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Strength compensation of deep beams with large web openings using carbon fiber–reinforced polymer sheets
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This article presents the results of an experimental investigation of using carbon fiber–reinforced polymer sheets to enhance the behavior of reinforced concrete deep beams with large web openings in shear spans. A set of 18 specimens were fabricated and tested up to a failure to evaluate the structural performance in terms of cracking, deformation, and load-carrying capacity. All tested specimens were with 1500-mm length, 500-mm cross-sectional deep, and 150-mm wide. Parameters that studied were opening size, opening location, and the strengthening factor. Two deep beams were implemented as control specimens without opening and without strengthening. Eight deep beams were fabricated with openings but without strengthening, while the other eight deep beams were with openings in shear spans and with carbon fiber–reinforced polymer sheet strengthening around opening zones. The opening size was adopted to be 200 × 200 mm dimensions in eight deep beams, while it was considered to be 230 × 230 mm dimensions in the other eight specimens. In eight specimens the opening was located at the center of the shear span, while in the other eight beams the opening was attached to the interior edge of the shear span. Carbon fiber–reinforced polymer sheets were installed around openings to compensate for the cutout area of concrete. Results gained from the experimental test showed that the creation of openings in shear spans affect the load-carrying capacity, where the reduction of the failure load for specimens with the opening but without strengthening may attain 66% compared to deep beams without openings. On the other hand, the strengthening by carbon fiber–reinforced polymer sheets for beams with openings increased the failure load by 20%–47% compared with the identical deep beam without strengthening. A significant contribution of carbon fiber–reinforced polymer sheets in restricting the deformability of deep beams was observed.

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Publication Date
Fri Dec 01 2023
Journal Name
Baghdad Science Journal
Nano composites of PAM Reinforced with Al2O3
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         The aim of this investigation is to determine how different weight percentages of alumina nanoparticles, including 0.02, 0.04, and 0.06 percent wt, affect the physical characteristics of Poly Acrylamide (PAAM). Using a hot plate magnetic stirrer, 10 g of poly acrylamide powder was dissolved in 90 g of di-ionized distillate water for 4 hours to produce PAAM with a concentration of 0.11 g/ml. Four sections of the resulting solution, each with a volume of 20 ml, were created. Each solution was added independently with alumina nanoparticles in different ratios 0.0, 0.02, 0.04, and 0.06 to create four nano fluid solutions with different alumina nanoparticle contents based on each weight percent. The hand casting process for n

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Publication Date
Fri Jan 01 2021
Journal Name
Aip Conf. Proc.
Preparation of nanostructured MnO2/carbon fiber composite electrode for removal of Cu2+ ions from aqueous solution by electrosorption process
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The nanostructured Manganese dioxide/Carbon fiber (CF) composite electrode was prepared galvanostatically using a facile method of anodic electrodeposition by varying the reaction time and MnSO4 concentration of the electrochemical solution. The effects of these parameters on the structures and properties of the prepared electrode were evaluated. For determining the crystal characteristics, morphologies, and topographies of the deposited MnO2 films onto the surfaces of carbon fibers, the X-ray diffraction (XRD), field emission scanning electron microscopy (FESEM), and atomic force microscopy (AFM) techniques were used, respectively. It found that the carbon fibers were coated with γ-MnO2 with a density that increased with increasing the de

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Publication Date
Sun Nov 01 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
3D scenes semantic segmentation using deep learning based Survey
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Abstract<p>Semantic segmentation realization and understanding is a stringent task not just for computer vision but also in the researches of the sciences of earth, semantic segmentation decompose compound architectures in one elements, the most mutual object in a civil outside or inside senses must classified then reinforced with information meaning of all object, it’s a method for labeling and clustering point cloud automatically. Three dimensions natural scenes classification need a point cloud dataset to representation data format as input, many challenge appeared with working of 3d data like: little number, resolution and accurate of three Dimensional dataset . Deep learning now is the po</p> ... Show More
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Publication Date
Mon Jan 01 2024
Journal Name
Computers, Materials &amp; Continua
Credit Card Fraud Detection Using Improved Deep Learning Models
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Publication Date
Mon Jan 09 2023
Journal Name
2023 15th International Conference On Developments In Esystems Engineering (dese)
Deep Learning-Based Speech Enhancement Algorithm Using Charlier Transform
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Publication Date
Thu Nov 01 2018
Journal Name
Optical Fiber Technology
Enhancing refractive index sensitivity using micro-tapered long-period fiber grating inscribed in biconical tapered fiber
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Publication Date
Tue Jun 01 2021
Journal Name
2021 Ieee/cvf Conference On Computer Vision And Pattern Recognition Workshops (cvprw)
Alps: Adaptive Quantization of Deep Neural Networks with GeneraLized PositS
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Publication Date
Sun Jun 01 2014
Journal Name
Baghdad Science Journal
Preparation of polymer thin film using as NH3 gas Sensor
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Polyaniline organic Semiconductor polymer thin films have been prepared by oxidative polymerization at room temperature, this polymer was deposited on glass substrate with thickness 900nm, FTIR spectra was tested , the structural,optical and electrical properties were studied through XRD ,UV-Vis ,IR measurements ,the results was appeared that polymer thin film sensing to NH3 gas.

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Publication Date
Wed Dec 31 2014
Journal Name
Al-khwarizmi Engineering Journal
Catalytic Cracking of Iraqi Vacuum Gasoil Using Large and Medium Pore Size of Zeolite Catalysts
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Abstract 

The catalytic cracking conversion of Iraqi vacuum gas oil was studied on large and medium pore size (HY, HX, ZSM-22 and ZSM-11) of zeolite catalysts. These catalysts were prepared locally and used in the present work. The catalytic conversion performed on a continuous fixed-bed laboratory reaction unit. Experiments were performed in the temperature range of 673 to 823K, pressure range of 3 to 15bar, and LHSV range of 0.5-3h-1. The results show that the catalytic conversion of vacuum gas oil increases with increase in reaction temperature and decreases with increase in LHSV. The catalytic activity for the proposed catalysts arranged in the following order:

HY>H

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Publication Date
Wed Dec 01 2021
Journal Name
Case Studies In Construction Materials
CFRP strengthening efficiency on enhancement punching shear resistance of RC bubbled slabs with openings
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