scholarly journals Cyclic performance of exterior R.C beam-column strengthened with different thicknesses of CFRP sheets

2022 ◽  
Vol 961 (1) ◽  
pp. 012069
Author(s):  
Mustafa Kareem Hamzah ◽  
Raizal Saifulnaz M. Rashid ◽  
Farzad Hejazi

Abstract The recent ground motion results indicated that the RC buildings are required to be retrofitted by different strengthening techniques. Nowadays, the external strengthening gain interest since its easy, cost effective and not required redesign of buildings. The CFRP sheets are suitable solution and utilized by a number of researchers. However, the numerical cyclic performance of connection strengthened with different thicknesses of CFRP need to be well investigated. This study assessed the performance of RC exterior beam column connection strengthened with CFRP sheets First, two grades of concrete are utilized to be control specimens, normal concrete compressive strength (C20) and high concrete compressive strength (C50) then, the specimens are retrofitted with different thicknesses (1.2, 2.4, 3.6mm) of CFRP sheets. The stresses and damage states showed the importance of connection retrofitting. The CFRP shift the plastic hinge zone away from the panel zone. Furthermore, the results demonstrated that by increase of CFRP thickness the connection resistance will be improved. The comparison between the hysteresis curves demonstrated that the yield and ultimate loading were enhanced for strengthened connection for both concrete grades and the incremental in thicknesses also increase them. The outputs also exhibited that the stiffness and ductility has increased for retrofitted specimens indicating that the CFRP comprehensively overcome the applied cyclic loading and the beam column connection is able to resist such type of loading.

2014 ◽  
Vol 875-877 ◽  
pp. 1490-1494
Author(s):  
Abdoullah Namdar ◽  
Ideris Bin Zakaria ◽  
Azam Khodashenas Pelko ◽  
Nurmunira Binti Muhammad

Several concrete additives have been innovated for improving concrete quality. In this research work the treated kaolin by heat has been used as concrete additive. Kaolin was subjected to the heat for 1 hour in different degree of temperatures. The crystal structure of Kaolin thermally is modified under heat and microstructure of the hydrated samples has been investigated using FESEM. The main objective is to introduce a cost effective concrete additive. The result is indicated that when kaolin subjected to 800 oC and used in 6% quantity as an additive in concrete mixed design, the concrete compressive strength of 14 days is 40% higher than concrete compressive strength of 28 days which is not used any additive. And if 12% additive is used the concrete compressive strength increased in same level on 7 days. This concrete additive reduces construction cost and time.


2013 ◽  
Vol 791-793 ◽  
pp. 323-325
Author(s):  
Xiao Chu Wang ◽  
Hong Bin Nie ◽  
Jian Peng Zhang

CFRP cloth strengthening concrete column is divided into constrained and unconstrained District area by the reasonable arch axis theory, then we obtain the effective confinement factor of reinforced columns, base on lateral stress formula of scholar XIAO Y and concrete compressive strength model of Karbhari, V. M, derive from the increasing coefficient of carrying capacity, according to the effective confinement factor and the increasing coefficient of carrying capacity, finally we obtain the bearing capacity formula of the modified compression column strengthened with CFRP sheets.


2021 ◽  
Author(s):  
Tadesse Gemeda Wakjira ◽  
M. Shahria Alam ◽  
Usama Ebead

Abstract Concrete bridge piers reinforced with conventional steel bars experience large permanent (residual) deformation that may lead to uneconomical repair or demotion of bridges due to their non-functionality post strong seismic event. Thus, sufficiently ductile materials are required to reinforce concrete bridge piers in the plastic hinge zone in order to limit their permanent damage and deformation post-earthquake event. Previous studies showed that partial replacement of conventional steel reinforcement bars with superelastic shape memory alloy (SMA) bars in the plastic hinge zone of concrete bridge piers has the capacity to limit the residual deformation owing to the superior self-centering properties of SMA bars. In this study, the efficacy of hybrid SMA/steel reinforcement for hollow section concrete bridge piers under combined reverse cyclic and constant axial loading is numerically investigated for the first time. The responses of the piers were evaluated in terms of different performance indices including hysteretic characteristics, residual deformation, energy dissipation capacity, and self-centering capacity. A sensitivity analysis was used to explore the main effects of key design parameters and their interactions on each performance index at four damage states, namely, complete, extensive, moderate, and slight damage states. The results of this study demonstrate the effectiveness of hybrid SMA/steel reinforcement for enhancing the seismic behavior of hollow section concrete bridge piers.


