Wear behavior of ultrasonic impact treated S235JR steel

Abstract

In this study, wear behavior of ultrasonic impact treated S235JR steel was investigated. Samples were peened for different times (5, 15 and 30 minutes) by ultrasonic impact treatment. It was found that triple layers (nanocrystallization, plastic deformation and residual stress) formed on the treated surface. The thickness of the layers treated samples increased with increasing treatment time. It was also determined that surface roughness of treated samples decreased with increasing treatment time. All treated samples have significant surface hardness. Nanocrystallization layer on top of the treated surface has the highest hardness values in comparison with the hardness of the other layers. The treatment increases not only surface hardness, but also wear resistance of all treated samples. The maximum wear resistance was observed for the 30 min treated samples due to the high hardness and thickness of the nanocrystallization layers.

Effect of Thermal Treatment and Erosion Aggressiveness on Resistance of S235JR Steel to Cavitation and Slurry

“…Because of high costs of stainless steels, carbon steels are still used for some ship elements and hydraulic devices, despite their low corrosion resistance [ 3 , 4 ]. They are used because of good weldability, good strength properties and low price [ 5 , 6 ]. Nevertheless, carbon steels have an unsatisfactory amount of research into these types of degradation.…”

“…However, later investigations of a wider range of carbon steels (AISI 1018, AISI 1080, API X80, X100 and API X120 steels) did not confirm such relations [ 9 ]. Another common steel used in many industrial applications is S235 JR steel due to its very good weldability, good mechanical properties and low price [ 5 , 6 ]. Ultrasonic impact treatment applied with various duration (5, 15, and 30 min) on this steel increased hardness from 133 HV to 213, 214 and 224 HV (by 60.1%, 60.9%, and 68.4%) at top of the surface layer, respectively, and decreased mass loss by about 15%, 27%, and 50%, respectively, in wear tests [ 6 ].…”

“…The aim of the study was to investigate the effect of the type of erosion (cavitation and slurry) on the strength and degradation mechanism of S235JR carbon steel, and to show the differences in the destruction process between these types of erosion. S 235JR steel was chosen for its strong influence of hardness on mass loss and erosion resistance, as demonstrated by Kahraman et al [ 6 ]. For this reason, the S235JR carbon steel was tested in two states: as received and after heat treatment, which was applied to obtain different hardness of the steel.…”

A Study on a Multi-Objective Optimization Method Based on Neuro-Response Surface Method (NRSM)

“…Then, we predicted the performance of the design cases in a continuous response surface that was not directly computed. We used 15 sets of data to generate the response surface (Case 1, 2, 3, 5, 6, 7, 9, 10, 11, 13, 14, 15, 17, 18 and 19) and 4 sets of data to check its accuracy (Case 4,8,12 and 16). To increase the learning rate for a neural network, all data was used as a normalized value between 0.5 and 1.…”

“…These approximation models represent the relationship between inputs and outputs. The RSM is used to predict the system performance [3,4,5], but the method produces some errors in highly nonlinear problems [6,7,8].…”