This paper presents a nonlinear finite element modeling and analysis of steel fiber reinforced concrete (SFRC) deep beams with and without openings in web subjected to two- point loading. In this study, the beams were modeled using ANSYS nonlinear finite element
software. The percentage of steel fiber was varied from 0 to 1.0%.The influence of fiber content in the concrete deep beams has been studied by measuring the deflection of the deep beams at mid- span and marking the cracking patterns, compute the failure loads for each deep beam, and also study the shearing and first principal stresses for the deep beams with and without openings and with different steel fiber ratios. The above study indicates that the location of openings and the amount steel fiber are affects to the behavior and strength of deep beams. And also when the results of the experiments taken from the literature were compared with the results obtained from the beam modeled with ANSYS finite element program, it was shown that the results of computer model gave similar results to the experimental behavior.
Test results of nine reinforced concrete one way slab with and without lacing reinforcement are reported. The tests were designed to study the effect of the lacing reinforcement on the flexural response of one way slabs. The test parameters were considered is the lacing steel ratios of (0, 0.0025, 0.0045, and 0.0065), flexural steel ratios of (0.0025, 0.0045, and 0.0065) and span to the effective depth ratios of (11, 13, and 16). Two specimens had no lacing reinforcement and the remaining seven specimens had the lacing reinforcement. Four point bending test were carried out, one of the specimens was tested under the static load applied gradually up to failure and the other specimens were tested under repeated load (5 cyc
... Show MoreExperimental research was carried out to investigate the performance of CFRP wrapping jackets used for retrofitting twelve square reinforced concrete (CR) column specimens damaged by exposure to fire flame, at different temperatures of 300, 500 and 700ºC, except for two specimens that were not burned. The specimens were then loaded axially till failure after gradual or sudden cooling. The specimens were divided into two groups containing two main reinforcement ratios, ρ= 0.0314 and ρ= 0.0542. This was followed by the retrofitting procedure that included wrapping all the specimens with two layers of CFRP fabric sheets. The test results of the retrofitted specimens showed that the fire damaged RC
... Show MoreThis paper presents theoretical parametric study of the curvature ductility capacity for reinforced concrete column sections. The study considers the behavior of concrete and reinforcing steel under different strain rates. A computer program has been written to compute the curvature ductility taking into account the spalling in concrete cover. Strain rate sensitive constitutive models of steel and concrete were used for predicting the moment-curvature relationship of reinforced concrete columns at different rate of straining. The study parameters are the yield strength of main reinforcement, yield strength of transverse reinforcement, compressive strength of concrete, spacing of ties and the axial load. The results indicated that hi
... Show MoreThis investigation deals with the use of orange peel (OP) waste as adsorbent for removal of nitrate (NO3) from simulated wastewater. Orange peel prepared in two conditions dried at 60C° (OPD) and burning at 500 °C (OPB). The effect of pH: 2-10, contact time: 30- 180 min, sorbent weight: 0.5- 3.0 g were considered. The optimal pH value for NO3 adsorption was found to be 2.0 for both adsorbents. The equilibrium data were analyzed using Langmuir and Freundlich isotherm models. Freundlich model was found to fit the equilibrium data very well with high-correlation coefficient (R2). The adsorption kinetics was found to follow pseudo-second-order rate kinetic model, with a good correlation (R2
... Show MoreThis paper presents a study to investigate the behavior of post-tensioned segmental concrete beams that exposed to high-temperature. The experimental program included fabricating and testing twelve simply supported beams that divided into three groups depending on the number of precasting concrete segments. All specimens were prepared with an identical length of 3150 mm and differed in the number of the incorporated segments of the beam (9, 7, or 5 segments). To simulate the genuine fire disasters, nine out of twelve beams were exposed to a high-temperature flame for one hour. Based on the standard fire curve (ASTM – E119), the temperatures of 300◦C (572◦F), 500◦C (932◦F), and 700◦C (1292◦F) were adopted. Consequently,
... Show MoreThis paper presents a study to investigate the behavior of post-tensioned segmental concrete beams that exposed to high-temperature. The experimental program included fabricating and testing twelve simply supported beams that divided into three groups depending on the number of precasting concrete segments. All specimens were prepared with an identical length of 3150 mm and differed in the number of the incorporated segments of the beam (9, 7, or 5 segments). To simulate the genuine fire disasters, nine out of twelve beams were exposed to a high-temperature flame for one hour. Based on the standard fire curve (ASTM – E119), the temperatures of 300◦C (572◦F), 500◦C (932◦F), and 700◦C (1292◦F) were adopted. Consequently,
... Show MoreThe proliferation of many editing programs based on artificial intelligence techniques has contributed to the emergence of deepfake technology. Deepfakes are committed to fabricating and falsifying facts by making a person do actions or say words that he never did or said. So that developing an algorithm for deepfakes detection is very important to discriminate real from fake media. Convolutional neural networks (CNNs) are among the most complex classifiers, but choosing the nature of the data fed to these networks is extremely important. For this reason, we capture fine texture details of input data frames using 16 Gabor filters indifferent directions and then feed them to a binary CNN classifier instead of using the red-green-blue
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