Abdollahzadeh, Mohammadamin and Yıldız, Mehmet and Kefal, Adnan (2021) Three-dimensional shape sensing of a representative ship-hull cross-section based on inverse finite element method. In: The 34th Asian-Pacific Technical Exchange and Advisory Meeting on Marine Structures (TEAM 2020/21 Conference), Istanbul, Turkey
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Abstract
Marine structures are usually exposed to harsh environmental conditions such as wave strikes and severe hurricanes, which can lead to damage/failure of the structure. Therefore, the implementation of a reliable Structural Health Monitoring (SHM) system is crucial to reduce the economic cost and improve the predictive maintenance plan. As an important part of SHM, shape sensing reconstructs the displacement field using in-situ strain sensors. The inverse finite element method (iFEM) is a powerful technique for tracking the static and dynamic response of structural components in three dimensions in real time. For this purpose, iFEM uses strain data collected from a discrete number of on-board/embedded sensors. The main objective of this study is to monitor the deformation of a ship hull structure under representative loads due to hydrostatic pressure and water wave impacts using the iFEM method. A robust inverse shell element, called iQS4, is used to estimate the iFEM capability in three-dimensional shape sensing of a ship hull structure with only a number of sensors on board. A direct Finite Element Analysis (FEM) is performed to simulate the strain information required for the iFEM analysis. The obtained reference result is compared with the iFEM analysis to prove the efficiency and accuracy of the iFEM method in predicting the full-field deformation of such complex structures with only a few sensor paths. In addition, the accuracy of iFEM approach is also assessed for broken/damaged sensors among other sensors.
Item Type: | Papers in Conference Proceedings |
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Divisions: | Faculty of Engineering and Natural Sciences Integrated Manufacturing Technologies Research and Application Center |
Depositing User: | Mohammadamin Abdollahzadeh |
Date Deposited: | 11 Jun 2024 20:51 |
Last Modified: | 11 Jun 2024 20:51 |
URI: | https://research.sabanciuniv.edu/id/eprint/49367 |