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[Display omitted] • The biodegradable surfactant-dodecyl dimethyl betaine (BS-12) was used as metal inhibitor. • Traces of BS-12 (10 mg·L−1) showed high inhibition efficiency (95.3 %) to cold-roll steel (CRS). • The MD simulations showed that the BS-12 adsorbed on the CRS surface horizontally. • The density of state proved that the electron transfer within BS-12 and CRS. • Adding BS-12 had no side effect on the performance of the nanofiltration membrane. The membrane process is an effective way to realize resource reutilization. Most membrane devices are made of cold-roll steel (CRS), which is easy to corrode when operating in acid conditions. Herein, the biodegradable surfactant dodecyl dimethyl betaine (BS-12) was used as the inhibitor to protect the CRS in the trichloroacetic acid (TCA) solution. The long-term stability membrane tests showed that adding BS-12 will not harm the membrane performance. The weight loss experiments proved that adding BS-12 with trace amount (10 mg·L−1) endowed the CRS with good inhibition efficiency (95.3 %). The electrochemical tests indicated that the mixed inhibitor- BS-12 works by inhibiting the anode and cathode simultaneously, and the polarization resistance increased to 21 times. The SEM, AFM, and CLSM tests proved that adding BS-12 enabled the CRS surface to remain stable. The FTIR and XPS tests proved that BS-12 adsorbed on the CRS surface via physical and chemical adsorption. The theoretical calculations proved the horizontal adsorption of BS-12 on the CRS surface and the existence of the electron transfer within the BS-12 and CRS. The BS-12 showed great potential in the CRS inhibition of the membrane separation and purification processing. [ABSTRACT FROM AUTHOR]

[Display omitted] • N1 of DDAC and N13 of BDDACP are the most vulnerable to electrophilic attack. • BDDACP can form a robust protective film in a parallel direction on Fe (1 1 0) plane. • BDDACP functions as a mixed inhibitor that primarily impedes the active site of CRS surface. • The chemical bonds between BDDACP molecules and Fe atoms are detected from the inhibited CRS surface. • A novel Gemini surfactant of BDDACP is an efficient inhibitor for steel in HCl media with good application prospect. Gemini surfactants have become the research focus of novel excellent inhibitors because of their special structure (two amphiphilic moieties covalently connected at head group by a spacer) and excellent surface properties. It is proved by theoretical calculations that 1, 3-bis (dodecyl dimethyl ammonium chloride) propane (BDDACP) molecules can perform electron transfer with Fe (1 1 0). And it has a small fraction free volume, thus greatly reducing the diffusion and migration degree of corrosive particles. The potentiodynamic polarization curve showed that coefficients of cathodic and anodic reaction less than 1 and polarization resistance increased to 1602.9 Ω cm−2 after added BDDACP, confirming that BDDACP significantly inhibited the corrosion reaction by occupying the active site. The electrochemical impedance spectrum of imperfect semi-circle shows that the system resistance increases and double layer capacitance after added BDDACP. Weight loss tests also confirmed that BDDACP forms protective film by occupying the active sites on steel surface, and the maximum inhibition efficiency is 92 %. Comparison of the microscopic morphology showed that steel surface roughness was significantly reduced after added BDDACP. The results of time-of-flight secondary ion mass spectrometry show that steel surface contains some elements from BDDACP, which confirms the adsorption of BDDACP on steel surface. [ABSTRACT FROM AUTHOR]

Based on the complex characteristics of nonlinearity, strong coupling, and multi-disturbance in hot-rolling steel production, developing a multi-objective optimization system for dynamic control of multi-scale process parameters is challenging. In this paper, novel solutions coupling physical mechanisms into the machine learning modeling are proposed, and their feasibility has been fully demonstrated by analyzing experimental verification and industrial trial production. By comparison with experimental data, the results show that the proposed model accurately describes the microstructure evolution during hot rolling and cooling under complex processing conditions. On this basis, the flexible cooling system is developed by multi-objective particle swarm optimization. Compared with the traditional purely data-driven optimization method, results show that the proposed model ensures that the optimization results meet the requirements of multiple property indicator collaborative optimization but also obtain the optimal comprehensive property and quality stability by controlling the cooling path. Finally, the established system applied to guide the industrial production of steel and the potential for matching optimum cooling parameters according to the fluctuation in steel composition and rolling parameters to achieve a compensatory effect is proved through metallographic observations of final microstructures under different cooling paths. [ABSTRACT FROM AUTHOR]

