Ferrite-pearlite Microstructure Research Articles

Medium-carbon dual-phase steels with spheroidized ferrite matrix

This study presents processing and properties of dual-phase (DP) steels, which contain islands of martensite among ferrite grains effectively reinforced by abundant carbide particles. To this end, a medium-carbon, low-alloyed steel plate with an initial ferrite-pearlite microstructure underwent cold rolling for 80% thickness reduction. Specimens obtained from the cold rolled strip were then heated in a neutralized salt bath at various temperatures ranging from 600 to 730 °C for 10 ks, followed by water quenching. The resulting microstructures and mechanical properties were analyzed. Preceding the formation of austenite during intercritical annealing, recrystallization led to the formation of a spheroidized ferrite microstructure with a high number of carbide particles dispersed mainly within the recrystallized ferrite grains. Initially, austenite grains formed on the carbides located at the boundaries between ferrite grains, followed by the formation of austenite on the carbides still present within the ferrite grains. Quenching from 715 °C resulted in a DP microstructure with intergranular martensite while increasing the annealing temperature to 725 °C led to the creation of intragranular martensite additionally. The study also focused on the distribution of alloying elements in the DP microstructure, revealing an enrichment of carbides with Mn, Cr, and Mo. Furthermore, an enrichment of martensite islands with manganese atoms was identified, but no comparable enrichment with carbon atoms was observed. The specimens annealed at 715–725 °C, which consisted of a martensite volume fraction ranging from 0.15 to 0.45, exhibited a superior balance of strength and ductility, as well as an outstanding work hardening exponent.

Development of intelligent methodologies perceiving microstructure and mechanical properties of hot rolled steels

Traditional metallographic characterization of steel microstructure can only roughly determine average grain size and phase fractions because it relies too much on researchers’ personal experiences. As a result, when the microstructure-property relationships are to be established, only the rough microstructural features can be taken into accounts, which is usually incapable of grasping the correct strengthening and toughening mechanisms. To solve this long-existed problem, an integrated system with the microstructural perception by deep learning (DL) and prediction of mechanical properties by machine learning (ML) was developed, which can quickly and precisely recognize typical ferrite-pearlite microstructures in the most used hot rolled plain carbon steels and make the predictions of their mechanical properties. In the microstructural perception, a U-shaped residual network was proposed to implement deep learning of metallographic images to obtain digital information such as the size and distribution of grains and the lengths of grain and second phase boundaries. As compared to the conventional deep learning algorithm, the pixel accuracy (PA) and frequency weighted intersection over union (FWIoU) of predictions were improved by 2.84% and 5.27%, respectively. On this basis, the relationships between mechanical properties and the detailed microstructural features were established by using the random forest (RF) algorithm. Compared with the predictions by rough features of average grain size and phase fractions, the root mean square errors (RMSE) of the yield strength (YS), tensile strength (TS), and elongation (EL) based on the test data were reduced by 71.53%, 67.51% and 53.4%, respectively. By using the accurate perceptron for microstructure and properties, changes of strengths and elongations with processing parameters and chemical compositions were analyzed in good agreement with physical laws. Also, this perceptron can be extended to high strength steels with microstructures comprised of ferrite and bainite or complex phases if the data of metallographic images and properties are available.

Effect of Cold Rolling Reduction Rate on the Microstructure and Properties of Q&P Steel with a Ferrite-Pearlite Initial Structure.

Quenching and partitioning (Q&P) steel has garnered attention as a promising third-generation automotive steel. While the conventional production (CP) method for Q&P steel involves a significant cumulative cold rolling reduction rate (CRRR) of 60-70%, the thin slab casting and rolling (TSCR) process has emerged as a potential alternative to reduce or eliminate the need for cold rolling, characterized with a streamline production chain, high-energy efficiency, mitigated CO2 emission and economical cost. However, the effect of the CRRR on the microstructure and properties of Q&P steel with an initial ferrite-pearlite microstructure has been overlooked, preventing the extensive application of TSCR in producing Q&P steel. In this work, investigations involving different degrees of CRRRs reveal a direct relationship between increased reduction and decreased yield strength and plasticity. Notably, changes in the microstructure were observed, including reduced size and proportion of martensite blocks, increased ferrite proportion and decreased retained austenite content. The decrease in yield strength was primarily attributed to the increased proportion of the softer ferrite phase, while the reduction in plasticity was primarily linked to the decrease in retained austenite content. This study provides valuable insights for optimizing the TSCR process of Q&P steel, facilitating its wider adoption in the automotive sector.

