In this work, functionally graded materials were synthesized by centrifugal technique at different
volume fractions 0.5, 1, 1.5, and 2% Vf with a rotation speed of 1200 rpm and a constant rotation time, T
= 6 min . The mechanical properties were characterized to study the graded and non-graded nanocomposites
and the pure epoxy material. The mechanical tests showed that graded and non-graded added alumina
(Al2O3) nanoparticles enhanced the effect more than pure epoxy. The maximum difference in impact strength
occurred at (FGM), which was loaded from the rich side of the nano-alumina where the maximum value was
at 1% Vf by 133.33% of the sample epoxy side. The flexural strength and Young modulus of the functionally
graded samples were enhanced by 43.69% and 52.74%, respectively, if loaded from the alumina-rich side.
On the other hand, when loading (FGM) from the epoxy side, the amount of decrease in bending resistance
was 122.4% while the improvement in bending modulus was 81.11% compared to pure epoxy. Scanning
electron microscopy (SEM) revealed the fracture surface of the impact samples and the gradient scattering of
nanoparticles in the epoxy matrix. Numerous applications can be used to manufacture the functionally
graded material by centrifugal casting method, including for the manufacture of gears and all bending
applications such as leaf springs.
Reducing the drag force has become one of the most important concerns in the automotive industry. This study concentrated on reducing drag through use of some external modifications of passive flow control, such as vortex generators, rear under body diffuser slices and a rear wing spoiler. The study was performed at inlet velocity (V=10,20,30,40 m/s) which correspond to an incompressible car model length Reynolds numbers (Re=2.62×105, 5.23×105, 7.85×105 and 10.46×105), respectively and we studied their effect on the drag force. We also present a theoretical study finite volume method (FVM) of solvi
In this study, pure SnO2 Nanoparticles doped with Cu were synthesized by a chemical precipitation method. Using SnCl2.2H2O, CuCl2.2H2O as raw materials, the materials were annealed at 550°C for 3 hours in order to improve crystallization. The XRD results showed that the samples crystallized in the tetragonal rutile type SnO2 stage. As the average SnO2 crystal size is pure 9nm and varies with the change of Cu doping (0.5%, 1%, 1.5%, 2%, 2.5%, 3%),( 8.35, 8.36, 8.67, 9 ,7, 8.86)nm respectively an increase in crystal size to 2.5% decreases at this rate and that the crystal of SnO2 does not change with the introduction of Cu, and S
... Show MoreMany oil and gas processes, including oil recovery, oil transportation, and petroleum processing, are negatively impacted by the precipitation and deposition of asphaltene. Screening methods for determining the stability of asphaltenes in crude oil have been developed due to the high cost of remediating asphaltene deposition in crude oil production and processing. The colloidal instability index, the Asphaltene-resin ratio, the De Boer plot, and the modified colloidal instability index were used to predict the stability of asphaltene in crude oil in this study. The screening approaches were investigated in detail, as done for the experimental results obtained from them. The factors regulating the asphaltene precipitation are different fr
... Show MoreEnergy savings are very common in IoT sensor networks because IoT sensor nodes operate with their own limited battery. The data transmission in the IoT sensor nodes is very costly and consume much of the energy while the energy usage for data processing is considerably lower. There are several energy-saving strategies and principles, mainly dedicated to reducing the transmission of data. Therefore, with minimizing data transfers in IoT sensor networks, can conserve a considerable amount of energy. In this research, a Compression-Based Data Reduction (CBDR) technique was suggested which works in the level of IoT sensor nodes. The CBDR includes two stages of compression, a lossy SAX Quantization stage which reduces the dynamic range of the
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Cutting forces are important factors for determining machine serviceability and product quality. Factors such as speed feed, depth of cut and tool noise radius affect on surface roughness and cutting forces in turning operation. The artificial neural network model was used to predict cutting forces with related to inputs including cutting speed (m/min), feed rate (mm/rev), depth of cut (mm) and work piece hardness (Map). The outputs of the ANN model are the machined cutting force parameters, the neural network showed that all (outputs) of all components of the processing force cutting force FT (N), feed force FA (N) and radial force FR (N) perfect accordance with the experimental data. Twenty-five samp
... Show MoreBackground Alloys with the addition of zirconium and niobium eliminate the adverse effects of aluminum and vanadium on the nervous system, the possibility of metallosis and the initiation of diseases (including cancers or Alzheimer›s disease). In addition, they have better corrosion resistance, and a Young›s modulus value similar to longitudinal bone tissue. Therefore, only choosing appropriate materials does not guarantee proper functioning of the implants, the surfaces of the implants also have to be suitable to meet the requirements. The laser surface hardening process modifies the surface properties by imparting microstructural changes, whereas surface remelting induces changes in the surface topography, roughness, wettability and w
... Show MoreQuantum calculations on the most stable structure were carried
out for calculating the electronic properties, energies and the charge
density at the Carbon and Hydrogen atoms by Semi-empirical
method (PM3) of zigzag carbon nano tube CNT (9,0) (SWCNTs), at
the equilibrium geometry depending on the pictures of Zigzag
CNT(9,0) which was found to has D3d symmetry point group by
applying for (Gaussian 2003) program. In this work the results
include calculation the relation for axial bonds length, which are the
vertical C-C bonds (annular bonds) in the rings and bonds length
which are in the outer ring that called the circumferential bonds. Also
include a different kind of vibration modes like breathing, puckering
In this work Study effect of annealing temperature on the Structure
of a-Se and electrical properties of a-Se/c-Si hetrojunction have been
studied.The hetrojunction fabricated by deposition of a-Se film on c-
Si using thermal evaporation.
Electrical properties of a-Se/ c-Si heterojunction include I-V
characteristics, in dark at different annealing temperature and C-V
characteristics are considered in the present work.
C-V characteristics suggested that the fabricated diode was
abrupt type, built in potential determined by extrapolation from
1/C2-V curve. The built - in potential (Vbi) for the Se/ Si System
was found to be increase from 1.21 to 1.62eV with increasing of
annealing temperature