The effects of starting microstructure (hot-rolled vs lamellar pearlite (LP)-annealed) and microalloying (Nb vs Al) on the induction hardening response of 1045 steels were investigated. The hot-rolled microstructures of the steels consisted of pearlite and pro-eutectoid ferrite, while the LP anneal produced ferrite/pearlite banded microstructures. The 1045Nb steel had a lower initial ferrite fraction than the 1045Al steel. All samples after simulated induction hardening contained non-martensitic transformation products (NMTP), consisting of ferrite, bainite, pearlite, and retained austenite, in the martensitic matrix. The NMTP fraction generally depended on the prior ferrite fraction and size. For a microstructure exhibiting a higher fraction of ferrite and larger size of ferrite islands, complete austenitization during heating was slower. More homogeneous, post-induction, martensitic microstructures were obtained when Al was replaced with Nb, which is associated with decreased ferrite fraction in the pre-induction microstructure for the 1045Nb steel, rather than the direct alloying influence. Hardenability for a given induction thermal cycle was also closely related to the ferrite amount/size in the pre-induction microstructure. It is therefore concluded that prior processing to reduce ferrite fraction/size in the starting microstructure can positively contribute to induction hardenability by efficiently homogenizing the martensitic microstructure during rapid induction hardening. [ABSTRACT FROM AUTHOR]

Smart manufacturing and Industry 4.0 are transforming traditional manufacturing processes by utilizing innovative technologies such as the artificial intelligence (AI) and internet of things (IoT) to enhance efficiency, reduce costs, and ensure product quality. In light of the recent advancement of Industry 4.0, identifying defects has become important for ensuring the quality of products during the manufacturing process. In this research, we present an ensemble methodology for accurately classifying hot rolled steel surface defects by combining the strengths of four pre-trained convolutional neural network (CNN) architectures: VGG16, VGG19, Xception, and Mobile-Net V2, compensating for their individual weaknesses. We evaluated our methodology on the Xsteel surface defect dataset (XSDD), which comprises seven different classes. The ensemble methodology integrated the predictions of individual models through two methods: model averaging and weighted averaging. Our evaluation showed that the model averaging ensemble achieved an accuracy of 98.89%, a recall of 98.92%, a precision of 99.05%, and an F1-score of 98.97%, while the weighted averaging ensemble reached an accuracy of 99.72%, a recall of 99.74%, a precision of 99.67%, and an F1-score of 99.70%. The proposed weighted averaging ensemble model outperformed the model averaging method and the individual models in detecting defects in terms of accuracy, recall, precision, and F1-score. Comparative analysis with recent studies also showed the superior performance of our methodology. [ABSTRACT FROM AUTHOR]

Surface defect detection in steel manufacturing is crucial for quality control and waste reduction, yet traditional manual inspection methods are time-consuming, subjective, and increasingly inadequate for modern production demands. This paper introduces a novel fuzzy hybrid stacked ensemble model that combines vision transformers (ViTs) and convolutional neural networks (CNNs) to detect and classify surface defects in hot-rolled steel strips. Our approach integrates multiple advanced preprocessing techniques including Canny Edge detection, Gaussian Blur, cumulative distribution function (CDF), and local binary patterns (LBP) with state-of-the-art deep learning architectures. The ensemble leverages a Gompertz function-based fuzzy ranking system to optimally combine predictions from individual models, addressing common challenges such as inter-class similarity, intra-class variance, and imbalanced datasets. We evaluate our model on the NEU-CLS-64 dataset, which contains over 7000 grayscale images across nine defect categories. The proposed ensemble achieves exceptional performance with 99.45% accuracy, significantly outperforming existing methods, including individual ViTs (95.68%) and CNNs (92.96%). Our model demonstrates robust generalization capabilities and maintains high precision (96.33%) and recall (94.16%) across all defect classes, making it particularly effective for real-world industrial applications. This research contributes to the growing field of automated quality control in steel manufacturing, offering a reliable solution that aligns with Industry 4.0 principles while addressing the limitations of traditional inspection methods. [ABSTRACT FROM AUTHOR]

