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Sectional and Stress Analysis of Hybrid Reinforced Concrete Beams with Embedded GFRP Profiles Under Monotonic Static Loading
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Glass fiber–reinforced polymer (GFRP) reinforcement provides an effective alternative to conventional steel in concrete structures due to its corrosion resistance. Nevertheless, the lower elastic modulus of GFRP necessitates careful consideration of serviceability behavior in GFRP-reinforced concrete members. This study presents a numerical sectional analysis model for predicting the flexural response and ultimate capacity of hybrid reinforced concrete beams incorporating embedded GFRP profiles in combination with either mild steel or GFRP reinforcement bars under monotonic static loading. The proposed model employs realistic nonlinear stress–strain relationships for concrete and steel, together with secant moduli of elasticity evaluated at different loading stages. Particular emphasis is placed on detailed stress distribution in flexural sections, including the contribution of tension stiffening in the post-cracking regime. The formulation integrates nonlinear constitutive material behavior with theoretical sectional equilibrium to evaluate the effective flexural secant stiffness. For practical serviceability assessment and to reduce dependence on complex analytical procedures, strain vectors and stiffness matrix components are derived using elasticity coefficients that reflect modulus degradation obtained from numerical analysis. The accuracy of the model is verified through comparison with experimental results, including ultimate flexural capacity and moment–deflection responses. Many crucial parameters were studied, such as the longitudinal reinforcement ratio, type of reinforcement, concrete compressive strength, position of the I-GFRP profile, and rotation of the I-GFRP profile. The results of this study demonstrated that both the longitudinal reinforcement ratio and the rotation of the I-GFRP profile have a significant influence on the ultimate load capacity and deflection behavior. The close agreement between numerical predictions and experimental observations demonstrates the reliability and applicability of the proposed model for structural engineering analysis and design.

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Publication Date
Wed Sep 01 2021
Journal Name
Computers And Concrete
Improving the seismic performance of reinforced concrete frames using an innovative metallic-shear damper
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Scopus (14)
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Publication Date
Tue Mar 30 2021
Journal Name
Journal Of Economics And Administrative Sciences
Detailed feasibility study of the pre-cast reinforced concrete project and its importance in the construction of Iraq
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Purpose:  Providing practical knowledge of the requirements of a detailed feasibility study for selecting the investment project.

Findings:  Directing the private sector towards investing in productive projects - the pre-cast reinforced concrete project - as it achieves a financial return as well as providing Providing foreign currencies by reducing imports and exploiting available natural resources

Practical implications: The importance of a detailed feasibility study to determining whether the project can be implemented or not.

The precast concrete method is one of the best modern c

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Publication Date
Mon May 01 2017
Journal Name
Energy Procedia
A Coupled Model of the Linear Joule Engine with Embedded Tubular Permanent Magnet Linear Alternator
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Publication Date
Tue Apr 02 2024
Journal Name
Engineering, Technology & Applied Science Research
Effect of Fire Exposure on the Properties of Self-Compacting Concrete reinforced by Glass Fibers
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The optimal design of any structural elements requires examining all environmental risks, emergency accidents, and standard load cases. Exposure to fire is one of the most common safety threats. Nowadays wide developments are achieved in the field of concrete technology, therefore, experimental and theoretical investigations should be performed on the characteristics of such developed materials under different loading conditions. This study investigates the impact of fire exposure on the mechanical characteristics of self-compacting concrete, specifically compressive and tensile strength, modulus of elasticity, and stress-strain relation. The adopted fire exposure consisted of six steady-state temperatures (300, 400, 500, 600, 700,

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Publication Date
Tue Sep 24 2019
Journal Name
Journal Of Engineering
Effect of Use Recycled Coarse Aggregate on the Behavior of Axially Loaded Reinforced Concrete Columns
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Nowadays, the use of recycled waste construction materials instead of aggregates is becoming popular in construction owing to its environmental benefits. This paper presents an experimental and analytical campaign to study the behavior of axially loaded columns constructed from recycled aggregates. The latter was used instead of natural aggregates, and they were collected from the waste of previous concrete constructions. Different concrete mixtures made from varying amounts of recycled aggregates ranged from 0 to 50% of the total coarse aggregate were conducted to achieve 28 MPa. The effect of steel fibers is another investigated variable with volumes ranged from 0 to 2% concerning concrete’s mixture. The experimental

