Search results

This paper aims to investigate the influence of slurry concentration on the erosion behavior of AISI 5117 steel and high-chromium white cast iron by using a whirling-arm rig. In this study, the slurry erosion mechanism with particle concentration has been studied.

The tests were carried out with particle concentrations in the range of 1-7 Wt.%, and the impact velocity of slurry stream was 15 m/s. Silica sand with a nominal size range of 500-710 µm was used as an erodent. The study revealed that the failure mode was independent of concentration.

The results showed that the erosion rate decreases with the increase in particle concentration and the variation in the reduction depends on the material. It was found that the variation of fractal dimension calculated from slope of linearized power spectral density of eroded surface image for different concentrations can be used to characterize the slurry erosion intensity in a similar manner to the erosion rate. It was also found that the variation of fractal dimension versus concentration of sand has a general trend that does not depend on magnification factor.

Using the gravitational measurement and image analysis, the variation of the wear with slurry concentration has been analyzed to investigate the implicated mechanisms of erosion during the process.

The aim of this paper is to evaluate the effect of surface treatment on slurry erosion behavior of AISI 5,117 steel using artificial neural network (ANN) technique.

The slurry erosion wear behavior of electroless nickel-phosphorus (Ni-P) coated, carburized and untreated AISI 5,117 alloy steel was investigated experimentally and theoretically using ANN technique based on error back propagation learning algorithm.

From the obtained results, it can be concluded that the proposed AAN model can be successfully used for evaluating slurry erosion behavior of the Ni-P coated, carburized and untreated AISI 5,117 steel for wide range of operating conditions and Ni-P coating and carburizing improve the slurry erosion resistance of AISI 5,117 steel; however, the coating is more efficient.

Slurry erosion is a serious problem for the performance, reliability and service life of engineering components used in many industrial applications. To improve the performance of these components, engineering surface technologies have been attracting a great deal of attention. The extent of slurry erosion is dependent on a wide range of variables. To account all variables that effect on erosion behavior, prediction of erosion behavior by soft computational technique is one of the most important requirements. ANN has the ability to tackle the problem of complex relationships among variables that cannot be accomplished by traditional analytical methods.