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Fatigue Characterization for Composite Materials used in Artificial Socket Prostheses with the Adding of Nanoparticles
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Abstract<p>The prostheses sockets use normally composite materials which means that their applications may be related with the human body. Therefore, it was very necessary to improve the mechanical properties of these materials. The prosthetic sockets are subjected to varying stresses in gait cycle scenario which may cause a fatigue damage. Therefore, it is necessary or this work to modify the fatigue behavior of the materials used for manufacturing the prostheses sockets. In this work, different Nano particle materials are used to modify the mechanical properties of the composite materials, and increase the fatigue strength. By using an experimental technique, the effect of using different volume fractions for various types for Nano particle materials on the fatigue behavior for composite materials, and preparing the fatigue samples and tested using the fatigue apparatus. The Nano particles used were (Nano SiO<sub>2</sub> and Nano Al<sub>2</sub>O<sub>3</sub>) materials with volume fraction as (0% to 2%), for each type of Nano material used. The artificial neural network technique was adopted to have a verification for the experimental results and calculating the fatigue life and strength for composite materials, with the addition of nanoparticles and then, a comparison of the results was achieved. The comparison of the results indicate a maximum error between results calculated by two technique did not exceeded about (1%). Then, the results calculated showed that the mechanical properties and fatigue life and strength increase with reinforcement with Nano particle. Also, the results showed that the modified for fatigue limits with materials by (Nano SiO<sub>2</sub>) Nano particle was more than the modified for fatigue limits for materials reinforcement with other materials. Finally, it can be concluded that the modified for fatigue strength, by reinforcement with (Nano SiO<sub>2</sub>), leads to 60% more than fatigue limit without Nano additive.</p>
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Publication Date
Mon Oct 02 2023
Journal Name
Journal Of Engineering
Comparative Study between Recycled Fine and Coarse Aggregate Used in Roller Compacted Concrete Pavement
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To decrease the impact on the environment of building waste, the recycled aggregate may be used in various sustainable engineering applications, such as roller compacted concrete pavement (RCCP). This research examined how using recycled aggregate as a partial replacement for natural aggregate as coarse or fine affected the mechanical properties of roller-compacted concrete pavement. The recycled aggregate was crushed and sieved to coarse and fine aggregate before being used in the roller-compacted concrete pavement. Compressive strength, splitting tensile strength, and flexural strength were all evaluated after the samples were prepared at 28 and 90 days of curing. According to the study's findings, the partial replacem

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Publication Date
Sun Jan 01 2023
Journal Name
Water, Air, And Soil Pollution
Sunflower Husks Coated with Copper Oxide Nanoparticles for Reactive Blue 49 and Reactive Red 195 Removals: Adsorption Mechanisms, Thermodynamic, Kinetic, and Isotherm Studies
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The adsorption process of reactive blue 49 (RB49) dye and reactive red 195 (RR195) dye from an aqueous solutions was explored using a novel adsorbent produced from the sunflower husks encapsulated with copper oxide nanoparticle (CSFH). Primarily, the features of a CSFH, such as surface morphology, functional groups, and structure, were characterized. It was determined that coating the sunflower husks with copper oxide nanoparticles greatly improved the surface and structural properties related to the adsorption capacity. The adsorption process was successful, with a removal efficiency of 97% for RB49 and 98% for RR195 under optimal operating conditions, contact time of 180 min, pH of 7, agitation speed of 150 rpm, initial dye concentration

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Publication Date
Sun Jan 01 2023
Journal Name
Water, Air, &amp; Soil Pollution
Sunflower Husks Coated with Copper Oxide Nanoparticles for Reactive Blue 49 and Reactive Red 195 Removals: Adsorption Mechanisms, Thermodynamic, Kinetic, and Isotherm Studies
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Publication Date
Thu Mar 01 2018
Journal Name
Journal Of Engineering
Analysis of Double Skin Composite Slabs
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This paper deals with finite element modeling of the ultimate load behavior of double skin composite (DSC) slabs. In a DSC slab, shear connectors in the form of nut bolt technique studs are used to transfer shear between the outer skin made of steel plates and the concrete core. The current study is based on finite element analysis using ANSYS Version 11 APDL release computer program. Experimental programmes were carried out by the others, two simply supported DSC beams were tested until failure under a concentrated load applied at the center. These test specimens were analyzed by the finite element method and the analyses have shown that these slabs displayed a high degree of flexural characteristics, ultimate strength,

