Steel Processing Research Articles

Ultrasmooth Micromilling of Stainless Steel by Ultrashort Pulsed Laser Ablation Using MHz Bursts.

Ultrashort pulsed (USP) laser burst ablation has attracted numerous interests for its great potential in enhancing ablation efficiency and reducing the heat-affected zone. However, little attention has been paid to the influence of burst ablation on the processed surface quality. To fill this research gap, the present study conducts a comprehensive investigation on the surface processing of stainless steel using ultrashort pulsed laser burst ablation. Systematic experiments have been carried out to investigate influences of pulse number per burst (PpB), pulse fluence, and burst overlap ratio on surface quality and ablation efficiency. A two-dimensional model has been developed to unveil the fundamental thermodynamic process and evolution of ablation and melting in material during USP laser burst ablation. Compared to single-pulse ablation, the optimum ablation efficiency decreases with increasing PpB by less than 30% in burst ablation. Despite reduced ablation efficiency, burst-mode ablation can generate much better surface quality, achieving an ultrasmooth surface with an Sa roughness as low as 0.13 μm. Burst ablation generates distinctive surface structures compared to single-pulse ablation, and their formation mechanisms are scrutinized. The thickness of the surface melting layer is unveiled to determine surface morphology. Based on transmission electron microscopy (TEM) analysis and numerical simulation, a melting layer thickness between 100 and 320 nm is found to result in smooth surfaces. This work highlights the advantage of burst-mode ablation in achieving ultrasmooth surfaces on stainless steel and unveils the fundamental mechanisms of surface structures formation in USP laser burst ablation.

Modeling and Simulation of Dynamic Recrystallization Microstructure Evolution for GCr15 Steel Using the Level Set Method.

The microstructure of metallic materials plays a crucial role in determining their performance. In order to accurately predict the dynamic recrystallization (DRX) behavior and microstructural evolution during the hot deformation process of GCr15 bearing steel, a microstructural evolution model for the DRX process of GCr15 steel was established by combining the level set (LS) method with the Yoshie-Laasraoui-Jonas dislocation dynamics model. Firstly, hot compression tests were conducted on GCr15 steel using the Gleeble-1500D thermal simulator, and the hardening coefficient k1 and dynamic recovery coefficient k2 of the Yoshie-Laasraoui-Jonas model were derived from the experimental flow stress data. The effects of temperature, strain, and strain rate on DRX behavior and grain size during the hot working process of GCr15 steel were investigated. Through secondary development of the software, the established microstructural evolution model was integrated into the DIGIMU® software. Metallographic images were imported in situ to reconstruct its initial microstructure, enabling GCr15 steel DRX microstructure finite element simulation of the hot compression process. The predicted mean grain size and flow stress demonstrated a strong correlation and excellent agreement with the experimental results. The results demonstrate that the established DRX model effectively predicts the evolution of the DRX fraction and average grain size during the hot forging process and reliably forecasts DRX behavior.

Microstructure evolution of forsterite film during the high-temperature annealing process in grain-oriented silicon steel

Microstructure evolution of forsterite film during the high-temperature annealing process in grain-oriented silicon steel

Preface to the Special Issue on “New Developments in High Temperature Processing of Steels and Related Materials Leading the Sustainable Society, and Key Properties of High Temperature Melts”

Preface to the Special Issue on “New Developments in High Temperature Processing of Steels and Related Materials Leading the Sustainable Society, and Key Properties of High Temperature Melts”

