Influence of ferrite matrix and precipitation status on the mechanical properties of low carbon low alloy steel during high temperature tension

2016 ◽  
Vol 678 ◽  
pp. 1-9 ◽  
Author(s):  
Lei Cheng ◽  
Qing-wu Cai ◽  
En-tao Dong ◽  
Xiao Li
2019 ◽  
Vol 10 (6) ◽  
pp. 1301-1308 ◽  
Author(s):  
S. V. Korotovskaya ◽  
O. V. Sych ◽  
E. I. Khlusova ◽  
E. A. Yashina

2020 ◽  
Vol 56 (5) ◽  
pp. 3995-4005
Author(s):  
Guofang Liang ◽  
Qiyang Tan ◽  
Yingang Liu ◽  
Tao Wu ◽  
Xianliang Yang ◽  
...  

Metals ◽  
2018 ◽  
Vol 8 (10) ◽  
pp. 807 ◽  
Author(s):  
Zhenjia Xie ◽  
Lin Xiong ◽  
Gang Han ◽  
Xuelin Wang ◽  
Chengjia Shang

In this work, we elucidate the effects of tempering on the microstructure and properties in a low carbon low alloy steel, with particular emphasis on the thermal stability of retained austenite during high-temperature tempering at 500–700 °C for 1 h. Volume fraction of ~14% of retained austenite was obtained in the studied steel by two-step intercritical heat treatment. Results from transmission electron microscopy (TEM) and X-ray diffraction (XRD) indicated that retained austenite had high thermal stability when tempering at 500 and 600 °C for 1 h. The volume fraction was ~11–12%, the length and width remained ~0.77 and 0.21 μm, and concentration of Mn and Ni in retained austenite remained ~6.2–6.6 and ~1.6 wt %, respectively. However, when tempering at 700 °C for 1 h, the volume fraction of retained austenite was decreased largely to ~8%. The underlying reason could be attributed to the growth of austenite during high-temperature holding, leading to a depletion of alloy contents and a decrease in stability. Moreover, for samples tempered at 700 °C for 1 h, retained austenite rapidly transformed into martensite at a strain of 2–10%, and a dramatic increase in work hardening was observed. This indicated that the mechanical stability of retained austenite decreased.


Author(s):  
D.S. Kotenko

Introduction. The use of different mathematical approaches to assessing and forecasting the quality characteristics of materials for different purposes is always relevant. The urgency of solving problems and problems of modern materials science with the use of methods of mathematical modeling allows to optimize technological processes of production, to determine in a short period of time the set parameters with minimal time and material costs. In the work using the method of regression analysis, the strength criteria of low-carbon low-alloy steel depending on the characteristics of the structure were evaluated. Materials and methods. Samples of Ст3пс steel grade made of a circle with a diameter of 24 mm were selected as the material for the study. The structure and mechanical properties were investigated at three reference points: at a distance of 0 mm from the center of the sample, 6 mm from the center of the sample and 12 mm from the center of the sample. The steel was investigated in the state of factory delivery, and after two modes of heat treatment to obtain ferritic-perlite and bainite structure. The following properties were determined: microhardness, tensile strength and yield strength, hardness and toughness at room temperature. The results of the experiment. Models for estimating mechanical properties were obtained using regression analysis. Models describing the relationship between the microhardness of pearlite and its area (R2 = 0.8366) in the state of factory delivery have a relatively high correlation coefficient; the score and the ultimate strength (R2 = 1.0) and yield strength (R2 = 0.8669) of steel after cooling in an oil medium; hardness and area of pearlite after hardening steel in the pearlite region (R2 = 0.7215). Conclusions. The practical significance of the work performed is the ability to perform a rapid analysis of the properties of rolled metal from steel Ст3пс based on determining the area of the structural elements and their scoring. However, it should be noted that the existing discrepancy between the results of the experiment and the forecast using the obtained models may be due to the influence of other factors. Such factors include the influence of chemical composition, incompleteness of formal axiomatics, which occurs when estimating the geometry of complex structural elements. Keywords: low-alloy steel; structure; chemical composition; mechanical properties; regression model; properties forecast


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