Affiliation:
1. Faculty of Aerospace Engineering, Delft University of Technology, Kluyverweg 1, 2629 HS Delft, The Netherlands
2. Department of Mechanical and Aerospace Engineering, Clarkson University, 8 Clarkson Av., Potsdam, NY 13699, USA
Abstract
Two shape-sensing algorithms, the calibration matrix (CM) method and the inverse Finite Element Method (iFEM), were compared on their ability to accurately reconstruct displacements, strains, and loads and on their computational efficiency. CM reconstructs deformation through a linear combination of known load cases using the sensor data measured for each of these known load cases and the sensor data measured for the actual load case. iFEM reconstructs deformation by minimizing a least-squares error functional based on the difference between the measured and numerical values for displacement and/or strain. In this study, CM is covered in detail to determine the applicability and practicality of the method. The CM results for several benchmark problems from the literature were compared to the iFEM results. In addition, a representative aerospace structure consisting of a twisted and tapered blade with a NACA 6412 cross-sectional profile was evaluated using quadratic hexahedral solid elements with reduced integration. Both methods assumed linear elastic material conditions and used discrete displacement sensors, strain sensors, or a combination of both to reconstruct the full displacement and strain fields. In our study, surface-mounted and distributed sensors throughout the volume of the structure were considered. This comparative study was performed to support the growing demand for load monitoring, specifically for applications where the sensor data is obtained from discrete and irregularly distributed points on the structure. In this study, the CM method was shown to achieve greater accuracy than iFEM. Averaged over all the load cases examined, the CM algorithm achieved average displacement and strain errors of less than 0.01%, whereas the iFEM algorithm had an average displacement error of 21% and an average strain error of 99%. In addition, CM also achieved equal or better computational efficiency than iFEM after initial set-up, with similar first solution times and faster repeat solution times by a factor of approximately 100, for hundreds to thousands of sensors.
Reference65 articles.
1. Reengineering Aircraft Structural Life Prediction Using a Digital Twin;Tuegel;Int. J. Aerosp. Eng.,2011
2. Glaessgen, E., and Stargel, D. (2012, January 23–26). The Digital Twin Paradigm for Future NASA and U.S. Air Force Vehicles. Proceedings of the 53rd AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference, Honolulu, HI, USA.
3. An efficient curved inverse-shell element for shape sensing and structural health monitoring of cylindrical marine structures;Kefal;Ocean Eng.,2019
4. Saunders, C.G. (1982, January 24–27). Reconstruction of Anatomical Shapes from Moire Contourographs. Proceedings of the Biostereometrics’ 82, San Diego, CA, USA.
5. Saunders, C.F.G. (1984, January 17–22). Automated Prosthetic Fitting. Proceedings of the Second International Conference on Rehabilitation Engineering, Ottawa, ON, Canada.