Influence of point defects on intergranular fracture of steel

At present, it has been established that the ageing process of pipe steel is multistage. The first stage is characterized by the release of carbon atoms from the metal grains. The second stage is determined by the removal of inter-nodal atoms to the grain boundaries. This removal mechanism is related to the diffusion of carbon through the inter-domain space, facilitated by point defects such as vacancies. The most optimistic estimates give an unrealistically long time of the ageing process of steel. Thus the diffusion mechanism remains unclear.The aim of this study is to construct a mechanism that would adequately describes this phenomenon. The authors believe such a mechanism should be related to point defects (vacancies). The leading method used in this research is theoretical analysis, which has led to the proposal of an effective way of influence of point defects in intergranular corrosion failure of steel is proposed.Under conditions of uphill diffusion in the linear approximation, mass transfer develops slowly and cannot enrich the adjacent grain boundary layers with impurities. The presence of defects makes the diffusion nonlinear.This study considers thermodefects generated by a temperature gradient. Based on changes in the magnetic properties of the samples, conclusions about the formation of the structure with the participation of carbon impurities displaced in the process of hydrogen introduction were made.The results of this study can be used in the development of methods of increase of service life of pipe steels.

MODELING AND MEASUREMENT OF FLARING OF OUTER FLANGES ON PIPE BLANKS IN THE ROLL STAMPING PROCESS USING THE FINITE ELEMENT METHOD

Roll stamping (RS) is an efficient process for shaping steels and alloys in a cold state, enabling the production of complex-profile parts. To improve RS processes, it is crucial to study the factors influencing material deformation and the stress-strain state of the blank. Research on flaring of outer flanges on pipe blanks is labor-intensive due to the complexity of accounting for real conditions of localized deformation and the contact interactions between the tool and the blank. An alternative to experimental methods is the use of simulation modeling with the finite element method (FEM). In this study, FEM was applied to model flange flaring on pipe blanks, based on a model consisting of a pipe blank, a conical roller, a die, and a mandrel. Calculations were performed using 8-node finite elements, with the tool modeled as a perfectly rigid body. Contact between the roller and the blank was defined using an automatic "surface-to-surface" contact algorithm. The results of the calculations revealed the deformation intensity in the flange cross-section after 55 seconds of compression, as well as the material microstructure and the distribution of deformation intensity and stresses. Comparison of the simulation results with experimental data showed that discrepancies in flange shape and deformation intensity distribution were within an error margin not exceeding 10–12%. Additionally, changes in the friction coefficient did not significantly affect the stress state on the free surface of the flange. The study confirmed good agreement between the stress-strain parameters obtained through simulation and experimental data, although some differences were observed for internal points in the flange cross-section. These results demonstrate the high efficiency of using FEM to model the flange flaring process in RS, allowing for more accurate prediction of deformation characteristics and the stress-strain state of the blank material.

Surface defect detection of steel strip at low resolution based on SAC-YOLOv5

Abstract Surface defects are common occurrences in the production process of strip steel. The development of automatic and efficient intelligent detection algorithms for strip steel is crucial for enhancing product quality and operational safety. While deep learning-based defect detection techniques have achieved satisfactory accuracy when applied to high-resolution images, obtaining a sufficient number of high-resolution images in practical engineering scenarios is challenging. The degradation of image quality often results in a significant decline in the performance of existing detection techniques. To address these challenges, this paper proposes SAC-you only look once (YOLO)v5-based surface defect detection model specifically designed for low-resolution strip steel images. SAC, SIoU based K-Means++, asymmetric convolutional neural networks (ACNNs) and composite down-sampling feature fusion block (CDFFB). Firstly, we introduce an anchor boxes clustering algorithm called Shape-IoU based K-Means++ (SIoU based K-Means++) to enhance the efficiency of anchor boxes regression. Secondly, we construct an ACNNs for multi-level feature extraction. Utilizing reparameterization techniques, we reduce the inference resources required by the model. Additionally, we propose a CDFFB which enhances key texture information and improves the model’s nonlinear fitting ability. Experimental analysis using NEU-DET surface defect data demonstrates the superiority of the proposed model in processing low-resolution strip steel surface defect images. In comparison to YOLOv8, YOLOv7, YOLOX, YOLOv3SPP, CenterNet and Faster RCNN, SAC-YOLOv5 outperforms all other models in terms of both speed and accuracy.

Effect of Heat Supplied to the Joint in the MAG Welding Process of Ferritic-Austenitic Stainless Steel 1.4462 on the Size of the Cross-Sectional Area of the Joints.