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Publication Date
Mon Jun 05 2023
Journal Name
Journal Of Engineering
Prediction of Compressive Strength of Reinforced Concrete Structural Elements by Using Combined Non-Destructive Tests
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This research is devoted to investigate relationship between both Ultrasonic Pulse Velocity and Rebound Number (Hammer Test) with cube compressive strength and also to study the effect of steel reinforcement on these relationships.
A study was carried out on 32 scale model reinforced concrete elements. Non destructive testing campaign (mainly ultrasonic and rebound hammer tests) made on the same elements. About 72 concrete cubes (15 X 15 X15) were taken from the concrete mixes to check the compressive strength.. Data analyzed.Include the possible correlations between non destructive testing (NDT) and compressive strength (DT) Statistical approach is used for this purpose. A new relationships obtained from correlations results is give

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Publication Date
Wed Jan 08 2020
Journal Name
Nursing & Health Sciences
Medication adherence and predictive factors in patients with cardiovascular disease: A cross‐sectional study
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Abstract<p>Adherence to cardiac medications makes a significant contribution to avoidance of morbidity and premature mortality in patients with cardiovascular disease. This quantitative study used cross‐sectional survey design to evaluate medication adherence and contributing factors among patients with cardiovascular disease, comparing patients who were admitted to a cardiac ward (<italic>n</italic> = 89) and those attending outpatient cardiac rehabilitation (<italic>n</italic> = 31) in Australia. Data collection was completed between October 2016 and December 2017. Descriptive and regression analyses were conducted to identify medication adherence and determine factors independently pred</p> ... Show More
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Publication Date
Sun Sep 25 2022
Journal Name
Lubricants
Development of Hybrid Intelligent Models for Prediction Machining Performance Measure in End Milling of Ti6Al4V Alloy with PVD Coated Tool under Dry Cutting Conditions
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Ti6Al4V alloy is widely used in aerospace and medical applications. It is classified as a difficult to machine material due to its low thermal conductivity and high chemical reactivity. In this study, hybrid intelligent models have been developed to predict surface roughness when end milling Ti6Al4V alloy with a Physical Vapor Deposition PVD coated tool under dry cutting conditions. Back propagation neural network (BPNN) has been hybridized with two heuristic optimization techniques, namely: gravitational search algorithm (GSA) and genetic algorithm (GA). Taguchi method was used with an L27 orthogonal array to generate 27 experiment runs. Design expert software was used to do analysis of variances (ANOVA). The experimental data were

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Publication Date
Sun Dec 01 2024
Journal Name
Nordic Concrete Research
Evaluating Concrete Strength Under Various Curing Conditions Using Artificial Neural Networks
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Abstract<p>This study examines the impact of different curing methods on the compressive strength of concrete. It investigates techniques such as air curing, periodic water spraying, full water submersion, and polyethylene encasement. Artificial neural network models were employed to evaluate the compressive strength under each curing condition. A model for calculating compressive strength that considers surrounding conditions was created using an artificial neural network. The current study’s figures were generated using this model. The research thoroughly examined the impact of curing environments and concrete mix components on strength properties, taking into account factors such as tempera</p> ... Show More
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Publication Date
Sat Sep 01 2018
Journal Name
Al-nahrain Journal For Engineering Sciences
Performance Analysis of FSO under Turbulent Channel Using OSTBC
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Free Space Optics (FSO) plays a vital role in modern wireless communications due to its advantages over fiber optics and RF techniques where a transmission of huge bandwidth and access to remote places become possible. The specific aim of this research is to analyze the Bit-Error Rate (BER) for FSO communication system when the signal is sent the over medium of turbulence channel, where the fading channel is described by the Gamma-Gamma model. The signal quality is improved by using Optical Space-Time Block- Code (OSTBC) and then the BER will be reduced. Optical 2×2 Alamouti scheme required 14 dB bit energy to noise ratio (Eb/N0) at 10-5 bit error rate (BER) which gives 3.5 dB gain as compared to no diversity scheme. Th

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