Flexure members such as reinforced concrete (RC) simply supported beams subjected to two-point loading were analyzed numerically. The Extended Finite Element Method (XFEM) was employed for the treatment the non-smooth h behaviour such as discontinuities and singularities. This method is a powerful technique used for the analysis of the fracture process and crack propagation in concrete. Concrete is a heterogeneous material that consists of coarse aggregate, cement mortar and air voids distributed in the cement paste. Numerical modeling of concrete comprises a two-scale model, using mesoscale and macroscale numerical models. The effectiveness and validity of the Meso-Scale Approach (MSA) in modeling of the reinforced concrete beams with minimum reinforcement was studied. ABAQUS program was utilized for Finite Element (FE) modeling and analysis of the beams. On the other hand, mesoscale modeling of concrete constituents was executed with the aid of ABAQUS PYTHON language and programing using excel sheets. The concrete beams under flexure were experimentally investigated as well as by the numerical analysis. The comparison between experimental and numerical results showed that the mesoscale model gives a better indication for representing the concrete models in the numerical approach and a more appropriate result when compared with the experimental results.
Management of Foreign Exchange Rate Exposure by Using Financial Hedging An Analytical Empirical Study The main purpose of this Research is to investigate the ability to reduce the effect of exchange rate fluctuation on firm value , by usage appropriate hedging strategies to provide the firms force to adopted with complex and highly uncertainty conditions , characteristic of the most of the financial markets . The field of this study is the giant five Multinational on the world. Nokia, Toyota Motor, Intel , Coca Cola, Microsoft. practical analysis is provide the truth of all study's hypothesis , and it is reach to many of conclusion, the most important of them is Stem from unexpected fluctuation on nominal ex
... Show MoreThis paper presents an experimental study of cooling photovoltaic (PV) panels using evaporative cooling. Underground (geothermal energy) water used to extract heat from it during cooling and cleaning of PV panels. An experimental test rig was constructed and tested under hot and dusty climate conditions in Baghdad. An active cooling system was used with auxiliary an underground water tank to provide cold water as a coolant over both PV surfaces to reduce its temperature. The cellulose pad has been arranged on the back surface and sprays cooling on the front side. Two identical PV panels modules used: without cooling and evaporative water cooling. The experiments are comprised of four cases: Case (I): backside cooling, Ca
... Show MoreSorting and grading agricultural crops using manual sorting is a cumbersome and arduous process, in addition to the high costs and increased labor, as well as the low quality of sorting and grading compared to automatic sorting. the importance of deep learning, which includes the artificial neural network in prediction, also shows the importance of automated sorting in terms of efficiency, quality, and accuracy of sorting and grading. artificial neural network in predicting values and choosing what is good and suitable for agricultural crops, especially local lemons.
Gypseous soils are spread in several regions in the world including Iraq, where it covers more than 28.6% [1] of the surface region of the country. This soil, with high gypsum content causes different problems in construction and strategic projects. As a result of water flow through the soil mass, permeability and chemical arrangement of these soils vary over time due to the solubility and leaching of gypsum. In this study the soil of 36% gypsum content, is taken from one location about 100 km (62 mi) southwest of Baghdad, where the sample is taken from depth (0.5 - 1) m below the natural ground surface and mixed with (3%, 6%, 9%) of Copolymer and Styrene-butadiene Rubber to improve t
Liposome-mediated transfection of cancer cells provide a valuable experimental technique to study cellular gene expression and may also be adapted for gene therapy studies. However, the widely recognized advantage of liposome-mediated transfection is high efficiency. Therefore, this study were performed to optimize transfection techniques in human larynx carcinoma cell line Hep-2 using the commercial synthetic lipid TransFast™ Reagent and monitoring the expression efficiency by using the pSV-?-galactosidase Control Vector which encoded ?-galactosidase, maximum transfection efficiency were achieved with TransFast™ Reagent used at the Charge ratios of 2:1 and 0.5 µg DNA/ml, this is indicate that TransFast™ Reagent can be used as an eff
... Show MoreBackground: Radiopacity is one of the prerequisites for dental materials, especially for composite restorations. It's essential for easy detection of secondary dental caries as well as observation of the radiographic interface between the materials and tooth structure. The aim of this study to assess the difference in radiopacity of different resin composites using a digital x-ray system. Materials and methods: Ten specimens (6mm diameter and 1mm thickness) of three types of composite resins (Evetric, Estelite Sigma Quick,and G-aenial) were fabricated using Teflon mold. The radiopacity was assessed using dental radiography equipment in combination with a phosphor plate digital system and a grey scale value aluminum step wedge with thickness
... Show More<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol
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