In this study, the relationships between the values of the parameters included in heat input (welding current, arc voltage and welding speed) and their effects on the size of the cross-sectional areas of welds in joints made of ferritic-austenitic stainless steel using the GMAW method were determined. An attempt was also made to determine to what extent it will be possible to predict the properties of fabricated welded joints using the functional relationship describing the effect of the value of heat input on the size of the cross-sectional area of welds. The analysis of the developed mathematical models shows their suitability for explaining (and predicting) the sizes of the cross-sectional areas of welded joints depending on the values of the input parameters of the welding process. Determining the regression function and making a three-dimensional plot of it (response surface) can provide a starting point for optimizing the parameters of the welding process. The results have practical relevance, supporting weld quality control and process design in industrial conditions, especially in applications requiring high strength and corrosion resistance, in industries such as construction and offshore.

Study of Process, Microstructure, and Properties of Double-Wire Narrow-Gap Gas Metal Arc Welding Low-Alloy Steel.

Narrow-gap arc welding is an efficient method that significantly enhances industrial production efficiency and reduces costs. This study investigates the application of low-alloy steel wire EG70-G in narrow-gap gas metal arc welding (GMAW) on thick plates. Experimental observations were made to examine the arc behavior, droplet transition behavior, and weld formation characteristics of double-wire welding under various process parameters. Additionally, the temperature field of the welding process was simulated using finite element software (ABAQUS 2020). Finally, the microstructure and microhardness of the fusion zone in a double-wire, single-pass filled joint under the different welding speeds were compared and analyzed. The results demonstrate that the use of double-wire GMAW in narrow-gap welding yielded positive outcomes. Optimal settings for wire feeding speed, welding speed, and double-wire lateral spacing significantly enhanced welding quality, effectively preventing side wall non-fusion and poor weld profiles in the welded joints. The microstructure of the fusion zone produced at a higher welding speed (11 mm/s) was finer, resulting in increased microhardness compared to welds obtained at a lower speed (8 mm/s). This is attributed to the shorter duration of the liquid molten pool and the faster cooling rate associated with higher welding speed. This research provides a reference for the practical application of double-wire narrow-gap gas metal arc welding technology.

Determining best dressing parameters for internal grinding SKD11 steel using EAMR technique

The article conducts a research study on the use of Multi-Criteria Decision-Making (MCDM) in the internal grinding process of SKD11 tool steel. The aim is to identify the optimal input process parameters for the dressing process in order to minimize surface roughness (SR) and maximize wheel life (Lw). The EAMR strategy was employed to address the MCDM task, whereas the Entropy method was utilized to determine the weights of the criterion. The experiment also included the analysis of six input process parameters: coarse dressing depth, coarse dressing passes, fine dressing depth, fine dressing passes, non-feeding dressing, and dressing feed rate. The experiment was performed using an L16 orthogonal array and the Taguchi method. The wheel's durability and the roughness of the sample's surface were quantified and recorded for analysis in the MCDM problem. The research findings have identified the optimal dressing solutions for internal cylindrical grinding.).

Predicting Surface Roughness and Grinding Forces in UNS S34700 Steel Grinding: A Machine Learning and Genetic Algorithm Approach to Coolant Effects

In today’s tech world of digitalization, engineers are leveraging tools such as artificial intelligence for analyzing data in order to enhance their capability in evaluating product quality effectively. This research study adds value by applying algorithms and various machine learning techniques—such as support vector regression, Gaussian process regression, and artificial neural networks—on a dataset related to the grinding process of UNS S34700 steel. What sets this study apart is its consideration of factors like three types of grinding wheels, four distinct cooling solutions, and seven varied depths of cut. These parameters are assessed for their impact on surface roughness and grinding forces, resulting in the conversion of information into insights. A relational equation with 25 coefficients is developed, using optimized algorithms to predict surface roughness with an 85 percent accuracy and grinding forces with a 90 percent accuracy rate. Learning from machine models like the Gaussian process regression exhibited stability, with an R2 value of 0.98 and a mean accuracy of 93 percent. Artificial neural networks achieved an R2 value of 0.96, and an accuracy rate of 90 percent. These findings suggest that machine learning techniques are versatile and precise when dealing with datasets. They align well with digitalization and predictive trends. In conclusion; machine learning provides flexibility and superior accuracy for predicting data trends compared to the formulaic approach, which is contained to existing datasets only. The versatility of machine learning highlights its significance in engineering practices for making data-informed decisions.

