Experimental and numerical investigation on large deformation reconstruction of thin laminated composite structures using inverse finite element method. (September 2022)

• Record Type: Journal Article
• Authors: Abdollahzadeh, M.A.; Ali, H.Q.; Yildiz, M.; Kefal, A.
• Is Part Of: Thin-walled structures. Volume 178(2022)
• Publication Date: 2022-09
• Subjects: Thin laminated composites -- Large displacement -- Inverse finite element method -- Nonlinear strain measurement -- Structural health monitoring; Thin-walled structures -- Periodicals; 690.1
• DOI: 10.1016/j.tws.2022.109485
• Languages: English
• ISSNs: 0263-8231

Abstract

Abstract: The inverse finite element method (iFEM) is one of the best candidates to perform displacement monitoring (shape sensing) of structures using a set of on-board/embedded strain sensors. This study demonstrates the high efficiency, robustness, and accuracy of the iFEM approach to reconstruct geometrically non-linear deformations of thin laminated plates and shells by performing experimental measurements and numerical analyses. The iFEM formulation is derived based on the first-order shear deformation theory of plates. A weighted least-squares variational principle is utilized with incremental non-linear strains while performing the geometrical update of the model using predicted incremental deformations. Moreover, a quadrilateral inverse-shell element (iQS4) is employed to discretize the whole domain of the laminated panels and solve the numerical/experimental shape-sensing problems. Further, a polynomial strain pre-extrapolation technique is incorporated with the iQS4 formulation to smoothen the discrete strain data obtained from a few strain rosettes placed along the entire length of the structures. For each case study, a high-fidelity finite element analysis is performed to establish a reference displacement solution. Finally, the qualitative and quantitative comparison of reconstructed displacement results with reference solutions confirms the superior potential of the iFEM-iQS4 approach for full-field shape sensing of thin laminates undergoing non-linear deformations. Highlights: High efficiency of the iFEM/iQS4 is numerically and experimentally proved for large deformation reconstruction of thin flat/curved laminates. Low-cost sensor placement models are proposed for effective shape sensing. Merits of polynomial strain pre-extrapolation is experimentally revealed for iFEM analysis. High sensing accuracy of iFEM is validated for post-buckling and non-linear deformations.