2018 ◽  
Vol 9 (2) ◽  
pp. 67-73
Author(s):  
M Zainul Arifin

This research was conducted to determine the value of the highest compressive strength from the ratio of normal concrete to normal concrete plus additive types of Sika Cim with a composition variation of 0.25%, 0.50%, 0.75%, 1.00%, 1.25%, 1 , 50% and 1.75% of the weight of cement besides that in this study also aims to find the highest tensile strength from the ratio of normal concrete to normal concrete in the mixture of sika cim composition at the highest compressive strength above and after that added fiber wire with a size diameter of 1 mm in length 100 mm with a ratio of 1% of material weight. The concrete mix plan was calculated using the ASTM method, the matrial composition of the normal concrete mixture as follows, 314 kg / m3 cement, 789 kg / m3 sand, 1125 kg / m3 gravel and 189 liters / m3 of water at 10 cm slump, then normal concrete added variations of the composition of sika cim 0.25%, 0.50%, 0.75%, 1.00%, 1.25%, 1.5%, 1.75% by weight of cement and fiber, the tests carried out were compressive strength of concrete and tensile strength of concrete, normal maintenance is soaked in fresh water for 28 days at 30oC. From the test results it was found that the normal concrete compressive strength at the age of 28 days was fc1 30 Mpa, the variation in the addition of the sika cim additive type mineral was achieved in composition 0.75% of the cement weight of fc1 40.2 Mpa 30C. Besides that the tensile strength test results were 28 days old with the addition of 1% fiber wire mineral to the weight of the material at a curing temperature of 30oC of 7.5%.


2013 ◽  
Vol 12 (3) ◽  
Author(s):  
Sudarmadi Sudarmadi

In this paper a case study about concrete strength assessment of bridge structure experiencing fire is discussed. Assessment methods include activities of visual inspection, concrete testing by Hammer Test, Ultrasonic Pulse Velocity Test, and Core Test. Then, test results are compared with the requirement of RSNI T-12-2004. Test results show that surface concrete at the location of fire deteriorates so that its quality is decreased into the category of Very Poor with ultrasonic pulse velocity ranges between 1,14 – 1,74 km/s. From test results also it can be known that concrete compressive strength of inner part of bridge pier ranges about 267 – 274 kg/cm2 and concrete compressive strength of beam and plate experiencing fire directly is about 173 kg/cm2 and 159 kg/cm2. It can be concluded that surface concrete strength at the location of fire does not meet the requirement of RSNI T-12-2004. So, repair on surface concrete of pier, beam, and plate at the location of fire is required.


2020 ◽  
pp. 136943322098166
Author(s):  
Shuhao Yin ◽  
Bin Rong ◽  
Lei Wang ◽  
Yiliang Sun ◽  
Wuchen Zhang ◽  
...  

This paper studies the shear performance of the connection with the external stiffening ring between the square steel tubular column and unequal-depth steel beams. Two specimens of interior column connections were tested under low cyclic loading. The deformation characteristics and failure modes exhibited by the test phenomena can be summarized as: (1) two specimens all exhibited shear deformation in steel tube web of the panel zone and (2) weld fracture in the panel zone and plastic hinge failure at beam end were observed. Besides, load-displacement behaviors and strain distributions have been also discussed. The nonlinear finite element models were developed to verify the test results. Comparative analyses of the bearing capacity, failure mode, and load-paths between the equal-depth and unequal-depth beam models have been carried out.


2021 ◽  
Vol 11 (9) ◽  
pp. 3866
Author(s):  
Jun-Ryeol Park ◽  
Hye-Jin Lee ◽  
Keun-Hyeok Yang ◽  
Jung-Keun Kook ◽  
Sanghee Kim

This study aims to predict the compressive strength of concrete using a machine-learning algorithm with linear regression analysis and to evaluate its accuracy. The open-source software library TensorFlow was used to develop the machine-learning algorithm. In the machine-earning algorithm, a total of seven variables were set: water, cement, fly ash, blast furnace slag, sand, coarse aggregate, and coarse aggregate size. A total of 4297 concrete mixtures with measured compressive strengths were employed to train and testing the machine-learning algorithm. Of these, 70% were used for training, and 30% were utilized for verification. For verification, the research was conducted by classifying the mixtures into three cases: the case where the machine-learning algorithm was trained using all the data (Case-1), the case where the machine-learning algorithm was trained while maintaining the same number of training dataset for each strength range (Case-2), and the case where the machine-learning algorithm was trained after making the subcase of each strength range (Case-3). The results indicated that the error percentages of Case-1 and Case-2 did not differ significantly. The error percentage of Case-3 was far smaller than those of Case-1 and Case-2. Therefore, it was concluded that the range of training dataset of the concrete compressive strength is as important as the amount of training dataset for accurately predicting the concrete compressive strength using the machine-learning algorithm.


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