Multi-Objective Optimization of the Surface Grinding Process for Heat-Treated Steel

This paper effectively integrates Taguchi, Response Surface Methodology (RSM), and Genetic Algorithm (GA) approaches for both single and multi-objective optimization, delivering low-cost, high-effectiveness solutions for grinding. It examines the effects of three factors—depth of cut in coarse grinding, depth of cut in fine grinding, and the number of spark-outs—on three objectives: surface roughness, grinding time, and the deviation between the desired and actual grinding depth for SKD61 steel. Through in-depth analysis, the paper describes the impact of these factors and their interactions with the responses. It also proposes the optimal parameter setup for each objective. The optimal grinding time is achieved at 950 seconds with a coarse grinding depth of 0.007 mm, fine grinding depth of 0.004 mm, and zero spark-out. The minimal deviation and surface roughness were obtained at 0 mm and 0.144 µm, respectively, using the optimal setup of a coarse grinding depth of 0.004 mm, fine grinding depth of 0.001 mm, and 10 spark-outs. By applying GA, the paper provides a Pareto solution set, offering multiple combinations of optimal factors for minimizing grinding time, deviation, and surface roughness. These solutions serve as useful references for users seeking the best trade-offs in multi-objective scenarios. This paper contributes to improving customer satisfaction by enhancing the quality and efficiency of the machining process while reducing production costs for grinding machines. Its methodology can also be applied to other optimization fields.

The Role of the Bactericidal Mechanism of Copper Elements and Its Effect on the Corrosion Resistance of Steel.

In this paper, two kinds of copper-containing steels with copper contents of 2.31 and 6.01 wt.% were designed. By comparing with commercial Q355, the bactericidal properties of copper in seawater containing sulfate-reducing bacteria (SRB) and its influence on the corrosion process of steel were revealed. The corrosion rate, morphology of products, and bactericidal action of copper were tracked by scanning electron microscopy, X-ray diffraction, confocal microscopy, and electrochemical analysis techniques. It was found that the resistance of copper-containing steel to bacterial corrosion was obviously better than that of non-copper-containing steel. At 28 days, the weight loss rates in the SRB environment for 0Ni2Cu6 samples increased by merely 5.43%, which was nearly half that of Q355 of 9.75%. Cu-containing steels exhibited potent antibacterial action, with the ε-Cu phase altering the corrosion byproduct composition from brittle flakes to robust particles and inhibiting the production of H2S. The killed bacteria adhered to the surface of the steel and slowed down the corrosion of the steel. The confocal laser scanning microscope and electrochemical experiments showed that a dense CuFeO4 film formed on the substrate, impeding corrosive ion penetration, and an upsurge in Cu content markedly enhanced the material's anti-corrosion and antimicrobial attributes.

