Numerical assessment of residual stresses induced by combining turning-burnishing (CoTuB) process of AISI 4140 steel using 3D simulation based on a mixed approach

2018 ◽  
Vol 97 (5-8) ◽  
pp. 1897-1912 ◽  
Author(s):  
Anis Rami ◽  
Achref Kallel ◽  
Syrine Djemaa ◽  
Tarek Mabrouki ◽  
Salem Sghaier ◽  
...  
2021 ◽  
Vol 5 (3) ◽  
pp. 73
Author(s):  
Ewald Kohls ◽  
Carsten Heinzel ◽  
Marco Eich

During surface grinding, internal material loads are generated, which take effect on the surface and subsurface zone of AISI 4140 steel. High thermal loads can result in specific material modifications, e.g., hardness reduction and tensile residual stresses, due to inappropriate combinations of system and process parameters which influence the functional performance of the ground component in a negative way. In order to avoid this damaging impact due to the thermal effect, an in-depth understanding of the thermal loads and the resulting modifications is required. This relationship is described in the concept of Process Signatures applied in this paper. Experimentally determined temperature-time histories at various depths below the surface were used to estimate the thermal loads at the surface and subsurface using a numerical approach based on the finite element method (FEM). The results show that the hardness change during surface grinding correlates with the maximum temperature rate at given maximum temperatures. In addition, correlations between the hardness change and the Hollomon–Jaffe parameter are identified, taking into account both the absolute temperature and its evolution over time. Furthermore, it was shown that the surface residual stresses correlate with the maximum local temperature gradients at the surface if no detectable tempering of the microstructure takes place.


2019 ◽  
Vol 61 (12) ◽  
pp. 701-705
Author(s):  
S Çalışkan ◽  
C Hakan Gür

The performance of engineering components under conditions of fatigue can be improved by shot peening. The location and magnitude of the highest residual compressive stress, the depth of the compression zone and the stability of the residual stress state during cyclic loading are critical parameters for maximum utilisation of the advantageous influence of shot peening on fatigue performance. For accurate assessment of fatigue lifetime, residual stresses should be considered because they are algebraically summed with applied stresses. Therefore, the development of a non-destructive testing (NDT) method that has the ability to rapidly monitor surface residual stresses has industrial importance when verifying the achievement of the design goals of shot peening. The utilisation potential of the magnetic Barkhausen noise (MBN) technique in shot peening of ferromagnetic steels includes automated sorting of the components and measurement of surface residual stress. This study aims to establish the correlation between MBN emission and the fatigue life of shot-peened AISI 4140 steel.


2018 ◽  
Vol 60 (2) ◽  
pp. 149-155 ◽  
Author(s):  
Turhan Kursun ◽  
Tanju Teker

2013 ◽  
Vol 20 (03n04) ◽  
pp. 1350033 ◽  
Author(s):  
ŞERAFETTIN EKINCI ◽  
AHMET AKDEMIR ◽  
HUMAR KAHRAMANLI

Nitriding is usually used to improve the surface properties of steel materials. In this way, the wear resistance of steels is improved. We conducted a series of studies in order to investigate the microstructural, mechanical and tribological properties of salt bath nitrided AISI 4140 steel. The present study has two parts. For the first phase, the tribological behavior of the AISI 4140 steel which was nitrided in sulfinuz salt bath (SBN) was compared to the behavior of the same steel which was untreated. After surface characterization using metallography, microhardness and sliding wear tests were performed on a block-on-cylinder machine in which carbonized AISI 52100 steel discs were used as the counter face. For the examined AISI 4140 steel samples with and without surface treatment, the evolution of both the friction coefficient and of the wear behavior were determined under various loads, at different sliding velocities and a total sliding distance of 1000 m. The test results showed that wear resistance increased with the nitriding process, friction coefficient decreased due to the sulfur in salt bath and friction coefficient depended systematically on surface hardness. For the second part of this study, four artificial neural network (ANN) models were designed to predict the weight loss and friction coefficient of the nitrided and unnitrided AISI 4140 steel. Load, velocity and sliding distance were used as input. Back-propagation algorithm was chosen for training the ANN. Statistical measurements of R2, MAE and RMSE were employed to evaluate the success of the systems. The results showed that all the systems produced successful results.


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