To accommodate utilities in buildings, different sizes of openings are provided in the web of reinforced concrete deep beams, which cause reductions in the beam strength and stiffness. This paper aims to investigate experimentally and numerically the effectiveness of using carbon fiber reinforced polymer (CFRP) strips, as a strengthening technique, to externally strengthen reinforced concrete continuous deep beams (RCCDBs) with large openings. The experimental work included testing three RCCDBs under five-point bending. A reference specimen was prepared without openings to explore the reductions in strength and stiffness after providing large openings. Openings were created symmetrically at the center of spans of the other specimens to represent 40% of the overall beam depth. Moreover, finite elements (FE) analysis was validated using the experimental results to conduct a parametric study on RCCDBs strengthened with CFRP strips. The results confirmed reductions in the ultimate load by 21% and 7% for the un-strengthened and strengthened specimens, respectively, due to the large openings. Although the large openings caused reductions in capacities, the CFRP strips limited the deterioration by enhancing the specimen capacity by 17% relative to the un-strengthened one.
Reactive Powder Concrete (RPC) can be incorporate as a one of the most important and progressive concrete technology. It is a special type of ultra-high strength concrete (UHSC) that’s exclude the coarse aggregate from its constitutive materials. In this research an experimental study had been carried out to investigate the effect of using three types of materials (porcelain aggregate) and others sustainable materials (glass waste and granular activated carbon) as a partial replacement of fine aggregate. Four percentages had considered (0, 10, 15 and 20) % to achieve better understanding for the influence of these materials upon the compressive strength of RPC. Four curing ages had included in this study, these are; 7, 28, 60 and
... Show MoreReactive Powder Concrete (RPC) can be incorporate as a one of the most important and progressive concrete technology. It is a special type of ultra-high strength concrete (UHSC) that’s exclude the coarse aggregate from its constitutive materials. In this research an experimental study had been carried out to investigate the effect of using three types of materials (porcelain aggregate) and others sustainable materials (glass waste and granular activated carbon) as a partial replacement of fine aggregate. Four percentages had considered (0, 10, 15 and 20) % to achieve better understanding for the influence of these materials upon the compressive strength of RPC. Four curing ages had included in this study, these are; 7, 28, 60 and
... Show MoreRoller compacted concrete (RCC) is a special type of concrete with zero or even negative slump consistency. In this work, it had aimed to produce an RCC mix suitable for roads paving with minimum cost and better engineering properties so, different RCC mixes had prepared i.e. (M1, M2, M3, and M4) using specified percentages of micro natural silica sand powder (SSP) as partial replacement of (0%, 5%, 10%, and 20%) by weight of sulfate resistant Portland cement. Additionally, M-sand, crushed stone, filler, and water had been used. The results had obtained after 28 days of water curing. The control mix (M1) had satisfied the required
The utilization of recycled brick tile powder as a replacement for conventional filler in the asphalt concrete mix has been studied in this research. This research evaluates the effectiveness of recycled brick tile powder and determines its optimum replacement level. Using recycled brick tile powder is significant from an environmental standpoint as it is a waste product from construction activities. Sixteen asphalt concrete samples were produced, and eight were soaked for a day. Samples contained 5% Bitumen, 2% to 5% brick tile powder, and conventional stone dust filler. The properties of samples were evaluated using the Marshall test. It was observed that the resistance to stiffness and deformation of asphalt concrete
... Show MoreHand-lay up method was used to prepare the samples made of epoxy (EP) as a matrix reinforced with chopped carbon fibers (CCF). The fatigue behavior of epoxy resin /chopped carbon fiber composites was studied with different weight percentage of chopped carbon fibers (2.5%,5%,7.5%,10%,12.5%). The fatigue test was carried out under alternate bending method, which was made by applying sinusoidal wave with constant displacement (15mm), stress ratio R=-1,and loading frequency 10Hz, which is believed to give a negligible temperature rise during the test. The results of the maximum stress, fatigue strength, fatigue limit and fatigue life of the tested composites are calculated from stress(S)-number of cycles(N) (S-N) curves.
It was shown that
Overlapped have been prepared from epoxy resin material added to carbon Nanotube and percentages weight (0.1, 0.05, 0.01) % Studied the mechanical properties of the composite (bending, tensile an d hardness) has been found that the Flexural and tensile modulus of the composites were higher than the pure epoxy resin this may be due to the high mechanical strength of carbon nano tube (CNT). The hardness of the epoxy carbon Nanotube composites increased and the reason is due to increased overlap and stacking between the additives and material basis, which reduces the movement of polymer molecules leading to increased resistance to scratching material and cutting, will become more resistance to plastic deformation.
The convolutional neural networks (CNN) are among the most utilized neural networks in various applications, including deep learning. In recent years, the continuing extension of CNN into increasingly complicated domains has made its training process more difficult. Thus, researchers adopted optimized hybrid algorithms to address this problem. In this work, a novel chaotic black hole algorithm-based approach was created for the training of CNN to optimize its performance via avoidance of entrapment in the local minima. The logistic chaotic map was used to initialize the population instead of using the uniform distribution. The proposed training algorithm was developed based on a specific benchmark problem for optical character recog
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