This study deals with the corrosion inhibition of metal corrosion process of medium carbon steel using 1M HCl for kinetic studies and rate reaction determination. The weight loss method is applied to pieces of Medium carbon steel divided to Cubans with dimensions (0.4*2*2.4) cm , and use Tafel Extrapolation Method, the samples were polished using carbide silicon paper with dimensions of (180,200,400,600,800,1000). The samples were immersed in the alcoholic medium ethanol at a temperature 293K for 3hr. Natural inhibitor Kujarat Tea (Hibiscus sabdarriffa L.) is used which is extracted in aqueous and alcoholic medium, different concentrations (1000،2000, 3000) ppm have been used ; The best concentration found through the results is a conce

Nano TiO₂ thin films on glass substrates were prepared at a constant temperature of (373 K) and base vacuum (10_-3 mbar), by pulsed laser deposition (PLD) using Nd:YAG laser at 1064 nm wavelength. The effects of different laser energies between (700-1000)mJ on the properties of TiO₂ films was investigated. TiO₂ thin films were characterized by X-ray diffraction (XRD) measurements have shown that the polycrystalline TiO₂ prepared at laser energy 1000 mJ. Preparation also includes optical transmittance and absorption measurements as well as measuring the uniformity of the surface of these films. Optimum parameters have been identified for the growth of high-quality TiO₂ films

Synthesis and study liquid crystalline properties of new compounds with terminal groups of amides ([III]a-c,[IV]a-c and [VI]n), alkoxy series[V]n or ester with azo linkage ([IX]a-c and[X]a-c) containing thaizole ring. These series were synthesized by many steps starting from 4- hydroxyacetophenone or 4-aminoacetophenone. The synthesized compounds were characterized using melting points, FTIR, C.H.N.S analysis and for some of them 1H NMR spectroscopy. The liquid crystalline properties were studied by hot stage polarizing microscopy and differential scanning calorimetry DSC. All compounds of series [III]a-c,[IV]a-c and compounds [V]n showed enantiotropic liquid crystal. While the series [VI]n showed nematic mesomorphism except [VI]8 did not s

The ejector refrigeration system is a desirable choice to reduce energy consumption. A Computational Fluid Dynamics CFD simulation using the ANSYS package was performed to investigate the flow inside the ejector and determine the performance of a small-scale steam ejector. The experimental results showed that at the nozzle throat diameter of 2.6 mm and the evaporator temperature of 10^oC, increasing boiler temperature from 110^oC to 140^oC decreases the entrainment ratio by 66.25%. At the boiler temperature of 120^oC, increasing the evaporator temperature from 7.5 to 15 ^oC increases the entrainment ratio by 65.57%. While at the boiler temperature of 120^oC and

In this research, experimental and numerical studies were carried out to investigate the performance of encased glass-fiber-reinforced polymer (GFRP) beams under fire. The test specimens were divided into two peer groups to be tested under the effect of ambient and elevated temperatures. The first group was statically tested to investigate the monotonic behavior of the specimens. The second group was exposed to fire loading first and then statically tested to explore the residual behavior of the burned specimens. Adding shear connectors and web stiffeners to the GFRP beam was the main parameter in this investigation. Moreover, service loads were applied to the tested beams during the fire. Utilizing shear connectors, web stiffeners,

In this research, experimental and numerical studies were carried out to investigate the performance of encased glass-fiber-reinforced polymer (GFRP) beams under fire. The test specimens were divided into two peer groups to be tested under the effect of ambient and elevated temperatures. The first group was statically tested to investigate the monotonic behavior of the specimens. The second group was exposed to fire loading first and then statically tested to explore the residual behavior of the burned specimens. Adding shear connectors and web stiffeners to the GFRP beam was the main parameter in this investigation. Moreover, service loads were applied to the tested beams during the fire. Utilizing shear connectors, web stiffeners,

     Deep learning (DL) plays a significant role in several tasks, especially classification and prediction. Classification tasks can be efficiently achieved via convolutional neural networks (CNN) with a huge dataset, while recurrent neural networks (RNN) can perform prediction tasks due to their ability to remember time series data. In this paper, three models have been proposed to certify the evaluation track for classification and prediction tasks associated with four datasets (two for each task). These models are CNN and RNN, which include two models (Long Short Term Memory (LSTM)) and GRU (Gated Recurrent Unit). Each model is employed to work consequently over the two mentioned tasks to draw a road map of deep learning mod

The objective of this work is to study the influence of end milling cutting process parameters, tool material and geometry on multi-response outputs for 4032 Al-alloy. This can be done by proposing an approach that combines Taguchi method with grey relational analysis. Three cutting parameters have been selected (spindle speed, feed rate and cut depth) with three levels for each parameter. Three tools with different materials and geometry have been also used to design the experimental tests and runs based on matrix L9. The end milling process with several output characteristics is solved using a grey relational analysis. The results of analysis of variance (ANOVA) showed that the major influencing parameters on multi-objective response w