In the final part of the work the external loads under the form of a pressure field are recovered using both the reconstructed displacements and directly the strain measurements. Both static and dynamic analyses will be carried out, so recovering the load both in space and in time.
The results obtained show that the beam model developed allows to obtain a satisfactory bending reconstruction of the structure, while the twist is not always accurate. Computing the full displacement field with iFEM brings to a relatively good representation, even though not as satisfactory as the one delivered by the Modal Method. Finally, recovering the static external loads directly from the strain measurements seems to perform better compared to the reconstruction from the full displacement field, but it is significantly affected by noise and uncertainties. The dynamic load reconstruction is in general much more challenging and the
results obtained often show a significant error compared to the reference solution.

Shape sensing
Load reconstruction
iFEM

http://resolver.tudelft.nl/uuid:7400c81a-c5bf-4422-bc2b-c5870dae46f6

2023-01-31

Student theses

master thesis

© 2022 Paolo Minigher