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Publication Date
Fri Aug 15 2025
Journal Name
Journal Port Science Research
The Antimicrobial Characteristics of Some Natural Remedies in Root Canal Disinfection and Artificial Intelligence (AI): A Review
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The primary goal of root canal treatment (RCT) is to expel the presence of any necrotic or vital tissue, microbes and their byproducts from the canal space before press forward with the following steps of the RCT procedures. Although this is difficult to attain, various strives had been practiced by employing chemical and mechanical methods to eliminate as much microorganisms as possible and make the canal space valid for the obturation materials to be received. The aim of this review is to demonstrate some of what new remedies that could be used as root canal disinfectant by summarizing the recent studies regarding the efficacy of different natural products against the most persistence microbiota that could be responsible for most

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Publication Date
Sun Jan 01 2012
Journal Name
Al-nahrain Journal Of Science
Synthesis and Characterization of New Azo Dye Complexes with Selected Metal Ions
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Coupling reaction of 2-amino benzoic acid with phenol gave the new bidentate azo ligand. The prepared ligand was identified by Microelemental Analysis, FT-IR and UV-Vis spectroscopic technique. Treatment of the prepared ligand with the following metal ions (CoII, NiII, CuII and ZnII) in aqueous ethanol with a 1:2 M:L ratio and at optimum pH, yielded a series of neutral complexes of the general formula [M(L)2]. The prepared complexes were characterized using flame atomic absorption, (C.H.N) Analysis, FT-IR and UV-Vis spectroscopic methods as well as magnetic susceptibility and conductivity measurements. The nature of the complexes formed were studied following the mole ratio and continuous variation methods, Beer's law obeyed over a concentr

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Publication Date
Wed May 16 2012
Journal Name
Journal Of Kerbala University
Synthesis and Characterization of Heterocyclic Azo Dye Complexes with Selected Metal Ions
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Coupling reaction of 4-amino antipyrene with 2,6-dimethyl phenol gave bidentate azo ligand. The prepared ligand was identified by Microelemental Analysis, 1HNMR, FT-IR and UV-Vis spectroscopic techniques. Treatment of the prepared ligand with the following metal ions (CoII, NiII, CuII, ZnII, CdII, and HgII) in aqueous ethanol with a 1:2 M:L ratio and at optimum pH, yielded a series of neutral complexes of the general formula [M(L)2Cl2]. The prepared complexes were characterized using flame atomic absorption, (C.H.N) Analysis, FT-IR and UVVis spectroscopic methods as well as magnetic susceptibility and conductivity measurements. Chloride ion content was also evaluated by (Mohr method). The nature of the complexes formed were studied followin

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Publication Date
Sat Aug 31 2019
Journal Name
Iraqi Journal Of Physics
Characterization of Zinc oxide Nanostructures prepared by hydrothermal method with Antibacterial property
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        In this study, Zinc oxide nanostructures were synthesized via a hydrothermal method by using zinc nitrate hexahydrate and sodium hydroxide as a precursor. Three different annealing temperatures were used to study their effect on ZnO NSs properties. The synthesized nanostructure was characterized by X-ray diffraction (XRD), field emission scanning electron microscopy (FESEM), Atomic force microscope (AFM), and Fourier Transform Infrared Spectroscopy (FTIR). Their optical properties were studied by using UV -visible spectroscopy. The XRD analysis confirms that all ZnO nanostructures have the hexagonal wurtzite structure with average crystallite size within the range of (30.59 - 34

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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
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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