Evaluating the current technical condition and residual life of structures that may have reached or exceeded the end of their design life is a challenging issue in many industrial sectors. This paper focuses on the assessment of the structural integrity of structural elements of a seaport portal crane after operation for about 33 years. Test specimens were extracted from two crane elements, a jib (element A) as the most seriously loaded unit and, for comparison, a boom (element B) as the less loaded one, and machined in two different orientations, longitudinal and transversal. Both crane elements were made of a low-carbon rolled steel. The analysis was performed according to the FAD approach of FITNET Procedures. The basic level of analysis was used. For this purpose, the strength and fracture toughness characteristics of the steel from tested elements were determined experimentally. The strength and plasticity properties of the steel of both elements were similar. At the same time, the fracture toughness characteristics differ for the elements A and B and for the longitudinal and transverse specimen directions. The results of the FAD (FITNET) analysis performed for the elements containing a central crack loaded by tensile stress showed that they are not susceptible to failure. The relative length of cracks for which the critical state will be reached is also estimated. [ABSTRACT FROM AUTHOR]

At Štore Steel Ltd., continuously cast billets (180 mm × 180 mm) are reheated and rolled after cooling to room temperature. Hot-rolled bars are controlled as they cool to room temperature in specially designed cooling chambers, minimizing residual stresses and the development of pre-existing surface and internal defects. The bar ends can be additionally covered with insulating material. The cooled, rolled bars undergo examination using automated control lines to detect surface and internal defects, which primarily originate from the casting process. Internal defects are identified using ultrasonic testing. Between January 2022 and June 2023, 1550.0 tons of 61SiCr7 rolled bars, with diameters ranging from 53 mm to 72 mm and lengths from 7010 mm to 7955 mm, were examined using ultrasonic testing. The scrap was 109.6 tons (7.07 %). After collecting data on chemical composition (C, Si, Mn, Cr, Mo, Ni content), the casting process (casting temperature, cooling water pressure and flow in the first, second, and third zones of secondary cooling, as well as the temperature difference between input and output mould cooling water), and rolled bar geometry (diameter, length), scrap modelling after ultrasonic testing was carried using genetic programming. The genetic programming model suggested reducing the length of the rolled bar. Due to length multiplication, it was possible to reduce the rolled bar length from the initial lengths of 7010-7955 mm to the current lengths of 4558-6720 mm in June 2023. Based on this adjustment, a new production of rolled bars was established. By August 2024, 1251.9 tons of 61SiCr7 rolled bars were produced with the mentioned length adjustments. These rolled bars were subsequently examined using ultrasonic testing. The scrap was reduced by nearly 14 times, amounting to only 8.1 tons (0.64 %). [ABSTRACT FROM AUTHOR]

This article designs the PELAN structure based on the lightweight YOLOv7-tiny model for surface defect detection of hot-rolled steel strips. At the same time, the CA (Channel Attention) is embedded in the feature pyramid structure and the Slim-Neck structure is introduced at the neck. Through experimental result analysis, it is proved that the lightweight algorithm not only reduces model complexity, but also has better detection accuracy and processing speed. This article focuses on exploring the potential of lightweight YOLOv7-tiny models in steel surface defect detection. With the advancement of Industry 4.0, quickly and accurately detecting surface defects on steel strips has become crucial. However, traditional defect detection methods often face issues such as large computational requirements and poor real-time performance. Therefore, we have designed a novel PELAN structure that combines CA(Channel Attention)and Slim-Neck structure. The aim is to reduce model complexity while maintaining or even improving detection accuracy and processing speed. [ABSTRACT FROM AUTHOR]

Copyright of Steel Pipe is the property of Steel Pipe Magazine and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The mechanical properties and microstructure of hot-rolled steel are critical in determining its performance in industrial applications, particularly when exposed to elevated temperatures. This study examines the effects of varying temperatures and soaking times on these properties through a series of controlled experiments. The primary objective was to optimize the key response parameters, including tensile strength, yield strength, and elongation, by analyzing the influence of temperature and time. A full factorial design approach was used, applying the desirability function theory to explore all possible combinations and identify optimal processing conditions. The experimental results showed that the soaking time played a critical role, significantly influencing the mechanical properties with an impact ratio of 62%. The microstructural analysis displayed that higher temperatures and longer soaking times resulted in the formation of coarser ferrite and pearlite grains, contributing to a decrease in strength and an increase in ductility. The optimum process condition - 650°C for 60 min - produced the highest values for tensile strength (400.32 MPa), elongation (36.78%) and yield strength (288.52 MPa). The study also highlighted the temperature-dependent nature of the mechanical behavior of hot-rolled steel. While tensile strength and yield strength initially increase with temperature, prolonged exposure, particularly at 600°C and 750°C, results in significant grain coarsening and a corresponding degradation of these properties. Conversely, elongation improves at moderate temperatures (150°C to 300°C) but decreases with prolonged exposure, especially at higher temperatures. These findings underscore the importance of precise control of thermal processing parameters to optimize the mechanical properties of hot-rolled steel. The findings offer significant insights that can be leveraged to optimize material performance in industrial applications, where thermal exposure is a critical consideration. [ABSTRACT FROM AUTHOR]

