This study reveals the results of a numerical simulation performed using the ABAQUS/CAE finite element program. The study aimed to provide a simulation model that can forecast the shear behavior of reinforced concrete beams confined with reinforcing meshes. Limited numerical studies have been conducted using geogrid or FRP mesh as shear reinforcement, with limited representation accuracy and limited material quality. The results were compared to published experimental findings in the literature. The finding of the finite element model and the experimental results were highly comparable; consequently, the model was determined to be valid. Following this, the domain of numerical analyses was broadened to include the investigation of m

Abstract

Stainless steel (AISI 304) has good electrical and thermal conductivities, good corrosion resistance at ambient temperature, apart from these it is cheap and abundantly available; but has good mechanical properties such as hardness. To improve the  hardness and corrosion resistance of stainless steel its surface can be modified by developing nanocomposite coatings applied on its surface. The main objective of this paper is to study effect of electroco-deposition method on microhardness and corrosion resistance of stainless steel, and to analyze effect of nanoparticles (Al₂O₃, ZrO₂ , and SiC)  on properties of composite coatings. I

Learn new methods of teaching mathematics contribute to raising the level of pupils to acquire mathematical concepts primary stage
Attempt advancement in the level of mathematics teaching for the better through the use of modern teaching strategies. The research aims at the progress in the acquisition of mathematical concepts schoolgirls after subjecting the fourth grade to teach in active learning strategies, the number of research sample (60) schoolgirl, by (30) schoolgirl experimental group and 30 pupils of the control group. Clear from the results shown the presence of a statistically significant difference between the acquisition of concepts of schoolgirls two groups (experimental and control) for the benefit of pupils of the exp

The present study designed to determine the ethanolic extract of Cyperus rotundus on Liver in Albino Male Mice . In the present study 18 Male mice were used they divided into six groups ( 1st group consedered control group , 2nd group injected by 250 mg/ml from extract , 3th group injected by 300 mg/ml from extract , 4th group injected by 350 mg/ml from extract , 5th group injected by 400 mg/ml from extract and the 6th group injected by 450 mg/ml from extract ) . the expermint lasted for two days and the doses gived by intraperitonial injection . showed from the study results that ethanolic extract for Cyperus rotundus have negative effect on Liver tissue in 250 , 300 , 350 mg/ml concentrations when comparsion with control group . the re

Despite the significant increase in public spending in Iraq, it was not directed toward the important sectors that have an important role in correcting the productive structure. Rather, most of the public expenditure was going to cover the required imports, or to face shocks, whether security or health, and this caused a continuous decrease in the volume of Iraq's exports of goods and services, as the aim of the study was to review the importance of public debt and its impact on the trade balance, as well as to know the economic policies that can contribute to strengthening the trade balance, as the study proved through the (ARDL) model that there is a direct relationship between the domestic debt and the net trade balance, and an invers

This paper presents seven modified Adomian Decomposition Method (ADM) techniques for efficiently solving initial value problems, especially those involving non-homogeneous and nonlinear differential equations. While the classical ADM is effective for linear homogeneous cases, it has difficulties solving more complex problems. The proposed modifications—from MADM1 to MLADM—include Maclaurin and Taylor expansions, Laplace transforms, and single-step iterations.• These modifications enhance convergence, reduce complexity, and improve accuracy.• Each method offers specific advantages, such as accelerating convergence (MADM2, RADM4), simplifying computation (TSADM5), and achieving higher accuracy (MLADM).• Numerical examples confirm th

The effect of different doping ratio (0.3, 0.5, and 0.7) with thickness in the range 300nmand annealed at different temp.(Ta=RT, 473, 573, 673) K on the electrical conductivity and hall effect measurements of AgInTe2thin film have and been investigated AgAlxIn(1-x) Te2 (AAIT) at RT, using thermal evaporation technique all the films were prepared on glass substrates from the alloy of the compound. Electrical conductivity (σ), the activation energies (Ea1, Ea2), Hall mobility and the carrier concentration are investigated as a function of doping. All films consist of two types of transport mechanisms for free carriers. The activation energy (Ea) decreased whereas electrical conductivity increases with increased doping. Results of Hall Effect

a porentioncsisteve has been carried out of the corrosion behavior of inconel(600) in chloride ions (Cl) over the tempreatures 293 over the temperatures 308K in both the dcacrated and the alloy

In this paper, a design of the broadband thin metamaterial absorber (MMA) is presented. Compared with the previously reported metamaterial absorbers, the proposed structure provides a wide bandwidth with a compatible overall size. The designed absorber consists of a combination of octagon disk and split octagon resonator to provide a wide bandwidth over the Ku and K bands' frequency range. Cheap FR-4 material is chosen to be a substate of the proposed absorber with 1.6 thicknesses and 6.5×6.5 overall unit cell size. CST Studio Suite was used for the simulation of the proposed absorber. The proposed absorber provides a wide absorption bandwidth of 14.4 GHz over a frequency range of 12.8-27.5 GHz with more than %90 absorp

Wildfire risk has globally increased during the past few years due to several factors. An efficient and fast response to wildfires is extremely important to reduce the damaging effect on humans and wildlife. This work introduces a methodology for designing an efficient machine learning system to detect wildfires using satellite imagery. A convolutional neural network (CNN) model is optimized to reduce the required computational resources. Due to the limitations of images containing fire and seasonal variations, an image augmentation process is used to develop adequate training samples for the change in the forest’s visual features and the seasonal wind direction at the study area during the fire season. The selected CNN model (Mob