• Earthquakes and Structures
• /
• 제25권4호
• /
• pp.235-247
• /
• 2023

Bingöl, a city in eastern Türkiye, is located at a very close distance to the Karlıova Region which is a junction point of the North Anatolian Fault Zone and Eastern Anatolian Fault Zone. By bilateral step over of North Anatolian Fault Zone and Eastern Anatolian Fault Zone each other there occurred NorthWest-SouthEast extended right-lateral and NorthEast-SouthWest extended left-lateral fault zones. In this paper, a typical school building located in Bingöl Çeltiksuyu was selected as the case study. Information on the school building and Bingöl Earthquake (2003) have been given in the paper. This study aimed to determine the fragility curves of the school building according to HAZUS 2022, Turkish Seismic Codes 1998, 2007 and 2018. These codes have been introduced in terms of damage limits. Incremental dynamic analysis is a parametric analysis method that has recently emerged in several different forms to estimate more thoroughly structural performance under seismic loads. Fragility analysis is commonly using to estimate the damage probability of buildings. Incremental Dynamic Analysis have performed, and 1295 Incremental Dynamic Analysis output was evaluated to obtain fragility curves. 20 different ground motion records have been selected with magnitudes between 5.6M and 7.6M. Scaling factors of these ground motions were selected between 0.1g and 2g. Comparison has been made between HAZUS 2022 and Turkish Seismic Codes 1998, 2007 and 2018 in terms of damage states and how they affected fragility curves. TSC 1998 has more conservative strictions along with TSC 2018 than TSC2007 and HAZUS moderate and extensive damage limits.

• Computers and Concrete
• /
• 제12권2호
• /
• pp.229-241
• /
• 2013

The objective of this study is to reveal the sufficiency of neural networks (NN) as a securer, quicker, more robust and reliable method to be used in seismic assessment of existing reinforced concrete buildings. The NN based approach is applied as an alternative method to determine the seismic performance of each existing RC buildings, in terms of damage level. In the application of the NN, a multilayer perceptron (MLP) with a back-propagation (BP) algorithm is employed using a scaled conjugate gradient. NN based model wasd eveloped, trained and tested through a based MATLAB program. The database of this model was developed by using a statistical procedure called P25 method. The NN based model was also proved by verification set constituting of real existing RC buildings exposed to 2003 Bingol earthquake. It is demonstrated that the NN based approach is highly successful and can be used as an alternative method to determine the seismic performance of each existing RC buildings.