With the development of rolled steel strips towards higher strength and thinner thickness, negative forward slip has been frequently observed during the process of cold rolling, and this phenomenon closely related to interface is believed to seriously influence rolling stability. However, the existing classic forward slip models are limited to calculating positive forward slip values and cannot reflect negative forward slip effects. Therefore, in this paper, based on BLAND-FORD forward slip theory, a novel modified forward slip model capable of predicting negative forward slip is established and verified, in which the corresponding flattened curve is characterized and a compensation coefficient related to actual tension and coil number is supplemented. Then, a dimensionless sensitivity factor is defined to compare and analyze the influences of various parameters on forward slip through the modified model, in order to pick a more effective and reasonable regulation approach. Finally, an idea of keeping stable forward slip through dynamic tension regulation is suggested and applied in the actual rolling process, and it is drawn that this strategy can be used to avoid fluctuations of process parameters and suppress mill chatter. As a result, the presented modified forward slip model can identify both positive and negative forward slips and is helpful in regulating the interface state and improving the stability of the rolling process. [ABSTRACT FROM AUTHOR]

In this study, a novel lightweight Fe-Mn-Al-C steel composition and thermomechanical processing route was developed to produce a fully austenitic microstructure with a uniform intragranular dispersion of B2-NiAl precipitation in order to overcome the significant challenge of strengthening hot-rolled Fe-Mn-Al-C steels while retaining toughness. The new composition and processing methods allow for the processing of ultrahigh-strength Fe-Mn-Al-C steel containing nickel as thicker gauge plate for a multitude of new automotive and structural applications where lightweighting is critical. The composition investigated in this study was a fully austenitic Fe-21Mn-9Al-1C-8Ni wt% steel. Two hot rolling methods were investigated: the first procedure involved lower temperature rolling cycles to precipitate B2-NiAl during hot rolling and reheating. The second method involved higher temperature rolling to precipitate B2-NiAl after thermomechanical processing during a short isothermal treatment. The lower temperature rolling produced plate with an ultimate tensile strength of 1120 MPa and a Charpy V-Notch (CVN) toughness of 24 J at −40 °C. After the high temperature rolling procedure, precipitation of B2-NiAl through a subsequent precipitation hardening step resulted in reduced B2-NiAl size and improved the ultimate tensile strength above 1300 MPa. The two novel processing routes of a single composition can be performed with current manufacturing capabilities to produce hot rolled plate strengthened by B2-NiAl precipitation to various hardness (ranging from 33 to 41 HRC) and strength levels (ranging from 1100 to 1320 MPa ultimate tensile strength) while retaining 22–27% elongation. [ABSTRACT FROM AUTHOR]

Hydrogen is being increasingly considered as a chemical feedstock and energy storage vector within the iron and steel industry. This study compares the cost and CO 2 emissions associated with green steel production as a function of location for the components in its supply chain between Australia (Pilbara) and China (Beijing). Results are benchmarked against a new facility using conventional coal-based technology, producing Hot Rolled Coil (HRC) steel in China as a common final product. Green steel production in Australia using hydrogen is considerably cheaper and presents lower emissions than exporting the hydrogen and iron ore to China for subsequent processing. Costs are comparable when intermediate Hot Briquetted Iron (HBI) is exported but with increased emissions. However, utilising blue hydrogen produced in China is the most immediately dispatchable with a 35% reduction in CO 2 emissions and an increase in levelised cost of steel (LCOS) of only 11% relative to current practice. [Display omitted] • Steel production using Chinese blue H 2 (Blue Steel) is currently cost competitive. • Exporting green steel is cheaper than exporting hydrogen for steel manufacture. • Exporting Hot Briquetted Iron (HBI) does not provide a cost reduction. [ABSTRACT FROM AUTHOR]

