Civil Engineering / İnşaat Mühendisliği

Permanent URI for this collectionhttps://hdl.handle.net/11147/13

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Start date: 2020Institution Author: search.filters.institutionAuthor.Hızal, Çağlayan

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Now showing 1 - 5 of 5
  • Article
    Citation - WoS: 10
    Citation - Scopus: 10
    A Reconnaissance Study in Izmir (bornova Plain) Affected by October 30, 2020 Samos Earthquake
    (Elsevier, 2021) Nuhoğlu, Ayhan; Erener, Mehmet Fahrettin; Hızal, Çağlayan; Kıncal, Cem; Erdoğan, Devrim Şüfa; Özdağ, Özkan Cevdet; Akgün, Mustafa
    On October 30th of 2020, 14:51 (GMT+3:00), Izmir city was hit by an earthquake of Mw = 7.0 magnitude (according to USGS). A rupture of 30-40 km of a west-east normal fault, which is roughly 12 km north to Samos Island caused significant damage, particularly in Izmir (Bornova plain). This study aims to present the preliminary field investigations, evaluation of structural damage as well as the possible geotechnical phenomenon affecting the damage that occurred. In this context, an extensive analysis of spectral characteristics of the earthquake and local site effects is presented. Field investigations reveal that there is a significant amplification of the rock acceleration along with a basin effect in the region, which results in a wider constant acceleration region. In addition, analysis of earthquake records shows a remarkable level of soil nonlinearity. Considering all these aspects, a detailed assessment of structural damage observed in Izmir Bayrakli District is presented. It is evident that, structures of poor construction details behaved as if they were affected by a near field earthquake. The structures to be constructed in alluvial zones such as Manavkuyu neighborhood should be designed considering the effects of soil amplification including basin effects and soil nonlinearity. To fulfill this aim, comparative results of 1D/2D/3D ground response analyses should be performed, for revising current earthquake codes.
  • Article
    Citation - WoS: 18
    Citation - Scopus: 19
    Modified Frequency and Spatial Domain Decomposition Method Based on Maximum Likelihood Estimation
    (Elsevier, 2020) Hızal, Çağlayan
    In this study, a Modified Frequency and Spatial Domain Decomposition (MFSDD) technique is developed for modal parameter identification, using output-only response measurements. According to the presented procedure, the most probable power spectral density matrix of the measured response (output PSD) is updated by a maximum likelihood estimation based on the observed data. Different from the available Frequency Domain Decomposition (FDD) techniques, a prediction error term which is associated with the measurement noise and modelling errors is included in the proposed methodology. In this context, a detailed discussion is provided from various aspects for the effect of measurement noise and modelling errors on the parameter estimation quality. Two numerical and two experimental analysis are conducted in order to demonstrate the effectiveness and accuracy of the proposed methodology under some extreme effects. The obtained results indicate that the proposed method shows very good performance in modal parameter estimation in case of noisy measurements.
  • Article
    Citation - WoS: 7
    Citation - Scopus: 9
    Frequency Domain Data Merging in Operational Modal Analysis Based on Least Squares Approach
    (Elsevier, 2020) Hızal, Çağlayan
    Assembling of multi-setup measurements emerges as a challenging problem in the structural health monitoring applications and may cause some important issues in the estimation of global modal parameters such as frequency, damping ratio and modal shape vector. To overcome this problem, a novel frequency domain pre-identification data merging method is proposed in this study. In the proposed methodology, to obtain a single measurement set, a least squares approach is employed resulting in a global response that is scaled from the multi-setup data. For the verification of the proposed merging procedure, one numerical, two experimental studies and one real data application have been conducted. The results obtained from the numerical, experimental and real data analysis indicate that the presented methodology provides rather high-quality estimations for multi-setup measurement problems. © 2020 Elsevier Ltd
  • Article
    Citation - WoS: 4
    Citation - Scopus: 5
    Pre-Identification Data Merging for Multiple Setup Measurements With Roving References
    (Springer Verlag, 2020) Ceylan, Hasan; Turan, Gürsoy; Hızal, Çağlayan
    One-time operational modal analysis (OMA) of large civil structures requires measurements of the vibrations, which, according to the number of channels to be measured, are generally expensive and arduous to obtain. In this study, identification of modal parameters of civil structures has been investigated by using multiple setups with a roving reference channel. In this manner, a limited amount of equipment becomes sufficient for OMA of structures. The procedure consists of a transformation function between measurement setups, which transforms all measured data to the time frame of a selected reference setup. To illustrate the procedure, an existing 10 story laboratory shear frame model is considered. A numerical and an experimental investigation have been carried out to identify its modal characteristics. The validity of the procedure has been explained in detail by making use of a coherence function in-between the multi-setup measurements. According to the results, OMA by using only a few sensors with the performed procedure can be equivalent to OMA by using a full measurement setup. Against a common believe, the results of this study reveal that synchronization among the setups does not prominently affect the identification results.
  • Article
    Citation - WoS: 29
    Citation - Scopus: 29
    A Two-Stage Bayesian Algorithm for Finite Element Model Updating by Using Ambient Response Data From Multiple Measurement Setups
    (Academic Press, 2020) Hızal, Çağlayan; Turan, Gürsoy
    This study presents a two-stage Bayesian finite element model updating procedure by using acceleration response measurements obtained from multiple setups. In the presented methodology, parametric uncertainties for the modal parameters are estimated by using the Bayesian Fast Fourier Transform Approach (BFFTA). Different from the previous Bayesian methods, a block diagonal covariance matrix is modeled for prior estimation of measured modal parameters. In addition, the modelling error in the eigenvalue equations is considered as soft constraints to be updated. Numerical and experimental studies are presented to validate the proposed method. The effect of soft constraints on the identification results as well as their posterior uncertainties are investigated. According to the results, it is shown that the proposed methodology can identify the most probable finite element model parameters with high level of accuracy. In addition, the posterior uncertainties obtained by the proposed procedure are significantly small when compared to the methods that consider rigid constraints for prediction and/or modelling error. (C) 2019 Elsevier Ltd. All rights reserved.