Corrosion experiments were carried out to investigate the effect of several operating parameters on the corrosion rate and corrosion potential of carbon steel in turbulent flow conditions in the absence and presence of sodium benzoate inhibitor using electrochemical polarization technique. These parameters were rotational velocity (0 - 1.57 m/s), temperature (30oC – 50oC), and time. The effect of these parameters on the corrosion rate and inhibition efficiency were investigated and discussed. It was found that the corrosion rate represented by limiting current increases considerably with increasing velocity and temperature and that it decreased with time due to the formation of corrosion product layer. The corrosion potential shifted to more positive with increasing temperature and velocity while it shifted to more negative with time. Sodium benzoate gave good inhibition efficiency for the whole investigated range of temperature and velocity. Its efficiency was high on clean surfaces and decreased with time in stationary and flow conditions. No noticeable effect of temperature on the inhibition efficiency was noticed.
The microdrilling and nanodrilling holes are produced by a Q-switched Nd :YAG laser (1064 nm) interaction with 8009 Al alloy using nanoparticles. Two kinds of nanoparticles were used with this alloy. These nanoparticles are tungsten carbide (WC) and silica carbide (SiC). In this work, the microholes and nanoholes have been investigated with different laser pulse energies (600, 700 and 800)mJ, different repetition rates (5Hz and 10Hz) and different concentration of nanoparticles (90%, 50% and 5% ). The results indicate that the microholes and nanoholes have been achieved when the laser pulse energy is 600 mJ, laser repetition rate is 5Hz, and the concentration of the nanoparticles (for the two types of n
... Show MorePick and place system is one of the significant employments of modern robots utilized in industrial environments. The objective of this research is to make a comparison of time sequences by combining multiple axes of sequences. A pick-place system implemented with pneumatic linear double-acting cylinders to applicator in automated systems processes for manufacturing. The challenge of 3-axes movement control was achieved using the PLC (Programmable Logic Controller) controller such that the merging between two or three axes was achieved according to the selected sequence of the program. The outcomes show the contrasted sequences and the reference in a constant velocity. The main variable parameter is the number of steps for each sequ
... Show MoreCNC machine is used to machine complex or simple shapes at higher speed with maximum accuracy and minimum error. In this paper a previously designed CNC control system is used to machine ellipses and polylines. The sample needs to be machined is drawn by using one of the drawing software like AUTOCAD® or 3D MAX and is saved in a well-known file format (DXF) then that file is fed to the CNC machine controller by the CNC operator then that part will be machined by the CNC machine. The CNC controller using developed algorithms that reads the DXF file feeds to the machine, extracts the shapes from the file and generates commands to move the CNC machine axes so that these shapes can be machined.
The aim of this stud to isolate and identified of A. fumigatus from different sources and study the genetic diversity among these isolates by using RAPD and ISSR markers.Collected 20 samples from 7samples were isolated A. fumigatusisolates were characterized depending on its morphological, then extracted DNA from its.RAPD markersrandomly bandingwith sitesof genome more than ISSR markers where the primer OPN-07 achieved discriminative power (19.1) and 43 bands, while ISSR6 achieved discriminative power (17.1) with 32 bands.ISSR were more efficiency in specific binding then RAPD, ISSR primers has great a binding to production unique band, when 9 primers from 01 primers, ISSR9 was produce (5) unique bands, while RAPD markers was low ability
... Show MoreThis paper proposes a better solution for EEG-based brain language signals classification, it is using machine learning and optimization algorithms. This project aims to replace the brain signal classification for language processing tasks by achieving the higher accuracy and speed process. Features extraction is performed using a modified Discrete Wavelet Transform (DWT) in this study which increases the capability of capturing signal characteristics appropriately by decomposing EEG signals into significant frequency components. A Gray Wolf Optimization (GWO) algorithm method is applied to improve the results and select the optimal features which achieves more accurate results by selecting impactful features with maximum relevance
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