Contrast inversion of ferrite and pearlite in a sweet corrosion environment

In-situ optical imaging in a confocal Raman system of a pipeline steel under sweet corrosion environmental conditions typical of a commercial environment (NaCl brine, pH 6.8, temp, 80 °C, low oxygen, open circuit potential) revealed contrast inversion of ferrite and pearlite microdomains as compared to their 3% Nital etched counterpart. This behaviour is in excellent agreement with the time resolved mineralogy growth profile obtained from in-situ confocal Raman and also complemented by AFM and SEM analysis of the surface roughness and corresponding morphology. The data presented here provides new insight into the process of sweet corrosion scaling in a ferritic-pearlitic microstructure steel.

A novel training methodology for phase segmentation of steel microstructures using a deep learning algorithm

In this work, an efficient training methodology for the segmentation of ferrite – pearlite microstructures using Convolutional Neural Network (CNN) UNET machine learning architecture (a semantic classifier) is presented. However, CNN driven image segmentation requires very large number of labelled training microstructure, which is generally not available. A novel method is proposed for circumventing the above problem. First polycrystalline templates are created by simulating a 3D nucleation and growth model which follow Avrami kinetics. Subsequently, cropped images of pearlite and ferrite (from real microstructures) are randomly positioned on the individual grains of the polycrystalline templates, producing synthetic microstructures of varying fractions and varying scale of the two constituents. A few thousand synthetic microstructures were created using a small number of cropped images. The UNET trained on the synthetic training set when tested on real ferrite-pearlite microstructures gave an accuracy of about 98%, which substantiates the robustness of above technique. This paper introduces a universal training methodology for practical and efficient multiphase microstructure quantification based on supervised learning.

Microstructure‐Based Modeling and Estimation of Mechanical Properties of High‐Carbon Steel

Herein, attempts are made to estimate the mechanical properties using microstructure‐based finite element (FE) modeling and validate these results with the experimental results. The two high‐carbon steel specimens are hot‐rolled and air‐cooled to develop ferrite–pearlite microstructures. Different characterizations are utilized to observe microstructures as well as Vickers hardness and tensile tests are carried out to determine the mechanical properties. Two high‐resolution scanning electron micrographs are chosen for representative volume element‐based FE analyses for modeling the mechanical behavior of ferrite–cementite microstructure. Object‐oriented finite elements (OOF2) and Abaqus FEA 6.14 software are used to estimate the elastic and elastoplastic behavior assuming plane stress conditions. The correlation between cementite lamellae orientation and the predicted elastoplastic properties is investigated and compared with the experimental results. The influence of image size and mesh size on the predicted true stress–true strain behavior is discussed. The hard and brittle cementite lamellae face maximum stress while the softer ferrite matrix experiences maximum strain. It is found that strain accumulation is maximum at the interfaces of ferrite and cementite. These findings are further validated by the microvoid and crack initiation spots in the fracture surface and subsurface micrographs of broken tensile specimens.

Modeling fatigue life and hydrogen embrittlement of bcc steel with unified mechanics theory

The fatigue life estimation of metals operating in hydrogen-rich environments such as hydrogen pipelines, hydrogen-burning internal combustion engines, etc. is important. Studies in the past 40 years have shown that the diffusion of hydrogen into steel and other metals causes various chemical reactions, hydrogen-material interactions, and microstructural changes. That leads to hydrogen embrittlement (HE) and other types of hydrogen damage mechanisms including hydrogen environmentally assisted cracking (HEAC). Hydrogen embrittlement mechanisms, such as hydrogen-enhanced localized plasticity (HELP) and hydrogen-enhanced decohesion (HEDE) can have synergetic effects in steel depending on the hydrogen concentration level. At concentrations above and below the critical hydrogen concentration, HEDE and HELP dominate the embrittlement process, respectively. Different HE mechanisms result in distinctly different fracture modes, both ductile and fully brittle. The ultrasonic vibration fatigue life of bcc steel with a ferrite-pearlite microstructure pre-charged with hydrogen at different concentrations is studied. Modeling is based on the unified mechanics theory (UMT), which does not need any empirical dissipation/degradation potential function or an empirical void evolution function. However, the UMT does require analytical derivation of the thermodynamic fundamental equation of the material, which is used to calculate the thermodynamic state index (TSI) of the material. The UMT is ab-initio unification of the second law of thermodynamics and the universal laws of motion of Newton [1]. Dissipation/degradation evolution is governed by Boltzmann's second law of thermodynamics entropy formulation. The original contribution of this paper is the derivation of the thermodynamic fundamental equation of pre-hydrogen embrittled bcc steel subjected to ultrasonic very high cycle fatigue and the numerical simulations of fatigue life estimation using the proposed novel model. The synergetic interaction of hydrogen embrittlement mechanisms in steel and other metallic materials, i.e., HELP and HEDE at different hydrogen concentrations (HELP + HEDE model) is also studied, reviewed, and applied. The synergetic effects between ultrasonic vibration fatigue life and synergistically active hydrogen embrittlement mechanisms in low carbon bcc steel (S355J2+N, equivalent to ASTM A656), according to the HELP + HEDE model for HE, is modeled for the first time using UMT and also thoroughly discussed.

