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Time Prediction of Dynamic Behavior of Glass Fiber Reinforced Polyester Composites Subjected to Fluctuating Varied Temperatures
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The reduction of vibration properties for composite material (woven roving E-glass fiber plies in thermosetting polyester matrix) is investigated at the prediction time under varied combined temperatures (60  to -15) using three types of boundary conditions like (CFCF, CCCF, and CFCC). The vibration properties are the amplitude, natural frequency, dynamic elastic moduli (young modulus in x, y directions and shear modulus in 1, 2 plane) and damping factor. The natural frequency of a system is a function of its elastic properties, dimensions, and mass. The woven roving glass fiber has been especially engineered for polymer reinforcement; but the unsaturated thermosetting polyester is widely used, offering a good balance of vibration properties at moderate or ambient temperatures, and also at relatively low cost. The mismatch between matrix and fiber yarns gives a predominant role for the fiber's mechanics where the matrix is the area where most damage mechanisms develop. The free vibration test was carried out for (5, 10, 15, 20, 25, 30) minutes. The composite plate was exposed to (75) of thermal gradient for ten times in various times at different stages. The results were classified into experimental and finite element using software ANSYS Ver. 9.    

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Publication Date
Thu Feb 01 2024
Journal Name
Journal Of Engineering
Rutting Prediction of Asphalt Mixtures Containing Treated and Untreated Recycled Concrete Aggregate
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Rutting is a crucial element of the mechanical performance characteristics of asphalt mixtures, which was the primary target of this study. The task involved substituting various portions of virgin coarse aggregate with recycled concrete aggregate materials that had been treated or left untreated at rates ranging from 25 to 100%, with a constant increase of 25%. The treatment process of recycled concrete aggregate involved soaking in acetic acid, followed by a mechanical process for a short time inside a Los Angeles machine without the balls. This research utilized two primary tests: the standard Marshall test to identify the optimal asphalt contents and the volumetric characteristics of asphalt mixtures. The other one w

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Publication Date
Sun Dec 30 2007
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Prediction of Fractional Hold-Up in RDC Column Using Artificial Neural Network
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In the literature, several correlations have been proposed for hold-up prediction in rotating disk contactor. However,
these correlations fail to predict hold-up over wide range of conditions. Based on a databank of around 611
measurements collected from the open literature, a correlation for hold up was derived using Artificial Neiral Network
(ANN) modeling. The dispersed phase hold up was found to be a function of six parameters: N, vc , vd , Dr , c d m / m ,
s . Statistical analysis showed that the proposed correlation has an Average Absolute Relative Error (AARE) of 6.52%
and Standard Deviation (SD) 9.21%. A comparison with selected correlations in the literature showed that the
developed ANN correlation noticeably

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Publication Date
Sat Jan 01 2022
Journal Name
Journal Of The Mechanical Behavior Of Materials
Evaluation of a fire safety risk prediction model for an existing building
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Abstract<p>Fire is one of the most critical risks devastating to human life and property. Therefore, humans make different efforts to deal with fire hazards. Many techniques have been developed to assess fire safety risks. One of these methods is to predict the outbreak of a fire in buildings, and although it is hard to predict when a fire will start, it is critical to do so to safeguard human life and property. This research deals with evaluating the safety risks of the existing building in the city of Samawah/Iraq and determining the appropriateness of these buildings in terms of safety from fire hazards. Twelve parameters are certified based on the National Fire Protection Association (NFPA20</p> ... Show More
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Publication Date
Mon Jun 01 2020
Journal Name
Al-khwarizmi Engineering Journal
Prediction of Cutting Force in Turning Process by Using Artificial Neural Network
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Cutting forces are important factors for determining machine serviceability and product quality. Factors such as speed feed, depth of cut and tool noise radius affect on surface roughness and cutting forces in turning operation. The artificial neural network model was used to predict cutting forces with related to inputs including cutting speed (m/min), feed rate (mm/rev), depth of cut (mm) and work piece hardness (Map). The outputs of the ANN model are the machined cutting force parameters, the neural network showed that all (outputs) of all components of the processing force cutting force FT (N), feed force FA (N) and radial force FR (N) perfect accordance with the experimental data. Twenty-five samp