SULFIDE CAPACITY AND PROPERTIES OF MODIFIED BUCKET SLAGS

Ladle slag during the entire period of iron refining must have a sufficient degree of ability to hold sulfides while simultaneously ensuring the minimization of iron losses. In ladles with recycled cast iron entering the desulphurization department, slags are formed already during the release of cast iron from the blast furnace or pouring from the mixer, which differ significantly from blast furnace slag in terms of physical and chemical properties. The basicity and sulphide capacity of slags decreases, which due to their active mixing with cast iron is accompanied by an increase in sulfur in the metal.The composition of slags, formed from the remains of blast furnace or mixer slags and products of chemical reactions of sulfur removal by injection of mixtures based on lime and magnesium, needs adjustment to increase the sulfide capacity while simultaneously thinning them to prevent excessive losses of iron with the slag. The use of an additional amount of fluidized lime for adjustment leads to an increase in the processing cost. It is proposed to use a slag modifier based on CaO- and Al2O3-containing steel processing waste to reduce the costs of fluidized lime. The rational specific consumption of modifiers was determined depending on the initial composition of ladle slags and the change in their sulfide capacity was calculated using models based on the concept of optical basicity.The change in melting point, viscosity, and melting point of modified ladle slags was determined, and the concentration path of CaO- and Al2O3-containing waste modified with additives was investigated. It is shown that for the typical composition of the ladle slag of cast iron desulfurization plant of PrJSC «Kamet-Stal», the sulfide capacity values ​​range from 1.0.10-4 to 20.0.10-4, which corresponds to blast furnace slags of the CaO-SiO2-MnO-Al2O3-MgO system with increased desulfurizing ability. The change in the amount of the solid fraction in the final slag in the course of refining and the effect of the basicity of the modified slag on the sulfur distribution coefficient in non-stationary temperature conditions were determined. With the application of the linear programming method, the range of rational chemical composition of ladle slag for the conditions of cast iron desulfurization plant of PrJSC «Kamet-Stal» was determined. Modified ladle slag with a basicity of 1.11-1.41 and a content of 40-51% CaO; 36-51 %SiO2 and 6-21 %Al2O3 are proposed to be considered as satisfying the given range of selected metallurgical properties.

Multi-Objective Optimization of Finishing Milling of C45 Steel using Factorial Design

This study presents an innovative approach to optimizing the milling process of C45 steel using a factorial design of experiments. The impact of key technological parameters, including cutting speed (Vc), feed per tooth (fz), depth of cut (ap), and lubrication conditions (dry and flood), on surface roughness (Ra) and Material Removal Rate (MRR) was thoroughly analyzed. Through the application of Analysis of Variance (ANOVA), significant factors and their interactions were identified, with fz and lubrication conditions showing the most substantial influence on Ra. The interaction between fz and lubrication condition was particularly notable, highlighting the importance of these parameters in achieving optimal surface quality. Multi-objective optimization was conducted using the desirability function method to balance the objectives of minimizing Ra and maximizing MRR. The optimal Vc and fz conditions under flood lubrication were found 200 m/min and 0.3 mm/tooth, respectively, achieving a desirability index of 0.801. Under dry lubrication, the optimal conditions were 200 m/min and 0.3 mm/tooth, respectively, with a desirability index of 0.803. These results demonstrate that both lubrication conditions can be effectively optimized to enhance machining performance. The findings provide a comprehensive framework for improving the milling process of C45 steel, contributing valuable insights into the effects of cutting parameters and lubrication conditions on surface quality and MRR.

Impact of reverse Marangoni convection and arc constriction on flux-based TIG welding processes of AISI 304L stainless steel

Impact of reverse Marangoni convection and arc constriction on flux-based TIG welding processes of AISI 304L stainless steel

Мaterial composition and thermal properties of chrysotile asbestos enrichment tailings of the Kiembaevsky deposit

The article discusses the issues of carbon removal in a circulating vacuum unit. It is shown that in order to achieve an ultra-low carbon content (less than 0.002 %), it is necessary to take into account the wear of the lining of steel ladles. When replacing periclase-carbon products in the walls and bottom of the steel ladle with carbon-freeones, carbon intake into the melt can be significantly reduced. Additionally, rational technological parameters of steel processing in a circulating vacuum unit were determined.

