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The purpose of the research was to obtain an arc welded joint of a preliminary quenched high-carbon wear resistant steel without losing the structure that is previously obtained by heat treatment. 120Mn3Si2 steel was chosen for experiments due to its good resistance to mechanical wear. The fast cooling of welding joints in water was carried out right after welding. The major conclusion is that the soft austenitic layer appears in the vicinity of the fusion line as a result of the fast cooling of the welding joint. The microstructure of the heat affected zone of quenched 120Mn3Si2 steel after welding with rapid cooling in water consists of several subzones. The first one is a purely austenitic subzone, followed by austenite + martensite microstructure, and finally, an almost fully martensitic subzone. The rest of the heat affected zone is tempered material that is heated during welding below A1 critical temperature. ISO 4136 tensile tests were carried out for the welded joints of 120Mn3Si2 steel and 09Mn2Si low carbon steel (ASTM A516, DIN13Mn6 equivalent) after welding with fast cooling in water. The tests showed that welded joints are stronger than the quenched 120Mn3Si2 steel itself. The results of work can be used in industries where the severe mechanical wear of machine parts is a challenge.

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The effect of heat treatment and chromium contents (up to 9.1 wt.%) on the wear resistance of spheroidal carbide cast iron (9.5 wt.% V) was studied using optical and scanning electron microscopy, X-ray diffractometry, dilatometry and three-body abrasive testing. It was found that quenching from 760 °C and 920 °C improved the alloys’ wear resistance compared to the as-cast state due to the formation of metastable austenite transforming into martensite under abrasion. The wear characteristics of alloys studied are 1.6 – 2.3 times higher than that of reference cast iron (12 wt.% V) having stable austenitic matrix. Chromium addition decreases surface damage due to the formation of M7C3 carbides, while it reduces wear resistance owing to austenite stabilization to abrasion-induced martensite transformation. The superposition of these factors results in decreasing the alloys’ wear behaviour with chromium content increase.

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This article aims to discusses machine learning modelling using a dataset provided by the LANL (Los Alamos National Laboratory) earthquake prediction competition hosted by Kaggle. The data were obtained from a laboratory stick-slip friction experiment that mimics real earthquakes. Digitized acoustic signals were recorded against time to failure of a granular layer compressed between steel plates. In this work, machine learning was employed to develop models that could predict earthquakes. The aim is to highlight the importance and potential applicability of machine learning in seismology The XGBoost algorithm was used for modelling combined with 6-fold cross-validation and the mean absolute error (MAE) metric for model quality estimation. The backward feature elimination technique was used followed by the forward feature construction approach to find the best combination of features. The advantage of this feature engineering method is that it enables the best subset to be found from a relatively large set of features in a relatively short time. It was confirmed that the proper combination of statistical characteristics describing acoustic data can be used for effective prediction of time to failure. Additionally, statistical features based on the autocorrelation of acoustic data can also be used for further improvement of model quality. A total of 48 statistical features were considered. The best subset was determined as having 10 features. Its corresponding MAE was 1.913 s, which was stable to the third decimal point. The presented results can be used to develop artificial intelligence algorithms devoted to earthquake prediction.

Tensile/impact behaviour of lower bainite obtained in high-Si steel 55Si3Mn2CrMoVNb was studied using SEM, TEM, and XRD. Specimens were austenitized at 900 • C and isothermally treated at 250, 270, and 300 • C with holding up to 600 min. The heat treatment results in the formation of cementite-free lower bainite/retained austenite structure, where retained austenite was found as blocky "islands" and interlaths "films". The width of bainitic ferrite laths decreases from 170-240 µm to 45-80 µm with holding temperature decreasing. This results in increasing UTS (to 1700 MPa) and hardness (to 52 HRC). The optimal combination of mechanical properties (UTS 1397-1522 MPa, hardness 45-47 HRC, total elongation 18-21 %, U-notched impact toughness 105-139 J cm −2 ) refers to holding at 300 • C to be associated with higher amount of retained austenite (30-33 %). With prolonging the bainitizing duration the hardness and ductility decreases while impact toughness increases. Prolonged holding at 300 • C leads to a continuation of bainite transformation and precipitation of transitional carbides within ferrite laths. K e y w o r d s : carbide-free lower bainite, retained austenite, phase transformations, microstructure, mechanical properties

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