The effects of using aqueous nanofluids containing covalently functionalized graphene nanoplatelets with triethanolamine (TEA-GNPs) as novel working fluids on the thermal performance of a flat-plate solar collector (FPSC) have been investigated. Water-based nanofluids with weight concentrations of 0.025%, 0.05%, 0.075%, and 0.1% of TEA-GNPs with specific surface areas of 300, 500, and 750 m2/g were prepared. An experimental setup was designed and built and a simulation program using MATLAB was developed. Experimental tests were performed using inlet fluid temperatures of 30, 40, and 50 °C; flow rates of 0.6, 1.0, and 1.4 kg/min; and heat flux intensities of 600, 800, and 1000 W/m2. The FPSC’s efficiency increased as the flow rate and heat flux intensity increased, and decreased as inlet fluid temperature increased. When using nanofluids in the FPSC, the measured temperatures of absorber plate and tube wall decreased down to 3.35% and 3.51%, respectively, with the increase in weight concentration and specific surface area, while the efficiency increased up to 10.53% for 0.1- wt% TEA-GNPs nanofluid with specific surface area of 750 m2/g, in comparison with water. When using water as heat transfer fluid, very good agreement was obtained between the experimental and predicted values of absorber plate temperature, tube wall temperature, and collector’s efficiency with maximum differences of 3.02%, 3.19%, and 3.26%, respectively. While, when using nanofluids, higher differences were found, up to 4.74%, 4.7%, and 13.47% for TEA-GNPs nanofluid with specific surface area of 750 m2/g, respectively. Accordingly, the MATLAB code was capable of simulating the thermal performance of FPSCs utilizing nanofluids as their heat transfer fluids with acceptable accuracy. Values of performance index were all greater than 1, and increased as weight concentration increased up to 1.104 for 0.1- wt% TEA-GNPs nanofluid with specific surface area of 750 m2/g, implying higher positive effects on efficiency than negative effects on pressure drop. Accordingly, the investigated nanofluids can efficiently be used in FPSCs for enhanced energy efficiency, and the 0.1- wt% water-based TEA-GNPs nanofluid with specific surface area of 750 m2/g was comparatively the superior one.
A set of ten drug compounds containing an amino group in the structure were determined theoretically. The parameters were entered into a model to forecast the optimal values of practical (log P) medicinal molecules. The drugs were evaluated theoretically using different types of calculations which are AM1, PM3, and Hartree Fock at the basis set (HF/STO-3G). The Physico-chemical data like (entropy, total energy, Gibbs Free Energy,…etc were computed and played an important role in the predictions of the practical lipophilicity values. Besides, Eigenvalues named HOMO and LUMO were determined. Linearity was shown when correlated between the experimental data with the evaluated physical properties. The statistical analysis was used to analy
... Show MoreThis study was conducted at the Poultry Research Station of the Agricultural Research Department/Ministry of Agriculture in Abu Ghraib for the period from 25/2/2019 to 7/4/2019 (42 days) with the aim of using several levels of Spirulina (SP)
Blood samples were collected from (31) pregnant women infected with cytomegalovirus , also (15) blood samples were collected from congenitally infected infants, and (20),(15),(15) blood samples were collected from pregnant women ,non pregnant and infants, respectively, all of them were as control groups. CMV infection identified by using ELISA assay to detect specific CMV IgM & IgG in sera. The results of lymphocyte transformation showed a significant decrease when phytoheamagglutinin (PHA) used as stimulator, lymphocytes response in infected pregnant women was lower than that of non infected pregnant women as well as non pregnant women. Result also showed a significant decrease in the ability of lymphocyte division in healthy pregnant w
... Show MoreThe main object of this article is to study and introduce a subclass of meromorphic univalent functions with fixed second positive defined by q-differed operator. Coefficient bounds, distortion and Growth theorems, and various are the obtained results.
The non static chain is always the problem of static analysis so that explained some of theoretical work, the properties of statistical regression analysis to lose when using strings in statistic and gives the slope of an imaginary relation under consideration. chain is not static can become static by adding variable time to the multivariate analysis the factors to remove the general trend as well as variable placebo seasons to remove the effect of seasonal .convert the data to form exponential or logarithmic , in addition to using the difference repeated d is said in this case it integrated class d. Where the research contained in the theoretical side in parts in the first part the research methodology ha
... Show MoreDue to the vast using of digital images and the fast evolution in computer science and especially the using of images in the social network.This lead to focus on securing these images and protect it against attackers, many techniques are proposed to achieve this goal. In this paper we proposed a new chaotic method to enhance AES (Advanced Encryption Standards) by eliminating Mix-Columns transformation to reduce time consuming and using palmprint biometric and Lorenz chaotic system to enhance authentication and security of the image, by using chaotic system that adds more sensitivity to the encryption system and authentication for the system.
The field of Optical Character Recognition (OCR) is the process of converting an image of text into a machine-readable text format. The classification of Arabic manuscripts in general is part of this field. In recent years, the processing of Arabian image databases by deep learning architectures has experienced a remarkable development. However, this remains insufficient to satisfy the enormous wealth of Arabic manuscripts. In this research, a deep learning architecture is used to address the issue of classifying Arabic letters written by hand. The method based on a convolutional neural network (CNN) architecture as a self-extractor and classifier. Considering the nature of the dataset images (binary images), the contours of the alphabet
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