The accelerating effect of 1,4- phenylenediamine (PDA) additions in 1M hydrochloric acid solution at temperature rang (20-60) C° has been studied by weight losses measurement during ranging time (1-260) h and by following the pb2+ concentration in solution after several times by using Atomic absorption spectroscopy (AAS) . The volume of hydrogen gas involving was followed also in presence and absence of (PDA) in the corrosive solution .Accelerating enhanced by adding (NaCl , NaBr , NaI ) was also investigated.

The c.orrosion rate of  low carbon  steel  in 4M  hydrochlwic acid with and without  presence of thiourea has b.een studied  by gravimetric ahd gasometric methods  over the temperature range 303-333 K.

The percentage protection of steel increases  vvith the decrease of thimuea concentrations at  various  temperature range  303-333 K and

approaching highest  protection  (86.82%) at 303K  by using  I X 1 o-4 M

of thiourea. The high concentration .of thiourea  ( lxlo-3 M), enl1ances.

the  corrosion rates and  act  as dcpolariser for  the hydrogen  evolution

reaction,&n

Background: This study report the corrosion behavior of commercially pure titanium and Ti-6Al-4V alloy samples without coating and with hydroxyapatite, partial stabilized zirconia and mixture of partial stabilized zirconia and hydroxyapatite coating and comparison between them through electrochemical polarization tests in 37 0 C Hank's solution. Materials and methods: Electrophoretic deposition technique (EPD) was used to achieve the coating from each one of three types of the coating materials (HAP, PSZ and mixture of 50% HAP and 50%PSZ) on Cp Ti and Ti-6Al-4V alloy samples. The electrochemical corrosion test was performed when samples were exposed to Hank's solution prepared in the laboratory and the polarization potential, corrosion rate

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

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

The turning process has various factors, which affecting machinability and should be investigated. These are surface roughness, tool life, power consumption, cutting temperature, machining force components, tool wear, and chip thickness ratio. These factors made the process nonlinear and complicated. This work aims to build neural network models to correlate the cutting parameters, namely cutting speed, depth of cut and feed rate, to the machining force and chip thickness ratio. The turning process was performed on high strength aluminum alloy 7075-T6. Three radial basis neural networks are constructed for cutting force, passive force, and feed force. In addition, a radial basis network is constructed to model the chip thickness ratio. T

In this study, multi-objective optimization of nanofluid aluminum oxide in a mixture of water and ethylene glycol (40:60) is studied. In order to reduce viscosity and increase thermal conductivity of nanofluids, NSGA-II algorithm is used to alter the temperature and volume fraction of nanoparticles. Neural network modeling of experimental data is used to obtain the values of viscosity and thermal conductivity on temperature and volume fraction of nanoparticles. In order to evaluate the optimization objective functions, neural network optimization is connected to NSGA-II algorithm and at any time assessment of the fitness function, the neural network model is called. Finally, Pareto Front and the corresponding optimum points are provided and

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