• Advances in concrete construction
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• v.9 no.3
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• pp.313-326
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• 2020

Glass fiber-reinforced polymer (GFRP) bars have been introduced as an effective alternative for the conventional steel reinforcement in concrete structures to mitigate the costly consequences of steel corrosion. However, despite the superior performance of these composite materials in terms of corrosion, the effect of replacing steel reinforcement with GFRP on the seismic performance of concrete structures is not fully covered yet. To address some of the key parameters in the seismic behavior of GFRP-reinforced concrete (RC) structures, two full-scale beam-column joints reinforced with GFRP bars and stirrups were constructed and tested under two phases of loading, each simulating a severe ground motion. The objective was to investigate the effect of damage due to earthquakes on the service and ultimate behavior of GFRP-RC moment-resisting frames. The main parameters under investigation were geometrical configuration (interior or exterior beam-column joint) and joint shear stress. The performance of the specimens was measured in terms of lateral load-drift response, energy dissipation, mode of failure and stress distribution. Moreover, the effect of concrete damage due to earthquake loading on the performance of beam-column joints under service loading was investigated and a modified damage index was proposed to quantify the magnitude of damage in GFRP-RC beam-column joints under dynamic loading. Test results indicated that the geometrical configuration significantly affects the level of concrete damage and energy dissipation. Moreover, the level of residual damage in GFRP-RC beam-column joints after undergoing lateral displacements was related to reinforcement ratio of the main beams.

• Journal of the Korea Concrete Institute
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• v.18 no.5 s.95
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• pp.595-602
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• 2006

An experimental study was conducted to investigate seismic behaviour of post-tensioned(PT) exterior slab-column connections used for the purpose to resist gravity loads only. For these, 2/3-scale, two PT post-tensioned exterior connections with two different tendon arrangement patterns and one conventional reinforced concrete(RC) exterior connection was tested under quasi-static, uni-directional reversed cyclic loading. During the lateral testing, gravity forces transferred to the column were kept constant to closely simulate a moment to shear ratio of a real building. One of the objectives of this study was to assess the necessity and/or the quantity of bottom bonded reinforcement needed to resist moment reversal which would occur under significant inelastic deformations of the adjacent lateral force resisting systems. The ACI 318 and 352 provisions for structural integrity were applied to provide the bottom reinforcement passing through the column for the specimens. Prior test results were also collected to conduct comparative studies for some design parameters such as the tendon arrangement pattern, the effect of post-tensioning forces and the use of bottom bonded reinforcement. Consequently, the impact of tendon arrangement on the seismic performance of the PT connection, that is lateral drift capacity and ductility, dissipated energy and failure mechanism, was considerable. Moreover, test results showed that the amount of bottom reinforcement specified by ACI 352. 1R-89 was sufficient for resisting positive moments arising from moment reversal under reversed cyclic loads. Shear strength of the tested specimens was more accurately predicted by the shear strength equation(ACI 318) considering the average compressive stress over the concrete($f_{pc}$) due to post-tensioning forces than that without considering $f_{pc}$.

• Journal of the Korea Concrete Institute
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• v.24 no.3
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• pp.259-266
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• 2012

A general earthquake resistant design philosophy of ductile frame buildings allows beams to form plastic hinges adjacent to beam-column connections. In order to carry out this design philosophy, the ultimate bond or shear strength of the beam should be greater than the flexural yielding force and should not degrade before reaching its required ductility. The behavior of RC members dominated by bond or shear action reveals a dramatic reduction of energy dissipation in the hysteretic response due to the severe pinching effects. In this study, a method was proposed to predict the deformability of reinforced concrete members with short-span-to-depth-ratios, which would result in bond failure after flexural yielding. Repeated or cyclic loading produces a progressive deterioration of bond that may lead to failure at lower cyclic bond stress levels. Accumulation of bond damage is caused by the propagation of micro-cracks and progressive crushing of concrete in front of the lugs. The proposed method takes into account bond deterioration due to the degradation of concrete in the post yield range. In order to verify bond deformability of the proposed method, the predicted results were compared with the experimental results of RC members reported in the technical literature. Comparisons between the observed and calculated bond deformability of the tested RC members showed reasonably good agreement.

• Journal of the Korean Geotechnical Society
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• v.18 no.5
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• pp.37-42
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• 2002

Artificial neural networks are efficient computing techniques that are widely used to solve complex problems in many fields. In this paper a liquefaction potential was estimated by using a back propagation neural network model applicated to cyclic triaxial test data, soil parameters and site investigation data. Training and testing of the network were based on a database of 43 cyclic triaxial test data from 00 sites. The neural networks are trained by modifying the weights of the neurons in response to the errors between the actual output values and the target output value. Training was done iteratively until the average sum squared errors over all the training patterns were minimized. This generally occurred after about 15,000 cycles of training. The accuracy from 72% to 98% was shown for the model equipped with two hidden layers and ten input variables. Important effective input variables have been identified as the NOC,$D_10$ and (N$_1$)$_60$. The study showed that the neural network model predicted a CSR(Cyclic shear stress Ratio) of silty-sand reasonably well. Analyzed results indicate that the neural-network model is more reliable than simplified method using N value of SPT.