Browsing by Subject "Concrete buildings"

Now showing 1 - 4 of 4
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    Neural network model for moment-curvature relationship of reinforced concrete sections
    (2010) Baǧci M.
    The analysis of moment-curvature relationship of reinforced concrete sections is complex due to large number of variables as well as non-linear material behavior involved. Artificial Neural Networks (ANNs) are found to be a tool capable of solving such problems. This has led to increasing use of ANN for analyzing the behavior of reinforced concrete sections. This paper reports the details of a study conducted using ANN for predicting moment-curvature relationship of a reinforced concrete section. Using data generated based on the analytical solutions, the ANN model was trained. The trained model was tested for a different set of input parameters and the output values were compared with the values based on analytical results. The agreement was found to be good. © Association for Scientific Research.
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    A comparative evaluation of performance based analysis procedures according to 2007 Turkish Earthquake Code and FEMA-440
    (Association for Scientific Research, 2011) Erdem R.T.; Baǧci M.; Demir A.
    Chapter 7 of the 2007 Turkish Earthquake Code (TEC) entitled "Assessment and Strengthening of Existing Buildings" sets standards for assessment and rehabilitation of existing buildings. Linear elastic and non-linear evaluation procedures of 2007 TEC are applied to reinforced concrete buildings. 2007 TEC gives two methods for assessment and rehabilitation of existing buildings. Linear elastic and non-linear static evaluation procedures are proposed for structural evaluation. A performance-based evaluation methodology is used under three levels of earthquake ground motion intensities with different return periods. The performance acceptance criteria are based on demand to capacity ratios at critical sections for the linear evaluation procedures (equivalent seismic load method and mode superposition method) and material strains for the non-linear evaluation procedures (the non-linear static pushover analysis). Member performance limits are described for three damage levels, considering the anticipated failure mode and ductility capacity of each member. Structural performance is then calculated by accounting for the distribution of member damages over the building.. Consistency between the results of the methods used for seismic evaluation of existing buildings is of prime importance. For this purpose, an irregular structure of in plane (A3 type) and 3 story is considered. The target performance level of the building is obtained by applying the linear and the non-linear evaluation procedures. The results are given comparatively on the target performance level of the building. Furthermore non-linear procedure results are compared between 2007TEC and FEMA-440 Capacity-Spectrum Method (CSM) and Displacement- Coefficient Method (DCM). © Association for Scientific Research.
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    Dynamic behavior investigation of scale building renovated by repair mortar
    (Techno Press, 2015) Baaran H.
    The objective of this study was to examine the effect of repair mortar on the dynamic properties such as natural frequencies, mode shape and damping ratios of two story single span scale reinforced concrete building. To this end, two story single span scale reinforced concrete building having dimensions of 150 cm (width), 150 cm (length) and 135 cm (height) was constructed. Workmanship defects such as separation of material, faulty vibration application and bad gradation of the structure were properly evaluated. Dynamic properties of damaged structure were experimentally determined using Operational Modal Analysis (OMA). Detected defects in the structure were fixed by plastering with repair mortar. Dynamic properties of repaired structure were reevaluated by using the OMA method. Finite element software called Abaqus was used to numerically determine dynamic properties of the structure. Structure modeled as solid was subjected to Linear Perturbation Frequency Method. The changes in dynamic properties of structure after the repair process were comparatively studied by evaluating experimental and numerical results. © 2015 Techno-Press, Ltd.
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    A study on the estimation of prefabricated glass fiber reinforced concrete panel strength values with an artificial neural network model
    (Tech Science Press, 2016) Yildizel S.A.; Öztürk A.U.
    In this study, artificial neural networks trained with swarm based artificial bee colony optimization algorithm was implemented for prediction of the modulus of rapture values of the fabricated glass fiber reinforced concrete panels. For the application of the ANN models, 143 different four-point bending test results of glass fiber reinforced concrete mixes with the varied parameters of temperature, fiber content and slump values were introduced the artificial bee colony optimization and conventional back propagation algorithms. Training and the testing results of the corresponding models showed that artificial neural networks trained with the artificial bee colony optimization algorithm have remarkable potential for the prediction of modulus of rupture values and this method can be used as a preliminary decision criterion for quality check of the fabricated products. © 2016 Tech Science Press.