Research on Automatic Identification and Rating of Ferrite–Pearlite Grain Boundaries Based on Deep Learning

Grain size has a significant effect on the mechanical properties of metals. It is very important to accurately rate the grain size number of steels. This paper presents a model for automatic detection and quantitative analysis of the grain size of ferrite-pearlite two-phase microstructure to segment ferrite grain boundaries. In view of the challenging problem of hidden grain boundaries in pearlite microstructure, the number of hidden grain boundaries is inferred by detecting them with the confidence of average grain size. The grain size number is then rated using the three-circle intercept procedure. The results show that grain boundaries can be accurately segmented by using this procedure. According to the rating results of grain size number of four types of ferrite-pearlite two-phase microstructure samples, the accuracy of this procedure is greater than 90%. The grain size rating results deviate from those calculated by experts using the manual intercept procedure by less than Grade 0.5-the allowable detection error specified in the standard. In addition, the detection time is shortened from 30 min of the manual intercept procedure to 2 s. The procedure presented in this paper allows automatic rating of grain size number of ferrite-pearlite microstructure, thereby effectively improving the detection efficiency and reducing the labor intensity.

In-situ micro-cantilever bending studies of a white etching layer thermally induced on rail wheels

A complex and untraceable mechanical and thermal loading situation in rolling-sliding contacts can lead to the formation of white etching layers (WELs), depicting critical crack initiation sites. For our detailed studies, to obtain a holistic view of the microstructural characteristics and micro-mechanical properties, we prepared a WEL on a decommissioned (after 200,000 km service life) rail wheel by laser surface treatments with a defined energy input. This WEL is predominantly martensitic down to a depth of 30–40 μm, after which a transition to the deformed ferritic-pearlitic microstructure of the hypoeutectoid rail wheel steel is present. The martensitic region is with 6.98 ± 0.68 GPa significantly harder than the transition zone (5.17 ± 0.39 GPa) and the deformed ferritic-pearlitic base material (3.30 ± 0.33 GPa). In-situ V-notched micro-cantilever bending experiments of the martensitic (and thus most brittle) region show crack initiation and propagation – mostly along the boundaries of the martensitic grains – besides a plastic behavior. Applying the elastoplastic fracture mechanics allows to derive the local fracture toughness KIQ, which is 16.4 ± 1.2 MPam1/2 for this martensitic region of the WEL. The results outpoint the application of micro-cantilever bending tests in addition to hardness testing as a promising tool to discuss the relationship of microstructural characteristics with its micro-mechanical properties.

Zavarivanje cijevi iz niskougljeničnog čelika TIG postupkom

In this work the results of welding the pipes from low-carbon steel St 35.8 (Č.1214, DIN17175, W.Nr. 1.0305, EN-P235GH) by TIG procedure were shown. After welding, the microstructure analysis by means of optical microscope was performed. Microstructural analysis out on the base material, heat affected zone and melting zone was carried. It was found that the base material has ferrite-pearlite microstructure with hardness 148 HV10, while in the heat affected zone is present ferrite-pearlite microstructure with Widmanstatten ferrite in some places with hardness 176 HV10. A cast microstructure consisting of ferrite and bainite was observed in the melting zone with hardness 228.7 HV10.

