In this work, two groups of nanocomposite material, was prepared from unsaturated polyester resin (UPE), they were prepared by hand lay-up method. The first group was consisting of (UPE) reinforced with individually (ZrO2) nanoparticles with particle size (47.23nm). The second group consists of (UPE) reinforced with hybrid nanoparticles consisting of zirconium oxide and yttrium oxide (70% ZrO2 + 30% Y2O3) with particles size (83.98nm). This study includes the effect of selected volume fraction (0.5%, 1%, 1.5%, 2%, 2.5%, 3%) for both reinforcement nano materials. Experimental investigation was carried out by analyzing the thermo-physical properties like thermal conductivity, thermal diffusivity and specific heat for the polymeric composites samples, as well as the hardness test. The results showed that the values of (hardness, specific heat) increased as the nanoparticle content in composite samples increased for both groups’ nanocomposites, whereas the values of thermal conductivity and thermal diffusion decrease for both groups composites. And it was found that the properties of composite materials reinforced by hybrid nanoparticles have higher properties as compared with their counterparts of other nanocomposite reinforced by zirconia nanoparticle. The morphology of the fracture surface was showed homogeneous micro structure formation for both groups composites, indicating a good compatibility between the matrix material and the reinforcement nanoparticles.
Use of computer simulation to quantify the effectiveness of blowing agents can be an effective tool for optimizing formulations and for the adopting of new blowing agents. This paper focuses on a mass balance on blowing agent during foaming including the quantification of the amount that stays in the resin, the amount that ends up in the foam cells, and the pressure of the blowing agent in the foam cells. Experimental data is presented both in the sense of developing the simulation capabilities and the validating of simulation results.
Abstract
In this research, the morphology and mechanical properties of (Epoxy/PVC) blend were investigated. (EP/PVC) blend was prepared by manual mixing of epoxy resin with different weight ratios of (Poly vinyl chloride (PVC) after dissolving it in cyclohexanon). Five sheets of polymer blends in wt% included (0%, 5%, 10%, 15% and 20%) of PVC were prepared at room temperature. Tests were carried out to study some mechanical properties for these blends and compared with the properties of pure epoxy. The morphology of the prepared materials was examined to study the compatibility nature between the two polymers under work. It was found that the best ratio of addition is (20%) of PVC.
... Show MoreThe study aimed to identify the degree of teaching competencies and job satisfaction of the teachers of physical education in the province of Baghdad, and then find the relationship between them. Use the descriptive approach in the style of associative relationships, the research community represented by teachers of physical education in the departments of education Karh (first, second, third) in the province of Baghdad. (522) teachers and (324) school principals distributed in (324) medium within the administrative configurations of these directorates for the academic year (2016 - 2017). The measure (teaching competencies) included (47) words distributed across seven areas. And the measure of (job satisfaction) included (15) words. After t
... Show MoreIn this study, nano TiO2 was prepared with titanium isopropoxide (TTIP) as a resource to titanium oxide. The catalyst was synthesized using phosphotungstic acid (PTA) and, stearyl trimethyl ammonium bromide (STAB) was used as the structure-directing material. Characterization of the product was done by the X-ray diffraction (XRD), X-ray fluorescent spectroscopy (XRF), nitrogen adsorption/desorption measurements, Atomic Force Microscope (AFM) and Fourier transform infrared (FTIR) spectra, were used to characterize the calcined TiO2 nanoparticles by STAB and PWA. The TiO2 nanomaterials were prepared in three crystalline forms (amorphous, anatase, anatase-rutile). The results showed that the
... Show MoreImage classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class
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