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The Experimental and Theoretical Effect of Fire on the Structural Behavior of Laced Reinforced Concrete Deep Beams
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A Laced Reinforced Concrete (LRC) structural element comprises continuously inclined shear reinforcement in the form of lacing that connects the longitudinal reinforcements on both faces of the structural element. This study conducted a theoretical investigation of LRC deep beams to predict their behavior after exposure to fire and high temperatures. Four simply supported reinforced concrete beams of 1500 mm, 200 mm, and 240 mm length, width, and depth, respectively, were considered. The specimens were identical in terms of compressive strength (  40 MPa) and steel reinforcement details. The same laced steel reinforcement ratio of 0.0035 was used. Three specimens were burned at variable durations and steady-state temperatures (one hour at 500 °C and 600 °C, and two hours at 500 °C). The flexural behavior of the simply supported deep beams, subjected to the two concentric loads in the middle third of the beam, was investigated with ABAQUS software. The results showed that the laced reinforcement with an inclination of 45˚ improved the structural behavior of the deep beams, and the lacing resisted failure and extended the life of the model. The optimal structural response was observed for the specimens. The laced reinforcement improved the failure mode and converted it from shear to flexure-shear failure. The parametric study showed that the lacing bars remarkably improved the strength of the deep beams and they were not affected more by the steady-state temperature and duration. Furthermore, a greater increase in load-carrying capacity was associated with an increase in the flexural diameter of approximately 12 and 16 mm by approximately 24.77% and 87.61%, respectively, compared to the reference LRC deep beams.

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Publication Date
Thu Jun 30 2011
Journal Name
Al-khwarizmi Engineering Journal
The Effect of the Solution Heat Treatment on the Mechanical Properties of Aluminum-Copper Alloy (2024-T3) Using Rolling Process
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The effect of solution heat treatment on the mechanical properties of Aluminum-Copper alloy. (2024-T3) by the rolling process is investigated. The solution heat treatment was implemented by heating the sheets to 480 C° and quenching them by water; then forming by rolling for many passes. And then natural aging is done for one month. Mechanical properties (tensile strength and hardness) are evaluated and the results are compared with the metal without treatment during the rolling process. ANSYS analysis is used to show the stresses distribution in the sheet during the rolling process.  It has been seen that good mechanical properties are evident in the alloy without heat treatment due to the strain hardening and also the mechanical

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Publication Date
Mon Sep 20 2021
Journal Name
Key Engineering Materials
Heat Treatment at Different Temperatures and its Effect on the Optical Properties of Pure PMMA and PMMA-Coumarin
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The effect of thermal treatment on optical constants of pure PMMA and with addition (15 and 35) ml of coumarin at different temperatures (100, 110 and 120) C0 for 1 hour were investigated. Cast method used to prepares films of pure PMMA and PMMA with (15 and 35) of coumarin. UV/VIS spectrometer technique used to measure the absorption spectra for these films. The optical constant (absorption spectra and absorption coefficient) don’t changes after applied temperatures in pure PMMA film but the optical constant (absorption spectra and absorption coefficient) in PMMA with (15 and 35) ml of coumarin increased with applied temperatures. The optical energy gap of pure PMMA and PMMA with (15 and 35) ml of coumarin sl

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Publication Date
Thu May 24 2018
Journal Name
Aip Conference Proceedings
The study effect of weight fraction on thermal and electrical conductivity for unsaturated polyester composite alone and hybrid
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In this research prepared two composite materials , the first prepared from unsaturated polyester resin (UP) , which is a matrix , and aluminum oxide (Al2O3) , and the second prepared from unsaturated polyester resin and aluminum oxide and copper oxide (CuO) , the two composites materials (Alone and Hybrid) of percentage weight (5,10,15)% . All samples were prepared by hand layup process, and study the electrical and thermal conductivity. The results showed decrease electrical conductivity from (10 - 2.39) ×10-15 for (Up+ Al2O3) and from (10 - 2.06)×10-15 for (Up+ Al2O3+ CuO) .But increase thermal conductivity from( 0.17 - 0.505) for (Up+ Al2O3) and from (0.17 - 0.489) for (Up+ Al2O3+ CuO).