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Publication Date
Fri Jan 01 2021
Journal Name
Ieee Access
Proposition of New Ensemble Data-Intelligence Models for Surface Water Quality Prediction
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Publication Date
Wed May 17 2023
Journal Name
International Journal Of Computational Intelligence Systems
Prediction of ROP Zones Using Deep Learning Algorithms and Voting Classifier Technique
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Abstract<p>Retinopathy of prematurity (ROP) can cause blindness in premature neonates. It is diagnosed when new blood vessels form abnormally in the retina. However, people at high risk of ROP might benefit significantly from early detection and treatment. Therefore, early diagnosis of ROP is vital in averting visual impairment. However, due to a lack of medical experience in detecting this condition, many people refuse treatment; this is especially troublesome given the rising cases of ROP. To deal with this problem, we trained three transfer learning models (VGG-19, ResNet-50, and EfficientNetB5) and a convolutional neural network (CNN) to identify the zones of ROP in preterm newborns. The dataset to train th</p> ... Show More
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Publication Date
Thu Dec 18 2025
Journal Name
Mathematical Methods In The Applied Sciences
Time‐Dependent Term Identification in the Time–Space Fractional Derivative Diffusion Equation From Integral Over Specified Condition
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ABSTRACT<p> In this paper, a time–space fractional order inverse source problem to determine the temperature solution and the time‐dependent source term from heat moment to the time–space fractional heat equation with an initial condition, homogeneous Dirichlet boundary conditions, and integral overdetermination condition is investigated. Two unconditionally stable finite difference schemes are proposed to find a numerical solution of the direct problem. Namely, method I is based on the approximation of the time‐fractional derivative via Laplace transformation, whereas method II is based on finite difference approximation. The inverse problem is solved iteratively </p> ... Show More
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Publication Date
Sun Mar 01 2020
Journal Name
Journal Of Engineering
The effect of titanium oxide microparticles on mechanical properties, absorption and solubility processes of a glass ionomer cement
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Glass Ionomer Cement (GIC) is one of the important dental temporary filing materials. The aim of this study is to evaluate the effect of adding 3, 5 and 7 wt. % of TiO2 microparticles to conventional GIC powder (Riva Self Cure) on mechanical properties and its effect on absorption and solubility processes. TiO2 particles additives improved compressive strength and biaxial flexural strength, where the compressive strength increased with increasing in the added ratio, while the highest value of the biaxial flexural strength was at 3 wt.%. The addition of TiO2 particles improved the surface Vickers microhardness values, with highest value at 5 wt. %. On other hand TiO2 addition im

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Publication Date
Mon Dec 01 2008
Journal Name
Iraqi Journal Of Physics,2008
optical pulse propagation in photonic bandgap fiber Bragg grating
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Abstract: In this work we demonstrate and investigate the optical pulse propagation in a photonic band gap fiber Bragg grating (FBG). The light propagates in opposite direction in FBG is explained and discussed by a Coupled Mode Theory (CMT). The photonic band gap (stop band gap) is created by fabricated, a Bragg grating in optical fiber. The results show the pulse spectrum falls entirely within the stop band gap, the entire pulse is reflected by the grating, while when the pulse spectrum is outside the stop band gap the pulses will transmitted through the grating. The group velocity (VG) becomes zero at the edges of the stop band and group velocity dispersion β2 is anomalous on the shorter side of stop band gap whereas β2 for uniform fi

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Publication Date
Fri Nov 05 2021
Journal Name
Semiconductor Science And Information Devices
Cladding Modified Fiber Bragg Grating for Copper Ions Detection
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This paper reports a fiber Bragg grating (FBG) as a biosensor. The FBGs were etched using a chemical agent,namely,hydrofluoric acid (HF). This implies the removal of some part of the cladding layer. Consequently, the evanescent field propagating out of the core will be closer to the environment and become more sensitive to the change in the surrounding. The proposed FBG sensor was utilized to detect toxic heavy metal ions aqueous medium namely, copper ions (Cu2+). Two FBG sensors were etched with 20 and 40 μm diameters and fabricated. The sensors were studied towards Cu2+ with different concentrations using wavelength shift as a result of the interaction between the evanescent field and copper ions. The FBG sensors showed

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