A series of laboratory model tests has been carried out to investigate the using of pomegranate sticks mat as reinforcement to increase the bearing capacity of footing on loose sand. The influence of depth and length of pomegranate sticks layer was examined. In the present research single layer of pomegranate sticks reinforcement was used to strengthen the loose sand stratum beneath the strip footing. The dimensions of the used foundation were 4*20 cm. The reinforcement layer has been embedded at depth 2, 4 and 8 cm under surcharge stresses . Reinforcing layer with length of 8 and 16 cm were used. The final model test results indicated that the inclusion of pomegranate sticks reinforcement is very effective in improvement the loading cap

When the flange of a reinforced concrete spandrel beam is in tension, current design codes and specifications enable a portion of the bonded flexure tension reinforcement to be distributed over an effective flange width. The flexural behavior of the RC L-shaped spandrel beam when reinforcement is laterally displaced in the tension flange is investigated experimentally and numerically in this work. Numerical analysis utilizing the finite element method is performed on discretized flanged beam models validated using experimentally verified L-shaped beam specimens to achieve study objectives. A parametric study was carried out to evaluate the influence of various factors on the beam’s flexure behavior. Results showed that

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

Biodegradable polymers have garnered increasing attention as eco-friendly alternatives to conventional petroleum-derived plastics, which pose a global environmental challenge due to their difficult recycling and slow degradation. This study focuses on the preliminary evaluation of surface functional properties of chitosan films reinforced with TiO₂ or ZnO nanoparticles (NPs). These films were prepared at different loading ratios using the solution-casting method. Structural and morphological properties were characterized using FTIR and FESEM, while functional properties were evaluated by surface wettability, UV–Vis spectroscopy, thermogravimetric analysis and antibacterial activity testing. FTIR results showed significant changes in abs

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 current work is concerned with preparing cobalt manganese ferrite (Co1-xMnxFe2O4) with different concentrations of cobalt and manganese (x=0.2, 0.4, and 0.6) and decorating it with polyaniline (PAni) for use in supercapacitive applications. The results of the X-ray diffraction (XRD) manifested a broad peak of PAni and a cubic structure of cobalt manganese ferrite having crystal size between 60 nm and 138 nm, which decreases with increasing concentration of Mn. The field emission scanning electron microscopy (FESEM) images evidenced that the PAni has nanofiber (NF) structures, according to the method of preparation, where the hydrothermal method was used. The magnetic properties of the prepared ferrite, as well as the prepared PAni/Co1-x

PVA:PEG/MnCl2 composites have been prepared by adding (MnCl2) to the mixture of the poly vinyl alcohol (PVA) and poly ethylene glycol (PEG) with different weight percentages (0, 2, 4, 6, 8 and 10) wt.% by using casting method. The type of charge carriers, concentration (nH) and Hall mobility (μH) have been estimated from Hall measurements and show that the films of all concentration have a negative Hall coefficient. In D.C measurement increase temperature leads to decrease the electrical resistance. The D.C conductivity of the composites increases with the increasing of the concentration of additive particles and temperature. The activation energy decreases for all composites with increasing the concentration of the additive particles.

The Dielectric properties of EP/TiO2 and MgO nanocomposite at
a frequency range of (102-106 Hz) were studied. The composite were
prepared with the state volume ratio (0, 0.05, 0.1) for EP/TiO2 and
MgO respectively. The impedance, dielectric constant and dielectric
loss were found decrease with frequency increase.

Several correlations have been proposed for bubble point pressure, however, the correlations could not predict bubble point pressure accurately over the wide range of operating conditions. This study presents Artificial Neural Network (ANN) model for predicting the bubble point pressure especially for oil fields in Iraq. The most affecting parameters were used as the input layer to the network. Those were reservoir temperature, oil gravity, solution gas-oil ratio and gas relative density. The model was developed using 104 real data points collected from Iraqi reservoirs. The data was divided into two groups: the first was used to train the ANN model, and the second was used to test the model to evaluate their accuracy and trend stability