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Publication Date
Sat Jul 01 2023
Journal Name
Iop Conference Series: Earth And Environmental Science
The Effect of Dry Farming and Water Stress under Subsurface Drip Irrigation System on Water and Rice Productivity
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Abstract<p>A field experiment was carried out during the 2020 season at the College of Agricultural Engineering/ University of Baghdad, Al-Jadriya to evaluate the effect of dry farming when applying water stress under the subsurface drip irrigation system on water productivity and rice yield. The experiment was conducted with three levels of irrigation water stress when 10, 20 and 40% of the available water was depleted and in three dimensions between drip lines 10, 15 and 20 cm. The experiment was designed according to a randomized complete block design, according to the split plot design, with three replications. Determine the depth of irrigation water depending on the moisture depletion of th</p> ... Show More
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Publication Date
Thu Jan 12 2023
Journal Name
Journal Of The Saudi Society Of Agricultural Sciences
Effect of planting density, foliar spraying and overlapping system on the growth and productivity using soilless culture system
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Publication Date
Fri Jan 01 2021
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
The effect of the dimensions of the strategic lens on achieving tax pioneer performance: Practical research in the General Authority for Taxes
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The aim of the research is to shed light on the dimensions of the strategic lens and its impact on achieving the pioneer tax performance and represented by the dimensions (strategic direction, growth, pilot indicator, renewal and modernization, efficiency and effectiveness) in the General Tax Authority. The questionnaire was adopted as a tool to collect data and information from the adult sample They are (91) who are on the site (Assistant Director General, Head of Division, First Division Deputy, Second Division Deputy, Division Officer, Division Officer Associate) The statistical program (SPSS) has been used to calculate (the mean, the standard deviation, the correlation coefficient, the difference coefficient, the F test, the

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Publication Date
Mon Jun 01 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
Improvement the corrosion Behavior of Titanium by Nanotubular Oxide in a simulated saliva solution
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Abstract<p>The corrosion behavior of Titanium in a simulated saliva solution was improved by Nanotubular Oxide via electrochemical anodizing treatment using three electrodes cell potentiostat at 37°C. The anodization treatment was achieved in a non-aqueous electrolyte with the following composition: 200mL ethylene glycol containing 0.6g NH4F and 10 ml of deionized water and using different applied directed voltage at 10°C and constant time of anodizing (15 min.). The anodized titanium layer was examined using SEM, and AFM technique.</p><p>The results showed that increasing applied voltage resulted in formation titanium oxide nanotubes with higher corrosion resistance </p> ... Show More
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Publication Date
Tue Jun 30 2020
Journal Name
Journal Of Economics And Administrative Sciences
The role of green strategy formulation in green behavior for municipal corporations – Analytical study
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The research shows the importance of orientation towards the formulation of the green strategy and its effect in determining the behavior of the green municipal institution in Babel governorate. The research highlighted the formulation of the green strategy as an important variable, especially today, the trend towards protecting the environment and minimizing the damage resulting from the delivery of services, and through it also the type of green behavior or performance adopted by the municipal institution and the emergence of the need for a strategy that is not harmful to the environment. The research took the sample intentionally comprehensive size of 222 personnel of municipal institutions and some formations concerned with t

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Publication Date
Tue Aug 10 2021
Journal Name
Design Engineering
Lossy Image Compression Using Hybrid Deep Learning Autoencoder Based On kmean Clusteri
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Image compression plays an important role in reducing the size and storage of data while increasing the speed of its transmission through the Internet significantly. Image compression is an important research topic for several decades and recently, with the great successes achieved by deep learning in many areas of image processing, especially image compression, and its use is increasing Gradually in the field of image compression. The deep learning neural network has also achieved great success in the field of processing and compressing various images of different sizes. In this paper, we present a structure for image compression based on the use of a Convolutional AutoEncoder (CAE) for deep learning, inspired by the diversity of human eye

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Publication Date
Wed Aug 30 2023
Journal Name
Baghdad Science Journal
Deep Learning-based Predictive Model of mRNA Vaccine Deterioration: An Analysis of the Stanford COVID-19 mRNA Vaccine Dataset
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The emergence of SARS-CoV-2, the virus responsible for the COVID-19 pandemic, has resulted in a global health crisis leading to widespread illness, death, and daily life disruptions. Having a vaccine for COVID-19 is crucial to controlling the spread of the virus which will help to end the pandemic and restore normalcy to society. Messenger RNA (mRNA) molecules vaccine has led the way as the swift vaccine candidate for COVID-19, but it faces key probable restrictions including spontaneous deterioration. To address mRNA degradation issues, Stanford University academics and the Eterna community sponsored a Kaggle competition.This study aims to build a deep learning (DL) model which will predict deterioration rates at each base of the mRNA

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