Ganjdoust, Faraz (2022) Damage detection of laminated composite structures using inverse finite element method. [Thesis]
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Abstract
In recent years, structural health monitoring (SHM) has been revolutionized with the advent of an inverse method based on the minimization of a weighted least squares functional, known as inverse finite element method (iFEM). This approach is suitable for detection of damage, thanks to its ability in accurate full-field reconstruction of the displacement field over the problem domain. This study focuses on the application of iFEM for shape sensing and damage detection in various case studies, using numerically generated in-situ strain data via high fidelity forward finite element modeling (FEM). The study is conducted utilizing quadrilateral inverse-plane, and quadrilateral inverse-shell elements (iQS4). By utilizing the field variable achieved via the iFEM, equivalent von Mises strains are computed, after that, through definition of a damage index, the health of the structure is evaluated in terms of the presence of damage as well as its extent. Additionally, a new strategy is introduced for detection of the through-the-thickness damage in laminated composite materials by incorporating refined zigzag theory (RZT) in the iFEM algorithm. As a result of these analyses, the inverse algorithm shows its efficiency in detecting flawed regions over the problem domain and through the thickness of layered materials, both in terms of the location of the damage as well as its morphology.
Item Type: | Thesis |
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Uncontrolled Keywords: | Damage detection. -- laminated composite shells. -- inverse finite element method. -- refined zigzag theory. -- structural health monitoring. -- Hasar tespiti. -- lamine kompozit kabuklar. -- ters sonlu elemanlar yöntemi. -- hassaslaştırılmış zikzak teorisi. -- yapısal sağlık izleme. |
Subjects: | T Technology > TJ Mechanical engineering and machinery > TJ163.12 Mechatronics |
Divisions: | Faculty of Engineering and Natural Sciences > Academic programs > Mechatronics Faculty of Engineering and Natural Sciences |
Depositing User: | Dila Günay |
Date Deposited: | 27 Apr 2023 09:26 |
Last Modified: | 27 Apr 2023 09:26 |
URI: | https://research.sabanciuniv.edu/id/eprint/47182 |