scholarly journals Statistical Research of Stainless Austenitic Steel Grain Size Distribution after Screw Rolling

Materials ◽  
2020 ◽  
Vol 13 (21) ◽  
pp. 5048
Author(s):  
Mikhail Mikhailovich Skripalenko ◽  
Tatyana Viktorovna Zavyalova ◽  
Zbigniew Pater ◽  
Boris Alekseevich Romantsev ◽  
Stanislav Olegovich Rogachev ◽  
...  
Keyword(s):  
Grain Size ◽  
Stainless Steel ◽  
Size Distribution ◽  
Grain Size Distribution ◽  
Cross Section ◽  
Screw Rolling ◽  
Statistical Research ◽  
Strong Negative Correlation ◽  
Billet Cross Section ◽  
Stainless Austenitic Steel

Screw rolling of austenitic stainless-steel billets was conducted in two- and three-high mills. Statistical research results showed that, compared to heated but not rolled conditions, both screw rolling techniques provided a decrease of grain size, variance, grain size distribution asymmetry, and excess in the billet cross-section at the stationary stage of screw rolling. At that stage, grain size distribution after two-high screw rolling is closer to normal in terms of asymmetry and excess values compared to grain-size distribution after three-high screw rolling. A strong negative correlation between strain effective values and grain-size values for the cross-section of the rolled billets at the stationary stage was revealed for both two- and three-high screw rolling.

scholarly journals Three-dimensional Grain Size Distribution in SUS304 Stainless Steel.

1994 ◽  
Vol 34 (2) ◽  
pp. 186-190 ◽  
Author(s):  
Kiyotaka Matsuura ◽  
Youichi Itoh ◽  
Masayuki Kudoh ◽  
Tatsuya Ohmi ◽  
Kuniyoshi Ishii
Keyword(s):  
Grain Size ◽  
Stainless Steel ◽  
Size Distribution ◽  
Grain Size Distribution ◽  
Three Dimensional ◽  
Sus304 Stainless Steel

scholarly journals Grain size distribution after similar and dissimilar gas tungsten arc welding of a ferritic stainless steel

2015 ◽  
Vol 51 (1) ◽  
pp. 61-66
Author(s):  
E. Ranjbarnodeh ◽  
S. Serajzadeh ◽  
A.H. Kokabi ◽  
A. Fischer
Keyword(s):  
Grain Size ◽  
Stainless Steel ◽  
Size Distribution ◽  
Grain Growth ◽  
Grain Size Distribution ◽  
Ferritic Stainless Steel ◽  
Arc Welding ◽  
Gas Tungsten Arc Welding ◽  
Gas Tungsten Arc ◽  
Gas Tungsten

In this study, gas tungsten arc welding of ferritic stainless steel and grain size distribution in heat affected zone of the welded samples were investigated. Both similar and dissimilar arc welding operations were considered where in dissimilar welding joining of stainless steel to mild steel was examined. In the first stage, a three-dimensional model was developed to evaluate temperature field during and after arc welding while the model was performed using finite element software, ANSYS. Then, the effects of welding heat input and dissimilarity of the joint on the weld pool shape and grain growth in HAZ of stainless steel was investigated by means of model predictions and experimental observations. The results show that the similar joint produces wider HAZ and considerably larger grain size structure while in the dissimilar welds, the low carbon part acts as an effective heat sink and prevents the grain growth in the stainless steel side as well reduces the welding maximum temperature.

In situ SEM analysis for deformation mechanism of micro/nanostructured 304 stainless steel with high strength and good plasticity

2018 ◽  
Vol 32 (17) ◽  
pp. 1850182 ◽  
Author(s):  
Jie Sheng ◽  
Peiqing La ◽  
Jiaqiang Su ◽  
Junqiang Ren ◽  
Jiqiang Ma ◽  
...  
Keyword(s):  
Grain Size ◽  
Stainless Steel ◽  
Size Distribution ◽  
Grain Size Distribution ◽  
Deformation Mechanism ◽  
Rolling Reduction ◽  
304 Stainless Steel ◽  
Bimodal Grain Size ◽  
Bimodal Grain Size Distribution

Bulk micro/nanostructured 304 austenitic stainless-steel plates with bimodal grain size distributions were prepared by Alumina Thermite Reaction at various temperatures and extents of rolling deformation. Rolling cogging of the sheet was performed with a rolling reduction of 40% at 1000[Formula: see text]C followed by rolling reduction of 80% at 700[Formula: see text]C. The strength and plasticity of the resulting micro/nanostructured 304 stainless steels with bimodal grain size distribution achieved the best matching, with tensile strength, yield strength, and elongation of 1410 MPa, 723 MPa and 15.3%, respectively. To better understand the deformation mechanism of this micro/nanostructured stainless steel sample, an in situ scanning electron microscopy technique was adopted. The crack initiation, propagation, and fracture were dynamically observed and recorded during the tensile deformation. Our results revealed that a stress concentration near the preset notch served as the initiation source and that microcracks were formed in the grain boundaries between micro- and nano-grains and then spread to the microcrystalline region until passing through the microcrystalline region or until passivation occurred in the microcrystalline region. The microcracks not only caused serious damage to the specimen but also generated back stress, which could lead to hardening of material, thereby enhancing the global ductility. Finally, the mechanism responsible for the enhanced plasticity and strength of the micro/nanostructured 304 stainless steel with a bimodal grain size distribution was analyzed and combined with the fracture morphology.

Predicting the Microstructural Evolution of an Austenitic Stainless Steel by Hybrid Modeling

2014 ◽  
Vol 783-786 ◽  
pp. 2154-2159 ◽  
Author(s):  
Andreas Johnsson ◽  
Mats Karlberg
Keyword(s):  
Heat Treatment ◽  
Grain Size ◽  
Stainless Steel ◽  
Austenitic Stainless Steel ◽  
Cold Rolling ◽  
Size Distribution ◽  
Grain Size Distribution ◽  
Sheet Material ◽  
Annealing Heat Treatment ◽  
Cold Rolled

During the annealing heat treatment following cold rolling of a 304L austenitic stainless steel sheet material, the material goes through changes in microstructure and mechanical properties. The cold rolling history together with the time/temperature trajectory in the annealing furnace can be used to model the final microstructure. In this work, physically based models for recrystallization and the following grain growth was created for the prediction of the microstructure evolution-both grain size and grain size distribution-, and an artificial neural network, ANN, was added for secondary effects. This is more commonly referred to as a hybrid model. The microstructure hybrid model was tested and validated against cold rolled and annealed production sheet material of various thicknesses and reductions, where the grain size and grain size distribution was measured by Electron Back Scatter Diffraction, EBSD. The recrystallization and grain growth parameters and functionality were fitted for non-isothermal conditions, against experimental tests of cold rolled material. Given process history and time/temperature data from the annealing heat treatment, the model can predict the microstructure, average grain size and grain size distribution with high accuracy and the executing time is short which makes it suitable for in-line use.

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