For many years controlled shot peening was considered as a surface treatment. It is now clear that the performance of control shot peening in terms of fatigue depends on the balance between its beneficial (compressive residual stress and work hardening) and beneficial effects (surface hardening).

The overall aim of this paper is to study the effects of aggressive shot peening on fatigue life of 7075 – T6 aluminum alloy. The fatigue life reduction factor (LRF) due to the aggressive shot peening was established and empirical relations were proposed to describe the behavior of LRF, roughness and fatigue life. The benefits of shot peering in terms of fatigue life are dependent on the shot peening time (SPT).

This study evaluates the performance of magnetic abrasive finishing (MAF) of aluminum alloy in terms of achieving materials removal (MR). A vertical milling machine is used to perform the finishing process using a developed MAF unit that consists of an inductor made out of a 150 mm long and 20 mm diameter iron core wound with 1500 turns and 0.5 mm copper wire. The commutator and magnetic pole are attached at the top and bottom of the inductor, respectively. The required current is supplied using a DC power supply. The South Pole workpiece is a 100×50×3 mm³ plate of AA 1100 aluminum alloy, whereas the magnetic pole represented the North Pole. Pole rotational speed, applied current, and abrasive finishing time was selected as

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

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

Corrosion rate tests were carried out on carbon steel under concentration cells conditions of oxygen and sodium chloride. The effect of aeration in one compartment on the corrosion rate of both coupled metals was determined. In addition, the effects of time and temperatures on the corrosion rate of both coupled metals and galvanic currents between them were investigated. Corrosion potentials for the whole range of operating conditions under concentration cell conditions were also studied.   The results showed that under aeration condition, the formation of concentration cell caused a considerable corrosion rate of the Carbon steel specimens coupled in different concentrations of O₂ and NaCl due to the galvanic effect

The impact of a Schiff base namely 2-((thiophen-2-ylmethylene)amino)benzenethiol  to corrode mild steel in 1 M HCl  resolved was evaluated using different weight loss technique and scanning electron microscopy (SEM).different weight measurements to expand that the 2-((thiophen-2-ylmethylene) amino) benzenethiol  inhibits  the corrosion of mild steel through adsorbing  of  top for mild steel and block the active locality. The inhibitive impacts of 2-((thiophen-2-ylmethylene)amino)benzenethiol  increase with increasing concentration and decrease with increasing temperature. SEM to checking revealed that the alloy surface was quite unaffected and formed protective film on its surface. The investigated

The new ligand [N1,N4-bis((1H-benzo[d]Glyoxalin-2-yl)carbamothioyl)Butanedi amide] (NCB) derived from Butanedioyl diisothiocyanate with 2-aminobenz imidazole was used to prepare a chain of new metal complexes of Cr(III), Mn(II), Co(II), Ni(II), Cu(II), Pd(II), Ag(I), Cd(II) by general formula [M(NCB)]Xn ,Where M= Cr(III), n=3, X=Cl; Mn(II), Co(II), Ni(II), Cu(II), Pd(II), Cd(II) ,n=2 , X=Cl; Ag(I), n=1, X=NO3. Characterized compounds on the basis of 1H, 13CNMR (for (NCB), FT-IR and U.V spectrum, melting point, molar conduct, %C, %H, %N and %S, the percentage of the metal in complexes %M, Magnetic susceptibility, thermal studies (TGA),while its corrosion inhibition for mild steel in Ca(OH)2 solution is studied by weight loss. These measureme

Abstract

 This work involves studying the effect of adding some selective organic component mixture on corrosion behavior of pure Al and its alloys in condensed synthetic automotive solution (CSAS) at room temperature. This mixture indicates the increasing of octane number in previous study and in this study show the increasing in corrosion resistance through the decreasing in corrosion rate values.

Electrochemical measurements were carried out by potentiostat at 3 mV/sec to estimate the corrosion parameters using  Tafel extrapolation method, in addition to cyclic polarization test to know the pitting susceptibility of materials in tested medium.

The cathodic Tafel slope

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