Browsing by Author "Ceylan, Hasan"

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Modal parameter identification of civil engineering structures by using an output-only system identification technique
(Izmir Institute of Technology, 2015-07) Ceylan, Hasan; Turan, Gürsoy
Civil engineering structures are designed for a limited lifetime. Due to environmental effects and degradation of these structures, engineers need to decide on their structural safety and sustainability from time to time. To this end, structural health monitoring techniques could be employed to determine the current structural state. Current conditions of structures could be investigated by system identification techniques that is based on the modal parameters (modal frequencies, modal damping ratios and mode shapes) of structures. In this thesis, output-only system identification of civil structures is studied to estimate modal parameters of two different types of structures. For this purpose, a combination of the Natural Excitation Technique (NExT) and the Eigensystem Realization Algorithm (ERA) is coded within Matlab environment. The first study consists of a numerical and an experimental phase. In the numerical phase, the technique is implemented on the mathematical model of a three-story model building. In the experimental phase, it is implemented on the physical model of this three-story model building. 10 different scenarios of structural conditions are simulated by means of changes in story masses of the structure. By using NExT-ERA, the calculated modal frequencies and mode shapes are in good agreement with the results of the eigenvalue analysis. Further, the simulated mass change in each scenario is detected by a least squares approach. Changes in story masses are detected within reasonable errors. In the second study, a methodology is proposed to acquire measurements of large structures by using a few sensors, only. These sensors are used in a segmental way to measure the whole structure. The sensors are grouped and the groups of sensors are shifted on the model to obtain the response measurements from the whole structure. Then the grouped response measurements that are obtained at different time frames are transformed into the equivalent response data as if being acquired at a single time interval. To implement the methodology, a finite element model of a continuous beam bridge is constructed. Modal parameters of the model are estimated by using NExT-ERA and the results show that the first 10 modal frequencies are consistent with those of the eigenvalue analysis of the model, but only the first 6 mode shapes are successfully identified.
Probabilistic finite element model updating and damage detection of structures by using Bayesian statistics
(01. Izmir Institute of Technology, 2022-12) Ceylan, Hasan; Turan, Gürsoy
Finite element (FE) model updating is extensively employed in many applications of various engineering branches for damage detection purposes. An FE model is expected to reflect the properties of actual structures. However, it is almost impossible for an FE model to carry the properties of the real-life structure. As a result, differences exist between analytical models and actual structures. The aim of model updating is to minimize these differences as much as possible. In model updating procedures, there are inevitable uncertainties due to inevitable measurement noise and modelling errors. Therefore, model updating and damage detection process should be performed in a probabilistic way instead of a deterministic one. To this end, Bayesian model updating methods have gained much attention in the literature to account for the uncertainties of the parameters to be updated. Among these methods, those that use the concept of system modes have gained much more attention since it enables researchers to account for modelling error uncertainties and to avoid mode matching problem. For those methods, discrepancies between system modes and measured modes are considered and system modes are updated to obtain those that best fit the measured modes. Further, system modes are connected to the FE model via eigenvalue equations. In this study, a two-stage Bayesian model updating method which utilizes the concept of system modes has been firstly reformulated to compare three different assumptions on the modelling error variance of eigenvalue equations. Results reveal that the Bayesian model updating formulations that use the system modes concept give unreasonably too small posterior uncertainties for the updated parameters. This makes the probabilistic approach questionable since getting such small uncertainties may almost be equivalent to a deterministic approach. To increase the posterior uncertainty levels to more reasonable levels, a two-stage sensitivity-based Bayesian model updating methodology is proposed in this study. The results show that the proposed method successfully improves the updating results and increases the posterior uncertainties to more realistic levels.