In this study the thermal conductivity of the epoxy composites were characterized as function of volume fraction, particle size of fillers and the time of immersion(30,60,90)days in water .Composites plates were prepared by incorporating (bi-directional) (0º-90º) glass fiber and silicon carbide (SiC) particles of (0.1,0.5,1)mm as particle size at (10%,20%,30%,40%) percent volume in epoxy matrix.
The composites shows slightly increase of the thermal conductivity with increasing volume fraction, particle size and increase with increasing the days of immersion in water. The maximum thermal conductivity (0.51W/m.K) was obtained before the immersion in water at 90 days for epoxy reinforcement by bi-directional glass fiber and SiC particl

Desulfurization of a simulated diesel fuel by different adsorbents was studied in a fixed-bed adsorption process operated at ambient temperature and pressure.  Three different adsorption beds were used, commercial activated carbon, Cu-Y zeolite, and layered bed of 15wt% activated carbon followed by Cu-Y zeolite.Initially Y-zeolite was prepared from Iraqi rice husk and then impregnated with copper. In general, the adsorbents tested for total sulfur adsorption capacity at break through followed the order Ac/Cu-Y zeolite>Cu-Y zeolite>Ac. The best adsorbent, Ac/Cu-Y zeolite is capable of producing more than 30 cm3 of simulated diesel fuel per gram of adsorbent with a weighted average content of 5 ppm-S, while Cu-Y zeolite producing of

The present work involves studying the effect of electrolyte composition [@1= 0.5 wt.%  NH₄F / 5% H₂O / 5% Glycerol (GLY)/ 90%  Ethylene Glycol (EG)] and [ @2= 0.5 wt. % NH₄F / 5% H₂O / 95%  Ethylene Glycol (EG)]  on the structural and photoelectrochemical properties of titania nanotubes arrays (TNTAs). TNTAs substrates were successfully carried out via anodization technique and were carried out in 40 V for one hour in different electrolytes (@1, and @2). The properties of physicochemical of TNTAs were distinguished via an X-ray Diffractometer (XRD), Field Emission Scanning Electron Microscope (FESEM), an Energy Dispersive X-ray (EDX), and UV–visible diffuse reflectance. T

The present research aims to study the effect of friction stir welding (FSW) parameters on temperature distribution and tensile strength of aluminum 6061-T6. Rotational and traverse speeds used were (500,1000,1400 rpm) and (14,40,112 mm/min) respectively. Results of mechanical tests showed that using 500rpm and 14mm/min speed give the best strength. A three- dimensional fully coupled thermal-stress finite element model via ANSYS software has been developed. The Rate dependent Johnson-Cook relation was utilized for elasto-plastic work deformations. Heat-transfer is formulated using a moving heat source, and later used the transient temperature outputs from the thermal analysis to determine equivalent stresses in the welde

Although many technological improvements are occurring in power production worldwide, power plants in third world countries are still using old technologies that are causing thermal pollution to the water bodies. Power facilities that dump hot water into water bodies are damaging aquatic life. In the study, the impact of the Al Dora thermal power plant on a nearby stretch of Tigris River in Baghdad city was assessed by measuring the temperature of the disposed of hot water in various cross-sections of the selected stretch of Tigris River, including measuring the thermal mixing length. The measurements were conducted in winter, spring, and summer. For field measurements, it was found that the impact of recovery distances

This study includes adding chemicals to gypseous soil to improve its collapse characteristics. The collapse behavior of gypseous soil brought from the north of Iraq (Salah El-Deen governorate) with a gypsum content of 59% was investigated using five types of additions (cement dust, powder sodium meta-silicate, powder activated carbon, sodium silicate solution, and granular activated carbon). The soil was mixed by weight with cement dust (10, 20, and 30%), powder sodium meta-silicate (6%), powder activated carbon (10%), sodium silicate solution (3, 6, and 9%), and granular activated carbon (5, 10, and 15%). The collapse potential is reduced by 86, 71, 43, 37, and 35% when 30% cement dust, 6% powder sodium meta-silicate, 10% powder activated

New Schiff base ligand 2-((4-amino-5-(3, 4, 5-trimethoxybenzyl) pyrimidin- 2-ylimino) (phenyl)methyl)benzoic acid] = [HL] was synthesized using microwave irradiation trimethoprim and 2-benzoyl benzoic acid. Mixed ligand complexes of Mn((ІІ), Co(ІІ), Ni(ІІ), Cu(ІІ), Zn(ІІ) and Cd(ІІ) are reacted in ethanol with Schiff base ligand [HL] and 8-hydroxyquinoline [HQ] then reacted with metal salts in ethanol as a solvent in (1:1:1) ratio. The ligand [HL] is characterized by FTIR, UV-Vis, melting point, elemental microanalysis (C.H.N), 1H-NMR, 13C-NMR, and mass spectra. The mixed ligand complexes are characterized by infrared spectra, electronic spectra, (C.H.N), melting point, atomic absorption, molar conductance and magnetic moment me

Molecular dynamics (MD) simulations were carried out in order to investigate the binding mode of axillaridine-A at the active site of human acetylcholinesterase (AChE) enzyme. 2.0 nanosecond of MD simulations was made for the protein and the complex to dynamically explore the active site and the behavior of the ligand at the peripheral AChE binding site. These calculations for the enzyme alone showed that the active site of AChE is located at the bottom of a deep and narrow cavity whose surface is lined with rings of aromatic residues and Tyr72 is almost perpendicular to the Trp286 ring and forms a stable - interaction. The size of the active site of the complex decreases with time due to increase the interaction. Axillaridine-A forms

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