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Reliability Assessment Based on Structural Health Monitoring Data and Bayesian Updating of Structural Models
(01. Izmir Institute of Technology, 2024) Uzun, Ertuğrul Türker; Aktaş, Engin; Hızal, Çağlayan
Finite element (FE) models are commonly used in numerical modeling of structures, but their assumptions can lead to inaccuracies and uncertainties. To address this, FE model update methods have been developed, calibrating the model based on structural health monitoring (SHM) data. However, a general framework for realistic life cycle performance assessment of structures using monitored data has not yet been presented. Bayesian modeling can characterize uncertain structural parameters as random variables, but it is complex and time-consuming. Metamodeling techniques, which are effective stochastic predictors, can be used to decrease the computational burden of model updating. Adapting a Polynomial-Chaos-Kriging (PCK) metamodeling technique to Bayesian model updating in order to reduce uncertainty and circumvent computational challenges using SHM data in order to assess the reliability of structures more precisely is the objective of this research. Therefore, the effectiveness of the proposed method has been tried and demonstrated through experimental and numerical studies. An experimental study of a bridge column is used to evaluate the reliability of structures subjected to various corrosion effects. As a result, the proposed solution method reduces computational costs and enables an updated FE model to be closer to real structure measurements. The updated models are found to be more reliable in reliability evaluations, providing more accurate predictions on issues like structure safety, service life, and maintenance cost compared to non-updated models.
Designing Composite-Based Cylindrical Structures and Manufacturing Composite Prototypes by Filament Winding Method
(01. Izmir Institute of Technology, 2024) Martin, Seçkin; Tanoğlu, Metin
This study reports the design, finite element modeling, optimization, fabrication and testing of relatively thick (radius/thickness ~ 7) and long carbon fiber reinforced polymers produced by filament winding against buckling damage under axial loading. The optimum winding angle and stacking sequence against Linear (Eigenvalue) buckling were determined in accordance with the predetermined design requirements utilizing genetic algorithm (GA) optimization via MATLAB. During the optimization process, the critical buckling load factor (λcr) was assigned as objective function, design constraints were natural frequency (fn) and angle of twist (Φ), and ply angles were considered to be variable and restricted with 20 to 87-degree continuous fiber angles in the laminate sequences. As a consequence of the test results, λcr of the proposed optimum model was found to be 3.2 times better than the reference model and both the analytical and finite element model satisfactorily predicted the critical buckling load for all CFRP rods consistent with the test results. The critical buckling loads calculated by applying a KDF of 0.95 for the finite element model and a KDF of 0.9 for the analytical solution were found to be reasonably appropriate for use in the preliminary design input. Additionally, results showed that a higher axial to the circumferential ratio of axial and bending stiffness (A11/A22, D11/D22) promises better buckling performance than other possible candidates. Finally, the microstructures of the produced rods were examined and the fiber volume ratios were calculated by means of chemical characterization.

Phd Degree / Doktora

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