Impact of repetitive, ultra-short soft X-ray pulses from processing of steel with ultrafast lasers on human cell cultures

Ultrafast lasers, with pulse durations below a few picoseconds, are of significant interest to the industry, offering a cutting-edge approach to enhancing manufacturing processes and enabling the fabrication of intricate components with unparalleled accuracy. When processing metals at irradiances exceeding the evaporation threshold of about 1010 W/cm² these processes can generate ultra-short, soft X-ray pulses with photon energies above 5 keV. This has prompted extensive discussions and regulatory measures on radiation safety. However, the impact of these ultra-short X-ray pulses on molecular pathways in the context of living cells, has not been investigated so far. This paper presents the first molecular characterization of epithelial cell responses to ultra-short soft X-ray pulses, generated during processing of steel with an ultrafast laser. The laser provided pulses of 6.7 ps with a pulse repetition rate of 300 kHz and an average power of 500 W. The irradiance was 1.95 ×1013 W/cm2. Ambient exposure of vitro human cell cultures, followed by imaging of the DNA damage response and fitting of the data to a calibrated model for the absorbed dose, revealed a linear increase in the DNA damage response relative to the exposure dose. This is in line with findings from work using continuous wave soft X-ray sources and suggests that the ultra-short X-ray pulses do not generate additional hazard. This research contributes valuable insights into the biological effects of ultrafast laser processes and their potential implications for user safety.

Prediction of surface roughness in electrochemical process of stainless steel 301 by response surface methodology

تم استخدام الآلات الكهروكيميائية على نطاق واسع في الأنشطة الصناعية، وخاصة لتصنيع المكونات المستخدمة في التطبيقات الطبية والفضاء والسيارات والصيانة العامة. أدت ظروف العملية المناسبة المستخدمة في التشغيل الكهروكيميائي إلى تقليل تكاليف تشغيل وصيانة المعدات بشكل كبير، بالإضافة إلى تكلفة الأدوات. حيث تعمل هذه الظروف في نفس الوقت على زيادة دقة المكونات التي يتم إنتاجها. تحتوي الإجراءات على معايير أكثر صرامة، أحدها يجب أن يكون لقطعة العمل موصلية كهربائية.وتتأثر خشونة قطعة العمل الناتجة عن المعالجة الكهروكيميائية بمجموعة كبيرة ومتنوعة من المعلمات المختلفة. يهدف هذا النهج السطحي للاستجابة البحثية إلى دراسة تأثير العوامل الرئيسية (التيار، وشدة الإلكتروليت، والفجوة) على خشونة أسطح الفولاذ المقاوم للصدأ 301 كقطعة عمل. كان للنموذج التنبؤي قيمة R2 قدرها 92.6%، والتي تقيس قدرة القيمة المدخلة للمتغيرات على عمل تنبؤات حول قيمة المخرجات للمتغيرات. وكان العنصر الأكثر أهمية في تحديد الحد الأدنى من خشونة السطح هو التيار بنسبة 80٪. كان تركيز المنحل بالكهرباء هو العنصر التالي الأكثر أهمية في تحديد الحد الأدنى لخشونة السطح بنسبة 5٪.

In Situ Ultrasonic Characterization of Hydrogen Damage Evolution in X80 Pipeline Steel.

A nondestructive evaluation of the hydrogen damage of materials in a hydrogen environment is important for monitoring the running conditions of various pieces of equipment. In this work, a new thermostatic electrolytic hydrogenation in situ ultrasonic test system (In Situ TEH-UT) was developed. The system operates by combining cross-correlation delay estimation and frequency domain amplitude estimation and hence improves measurement accuracy with respect to ultrasonic propagation time and amplitude, allowing in situ ultrasonic evaluation of the hydrogen-charging process in X80 pipeline steel. The experimental results show that under a 30 mA/cm2 hydrogen-charging current, the hydrogen saturation time of X80 pipeline steel is 800 min. Between 0 and 800 min, the attenuation coefficient and amplitude attenuation both demonstrate a strong linear relationship with the hydrogen-charging time. After 800 min, the attenuation coefficient and amplitude attenuation do not change further, while the attenuation coefficient fluctuates greatly. Through the characterization of the microstructures of the materials analyzed, it was found that hydrogen-induced cracks (HICs) constituted the main reason for the change in the ultrasonic parameters, and the mechanism behind the hydrogen-induced damage layer (HIDL) was determined. This study provides reference significance for clarifying the change mechanism of ultrasonic parameters under hydrogen damage conditions and determining the extent of hydrogen damage using an ultrasonic technique.