Development of rolling procedures for pipes of K55 strength class at the laboratorial mill

Experimental results of physical simulation of the manufacturing technology of coiled rolled strip for pipes of K55 strength class (API SCT) at the laboratorial mill are presented. This manufacturing process includes hot rolling with accelerated cooling and coiling at high temperature. Melting of 4 laboratorial melts of K55 steel was conducted. Mechanical properties of pilot strips were examined. Investigation of microstructure via the methods of optical and scanning electronic microscopy was conducted. All samples have ferrite-pearlite microstructure which corresponded to the aimed microstructure. It was noted that molten metal without vanadium is more susceptible to forming of undesirable products of intermediate transformation stage. Recommendations on chemical composition and manufacturing technology of K55 steel on 2000 rolling mill are developed. Steel has the following aimed chemical composition for the main elements: 0.32 % C; 0.5 % Si; 1.05 % Mn; 0.05 % V. The following main technological parameters were recommended: heating up to 1240-1260 ºC; temperature after 5th stand 1060-1100 ºC; thickness of rolled semiproduct 30-40 mm; temperature before 6th stand 950-970 ºC; finishing rolling temperature 830-870 ºC; temperature in the 1st coiling group 650-680 ºC; coiling temperature 620-640 ºC.

Effect of Microstructure of Low-Alloy Steel on Corrosion Propagation in a Simulated CO2 Environment

The paper focuses on the analysis of initiation and propagation of CO2 corrosion in several samples of low-alloy steel with different microstructures using scanning electrochemical microscopy (SECM) and other microscopy techniques. It is found that the corrosion rate and the mode of corrosion are highly sensitive to the microstructure. The overall current density is much higher and more uniformly distributed for the tempered martensite structure than for samples having either a ferritic-pearlitic microstructure or a microstructure combining ferritic, bainitic and martensitic-austenitic regions. As a result, the sample with the tempered martensite structure undergoes uniform corrosion, while the other two samples undergo selective corrosion. The SECM maps show that regions of polygonal ferrite generate larger anodic currents than the pearlitic structure in the early stages of corrosion. The residual cementite provides greater cathodic surface areas after the initial dissolution of ferritic lamellae within pearlite, promoting galvanic corrosion and subsequently enhanced dissolution of ferritic lamellae. According to SECM data, the dissolution of iron in polygonal ferritic grains is 2.4 times faster than that of ferritic lamellae in pearlitic regions.

EBSD analysis of strain distribution and evolution in ferritic-Pearlitic steel under cyclic deformation at intermediate temperature

Strain accumulation as a result of cyclic loading affects the microstructure and mechanical performance of low-alloy steels under cyclic operation conditition. This manuscript presents a comprehensive analysis of a ferritic-pearlitic SA204 Grade C steel under strain-controlled low-cycle fatigue tests to understand the microstructural deformation and strain localization in the ferritic-pearlitic steel. Low-cycle fatigue tests were performed in a Gleeble® thermo-mechanical simulator at 0.008, 0.01, 0.015, and 0.02 strain amplitudes under an isothermal condition at 250 °C. The microstructure evolution during cyclic loading was evaluated using the samples from interrupted 0.01 strain amplitude tests. The LCF analysis shows strain localization at the ferrite-cementite interfaces and ferrite-pearlite interfaces. The characterization results using OM, SEM, EBSD, and nanoindentation analysis reveals the grain misorientation in the ferritic-pearlitic microstructure due to strain accumulation increases with the strain amplitudes and the loading cycles.

Microstructural, mechanical, and electrochemical analysis of carbon doped AISI carbon steels

The effect of carbon doping contents on the microstructure, hardness, and corrosion properties of heat-treated AISI steel grades of plain carbon steel was investigated in this study. Various microstructures including coarse ferrite-pearlite, fine ferrite-pearlite, martensite, and bainite were developed by different heat treatments i.e. annealing, normalizing, quenching, and austempering, respectively. The developed microstructures, micro-hardness, and corrosion properties were investigated by a light optical microscope, scanning electron microscope, electromechanical (Vickers Hardness tester), and electrochemical (Gamry Potentiostat) equipment, respectively. The highest corrosion rates were observed in bainitic microstructures (2.68–12.12 mpy), whereas the lowest were found in the fine ferritic-pearlitic microstructures (1.57–6.36 mpy). A direct correlation has been observed between carbon concentration and corrosion rate, i.e. carbon content resulted in an increase in corrosion rate (2.37 mpy for AISI 1020 to 9.67 mpy for AISI 1050 in annealed condition).

