In this study, aluminum alloyAA6061-T6 was joined by a hot press process with three types of material; polyamide PA 6.6 (nylon), 1% carbon nanotube/PA6.6 and 30% carbon fiber/PA6.6 composites. Three parameters were considered in the hot pressing; temperature (180, 200 and 220°C), pressure (2, 3, 4, 5 and 6 bar) and time of pressing (1, 2, 3, 4 and 5 minutes for 200ºC, and 0.25, 0.5, 0.75, 1 and 1.25 minutes for220ºC). Applied pressure has great effect on shear strength of the joint, corresponding to bonding time and temperature. Maximum shear strength was 8.89MPa obtained for PA6.6 at bonding conditions of 4 bar, 220ºC and 0.75 minute. For 30% carbon fiber/PA6,6 shear recorded was 8MPa at 4 bar, 220°C and 1 minute, while 1% carbon nanotube/PA6.6 was registered at 8MPa at 4 bar, 220ºC and 0.75 minute. Mechanical interlocking of polyimide in anodizing surface is 8μm approximately. The melting point and glass transmission temperature of polyimide and composites are decreased after hot pressing.
The present study was conducted to estimate the antimicrobial activity and the potential biological control of the killer toxin produced by
Volleyball is one of the sports that require physical and skill abilities thus many teaching models appeared to teach these abilities like group investigation model. The research aimed at identifying the effect of group investigation model on learning underarm and overhead passing in volleyball. The researchers hypothesized statistical differences between pre and posttests in learning underarm and overhead passing in volleyball as well as differences in posttests of controlling and experimental groups in learning underarm and overhead passing in volleyball. The researcher used the experimental method on (30) second year female students of physical education and sport sciences college/ university of Baghdad. Group investigation model was app
... Show MoreThis paper studies the behavior of reinforced Reactive Powder Concrete (RPC) two-way slabs under static and repeated load. The experimental program included testing six simply supported RPC two-way slabs of 1000 mm length, 1000 mm width, and 70 mm thickness. All the tested specimens were identical in their material properties, and reinforcement details except their steel fibers content. They were cast in three pairs, each one had a different steel fibers ratio (0.5 %, 1 %, and 1.5 %) respectively. In each pair, one specimen was tested under static load and the other under five cycles of repeated load (loading-unloading). Static test results revealed that increasing steel fibres volume fraction from 0.5 % to 1 % and from 1% to 1.5%,
... Show MoreThis study includes using green or biosynthesis-friendly technology, which is effective in terms of low cost and low time and energy to prepare V2O5NPs nanoparticles from vanadium sulfate VSO4.H2O using aqueous extract of Punica Granatum at a concentration of 0.1M and with a basic medium PH= 8-12. The V2O5NPs nanoparticles were diagnosed using several techniques, such as FT-IR, UV-visible with energy gap Eg = 3.734eV, and the X-Ray diffraction XRD was calculated using the Debye Scherrer equation. It was discovered to be 34.39nm, Scanning Electron Microscope (SEM), Transmission Electron Microscopy TEM. The size, structure, and composition of synthetic V2O5NPs were determined using the (EDX) pattern, Atomic force microscopy AFM. The a
... Show MoreBackground: The aims of this study were to evaluate the effect of implant site preparation in low-density bone using osseodensification method in terms of implant stability changes during the osseous healing period and peri-implant bone density using CBCT. Material and methods: This prospective observational clinical study included 24 patients who received 46 dental implants that were installed in low-density bone using the osseodensification method. CBCT was used to measure the bone density pre- and postoperatively and implant stability was measured using Periotest® immediately after implant insertion and then after 6 weeks and 12 weeks postoperatively. The data were analyzed using paired t-test and the probability value <0.05 was conside
... Show MoreIn this work, the geomagnetic storms that occurred during solar cycles 23 and 24 were classified based on the value of the Disturbance Storm Time index (Dst), which was considered an indicator of the strength of geomagnetic conditions. The special criterion of Dst >-50 nT was adopted in the classification process of the geomagnetic storms based on the minimum daily value of the Dst-index. The number of geomagnetic storms that occurred during the study period was counted according to the adopted criteria, including moderate storms with (Dst >-50 nT), strong storms with (Dst >-100 nT), severe storms with (Dst >-200 nT), and great storms with (Dst >-350 nT). The statistica
This paper considers and proposes new estimators that depend on the sample and on prior information in the case that they either are equally or are not equally important in the model. The prior information is described as linear stochastic restrictions. We study the properties and the performances of these estimators compared to other common estimators using the mean squared error as a criterion for the goodness of fit. A numerical example and a simulation study are proposed to explain the performance of the estimators.
This study aims to employ modern spatial simulation models to predict the future growth of Al-Najaf city for the year 2036 by studying the change in land use for the time period (1986-2016) because of its importance in shaping future policy for the planning process and decision-making process and ensuring a sustainable urban future, using Geographical information software programs and remote sensing (GIS, IDRISI Selva) as they are appropriate tools for exploring spatial temporal changes from the local level to the global scale. The application of the Markov chain model, which is a popular model that calculates the probability of future change based on the past, and the Cellular Automa
Wellbore instability and sand production onset modeling are very affected by Sonic Shear Wave Time (SSW). In any field, SSW is not available for all wells due to the high cost of measuring. Many authors developed empirical correlations using information from selected worldwide fields for SSW prediction. Recently, researchers have used different Artificial Intelligence methods for estimating SSW. Three existing empirical correlations of Carroll, Freund, and Brocher are used to estimate SSW in this paper, while a fourth new empirical correlation is established. For comparing with the empirical correlation results, another study's Artificial Neural Network (ANN) was used. The same data t
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