Abstract: Strengthening of the existing seismically deficient reinforced concrete (RC) buildings is an important issue in earthquake prone regions. Addition of RC shear wall as infill or external walls into the structural system has been a commonly preferred strengthening technique since the Big Erzincan Earthquake occurred in Turkey, 1992. The newly added rigid infill walls act primarily as shear walls and relieve the non-ductile existing frames from being subjected to large shear demands providing that new RC inner or external walls are adequately anchored to the existing weak RC frame. The performance of the RC shear walls-RC weak frame connections by steel anchor dowels depends on some parameters such as compressive strength of the existing RC frame concrete, diameter and embedment length of anchored rebar, type of rebar, yielding stress of bar, properties of used chemicals, position of the anchor bars in RC. In this study, application problems of the steel anchor dowels have been checked with some field studies such as tensile test. Two different RC buildings which will be strengthened were selected, and before strengthening, some tests have been performed in the existing RC buildings. According to the field observation and experimental studies, if the concrete compressive strength is lower than 10 MPa, the performance of the anchors is reduced by 70%.
Abstract: In this study, an Artificial Neural Network (ANN)
analytical method has been developed for analyzing earthquake
performances of the Reinforced Concrete (RC) buildings. 66 RC
buildings with four to ten storeys were subjected to performance
analysis according to the parameters which are the existing material,
loading and geometrical characteristics of the buildings. The selected
parameters have been thought to be effective on the performance of
RC buildings. In the performance analyses stage of the study, level of
performance possible to be shown by these buildings in case of an
earthquake was determined on the basis of the 4-grade performance
levels specified in Turkish Earthquake Code-2007 (TEC-2007). After
obtaining the 4-grade performance level, selected 23 parameters of
each building have been matched with the performance level. In this
stage, ANN-based fast evaluation algorithm mentioned above made
an economic and rapid evaluation of four to ten storey RC buildings.
According to the study, the prediction accuracy of ANN has been
found about 74%.