(Digital Presentation) Investigation of Microstructure Dependent Inhibitor Adsorption Mechanism on Carbon Steel By in Situ Atomic Force Microscopy

In the petroleum industry, organic surfactant type inhibitors have been widely applied in the oil and gas industry considering their high efficiency. Carbon steels with various carbide contents have also been used extensively as pipeline materials during the transport and storage of crude oil due to their excellent mechanical properties and low cost. The previous investigation of inhibition mechanism on carbon steel is limited by lack of surface characterization techniques at a molecular level. Atomic force microscopy (AFM) can not only provide localized visual observation, but can also achieve the detection of mechanical properties of an inhibitor film. In this study, in situ AFM contact mode friction imaging and in situ AFM tapping mode phase imaging techniques have been applied to investigate the influence of the ferritic-pearlitic microstructure of carbon steel on inhibitor adsorption mechanisms during CO2 corrosion under different inhibitor concentrations. At concentration above surface saturation, AFM contact mode friction images show a large friction contrast between inhibitor covered cementite structures and ferrite structures, while in the absence of inhibitor, this friction contrast almost disappears, indicating the inhibitor adsorption induced this difference. AFM tapping mode phase images indicate uniform adsorption of inhibitor on both cementite and ferrite structures.The differences observed in these AFM analyses indicate that the adhesion force of inhibitor molecules on cementite could be smaller than on ferrite, or the molecular orientations of inhibitor molecules adsorbed on cementite and ferrite structures could be different. The special adsorption behavior of inhibitor molecules on cementite means the carbide component of the microstructure could directly influence inhibitor adsorption and may decrease inhibitor efficiency. Simultaneous linear polarization resistance tests in electrochemical AFM (EC-AFM) cell indicates a maximum inhibition efficiency at concentration above saturation.Keywords : Contact mode AFM, friction contrast, tapping mode AFM, phase contrast, cementite, ferrite, organic inhibitor, adhesion force.Statement of importance:Studies related to inhibitor adsorption mechanisms on ferritc-pearlitic carbon steels can be connected with the practical issues that iron carbide can impair the corrosion inhibitor performance on carbon steels. This AFM work connects the corrosion inhibition effect with the carbon steel components at a molecular level for the first time. Physical explanations regarding the interactions between inhibitor molecules and carbon steel microstructures can also be provided with the assistance of molecular simulations.Figure caption: Contact and tapping mode AFM images of inhibitor film formed on UNS G1018 steel at 2 CMC (100ppm) tetradecyldimethylbenzylammonium inhibitor + 1 wt% NaCl. The contact mode friction image indicates a large friction contrast between inhibitor covered cementite and ferrite structure, while the tapping mode phase image indicates a negligible softness contrast between cementite and ferrite structure. Figure 1

Fatigue life assessment of low carbon API 5L X52 pipeline steels retired from long-term service

The fatigue lifetime of two API 5L X52 steels retired from long-term service was investigated. Both steels presented pearlite fragmentation, fine precipitate particles and spheroidized cementite at the grain boundaries, which is associated to microstructural degradation due to natural aging. Neither tensile strength nor hardness properties have significant variations respect to the design specifications; however, lower ductility was observed in the most degraded steel. Fatigue characterization was carried out by axial force-controlled tests, finding that the fatigue life is 77 % lower in the steel with the lowest ductility and highest microstructural degradation. Results indicate that the fatigue lifetime of a ferrite-pearlite microstructure is more affected by the microstructural degradation due to long-term service of the steel, in spite of traditional considerations as non-metallic inclusion or grain size. Hence, the natural aging effect is a main factor to be considered in the fatigue life of long-term exposure low carbon steels.

Supervised pearlitic–ferritic steel microstructure segmentation by U-Net convolutional neural network

The aim of this work is to develop an automated procedure based on machine learning capabilities for the identification of the pearlite islands within the two-phase pearlitic–ferritic steel. The input parameters for the custom implementation of a braided neural network are provided as a data set of scanning electron microscopy images of metallographic specimens. The procedures related to the processing of the data and the optimization parameters affecting the final architecture and effectiveness of the network learning stage are examined. The objective is to find the best solution to the problem of ferritic–pearlitic microstructure segmentation, allowing further processing during, e.g., 3D reconstruction of data from serial sectioning. The work examines the various quality of input data and different U-Net architectures to find the one that can identify pearlite islands with the highest precision. Two types of images acquired from secondary electron (SE) and electron backscattered diffraction (EBSD) detectors are used during the investigation. The work revealed that the developed approach offers improvements in metallographic investigations by removing the requirement for expert knowledge for the interpretation of image data prior to further characterization. It has also been proven that artificial neural networks based on the deep learning process using extensible U-Net network architectures and nonlinear learning tools can identify pearlite islands within a two-phase microstructure, while the overtraining level remains low. Convolutional neural networks do not require manual feature extraction and are able to automatically find appropriate search functions to recognize pearlite structure areas in the training process without human intervention. It was shown that the network recognizes areas of analyzed steel with satisfactory precision of 79% for EBSD and 87% for SE images.

Effect of nitrogen content on the mechanical properties and deformation behaviors of ferritic-pearlitic steels

The effect of nitrogen content (0.001 wt%, 0.009 wt%, 0.017 wt%) on the microstructure, mechanical properties and deformation behaviors of a medium-carbon ferritic-pearlitic steel is investigated in this study. The addition of nitrogen is shown to have little effect on the ferrite-pearlite microstructure and only marginally coarsens it because austenite grain growth is promoted. Although nitrogen is a strong element for solid solution strengthening, nitrogen addition only marginally improves the strength of the steel and has little effect on the ductility because fine Fe3N phases are precipitated during the tensile process. The toughness of the steel is markedly decreased by the addition of nitrogen because the dislocation locking effect caused by interstitial nitrogen atoms is enhanced. When the nitrogen content increases from 0.001 wt% to 0.017 wt%, the yield-point phenomenon in the tensile process is first strengthened and then weakened. The yield-point phenomenon is closely related to the dislocation behaviors in proeutectoid ferrite, and the different yield-point phenomena under different nitrogen contents are related to the dislocation locking effect caused by interstitial nitrogen atoms and to the dislocation pinning effect caused by Fe3N phases.

Influence of Different Pre-Heat Treatments on the Grain Size in the Core Region of Ultra-Clean Gear Steels

Abstract In a previous publication, the influence of various process steps during the case-hardening process on the resulting material properties of two distinct batches of ultra-clean gear steels were investigated. The steel batches were case-hardened in the as-delivered condition. However, in the industrial practice it is common that pre-heat treatments are done, such as annealing to a ferritic-pearlitic microstructure, or quenching and tempering, as well as forging as a process if for example larger gears are needed. It is known that the whole heat treatment process route can affect the grain size negatively. Therefore, this publication presents investigations into the effects of preheat treatments on the grain size in the core region of ultra-clean gear steels after case-hardening. The aim is to receive a deeper understanding on how the whole process route influences the grain size in the core region of ultra-clean gear steels.

Residual Stress Reduction with the LTT Effect in Low Carbon Manganese-Steel through Chemical Composition Manipulation Using Dissimilar Filler Material in Laser Beam Welding

This paper investigates the manipulation of chemical composition of a laser weld by dissimilar filler material and its effect on residual stress. The aim is to minimize residual stresses in the weld seam. In order to negate residual stresses, dissimilar combinations of low-carbon manganese steel (S235JR) base material with high-alloyed solid filler wires (G19 9 and G25 20), as well as similar combinations with low-alloyed solid filler wire G3Si1 are analyzed. The goal of the paper is to show that the so-called low-transformation-temperature effect can be used to induce residual compressive stresses in a weld without the use of specially manufactured filler wires. Chemical compositions are generated within a laser-beam-welding process by means of dilution, proving that the concept of in situ alloying is usable in order to affect the martensite formation on a weld. Dilatometry measurements show that a varying Cr and Ni content in a weld reduces the phase-transformation temperature and increases dilatation. EBSD analysis indicates that a fully martensitic weld with a negligible amount of retained austenite is created while the base material preserves its ferritic-pearlitic microstructure. Residual stress measurements with the hole-drilling method demonstrate a reduction in longitudinal tensile residual stresses, whereby the magnitude of the induced residual compressive stresses depend on the Ms temperature. As a result of this research, it was proven that a reduction in tensile residual stress by means of targeted alloying with conventional materials in low-carbon manganese steel is possible. Under the experimental conditions, residual stress in the weld seam could be reduced to 0 MPa. In some cases, even compressive residual stress in the weld could be achieved.