In this investigation hot rolled steel bars of 1.24 weight % carbon steel are subjected to incomplete austenitization based cyclic quenching treatment. Each cycle consists of inserting the specimen in an electric resistance furnace at a temperature of 894 °C and holding for a short duration (6 minutes), followed by oil quenching to the room temperature. Such a typical thermal cycling results in the evolution of a novel microstructure that comprises of large clusters and blocks of cementite in a matrix of martensite after 3 and 4 cycles. Accordingly, a significantly high hardness (7.13 GPa) is achieved on execution of 3 cycles which envisages a new pathway of incomplete austenitization based cyclic quenching treatment for development of new‐generation plain carbon hypereutectoid tool steel. [ABSTRACT FROM AUTHOR]

In this paper, an attempt was made to determine the load-bearing capacity of a bonded joint of galvanized steel elements with carbon fiber reinforced polymer (CFRP) fabric. This issue is extremely relevant to the use of bonded carbon fiber fabric as a mean of reinforcing hot-dip galvanized steel structures. This technique is used in engineering practice for both hot-rolled and cold-formed steel elements. In order to obtain the necessary parameters for modelling bonded joints of galvanised steel thin-walled elements, laboratory tests were carried out. In the first stage, four specimens made of 50 mm diameter steel cylinders bonded to 16 mm thick hot-dip galvanised steel sheet of S350 GD were subjected to the pull-off test. In this connection the SikaWrap 230C composite fabric embedded in SikaDur 330 adhesive layer was investigated. In the second stage, the axial tensile test of the bonded butt joint using the same materials was performed. In this stage, 10 hot-dip galvanised steel sheet samples of S350 GD and 16 mm thickness were tested. The discussion on the failure mechanism in the context of the bonding capacity of the composite joint was carried out. Moreover the advanced numerical model using the commercial FE program ABAQUS/Standard and the coupled Cohesive Zone Model was developed. The significant influence of the preparation method of steel element surface and the thickness of the adhesive layer on the failure mechanism of the joint and the value of the maximum failure force was shown. [ABSTRACT FROM AUTHOR]

Achieving perfect flatness, tension-free surfaces, and exceptional resistance to spring back are important characteristics of packaging steel, setting the standard for high-quality material performance. To guarantee these crucial parameters, the implementation of the stretch-bending process at the final stage of the production route is indispensable. Besides improving the flatness properties, the induced plastic deformation results in an accompanying change in the mechanical properties. This investigation focuses on understanding this change in mechanical properties due to different stretch-bending straightening process parameters. A multivariate predictive model is created to calculate a process window for achieving the desired flatness and also mechanical properties in the production of packaging steel. This model is validated by experiments with a laboratory facility. [ABSTRACT FROM AUTHOR]

Hot-rolled strip steel is an essential material extensively used in various industrial fields, with its mechanical properties being critical to product quality and engineering design. This article presents a method for predicting the mechanical properties of hot-rolled strip steel using the NGBoost (natural gradient boosting) algorithm. The study focused on predicting tensile strength, yield strength, and elongation of hot-rolled strip steel and compared the predictive results with those obtained from the gradient boosting algorithm, Lasso regression, and decision tree algorithms. The results indicated that the NGBoost algorithm performs well on average coverage error (ACE) and prediction interval absolute width (PIAW) values at different confidence levels, demonstrating strong predictive performance. Furthermore, the analysis of variance (ANOVA) method was employed to identify factors that significantly impact mechanical performance, providing theoretical support for optimizing design schemes and enhancing structural safety and reliability. [ABSTRACT FROM AUTHOR]

Steel buildings utilizing steel-concrete composite construction typically have large floor depths due to the concrete deck cast above wide-flange beams. Stay-in-place formwork is placed on the bottom flange to achieve shallower composite floor systems. This formwork comprises either concrete precast panels or steel deep decking, which supports a concrete topping slab that encases the steel beam. The goal is to minimize the floor depth, reducing the building's overall height or increasing the floor-to-floor height. Currently in the United States, no readily available hot-rolled steel shapes allow for easy placement of stay-in-place formwork on the bottom flange. This necessitates intensive fabrication to create asymmetric beams and facilitate rapid placement of stay-in-place formwork on the wider bottom flange. This study aims to develop standardized hot-rolled asymmetric steel I-beams (A-shapes) for potential large-scale production in the United States. Utilizing A-shapes decreases the required manufacturing time and allows for increased speed and efficiency of residential building construction. The research presented herein includes beam sizing constraints established from interviews with three US steel mills. Utilizing the beam sizing constraints for manufacturing, a wide range of possible cross sections were investigated for three structural load cases. Each cross section iteration was analyzed for a total of 16 limit states to establish efficient and effective standardized A-shapes. Parametric studies were conducted to investigate sensitive limit states when altering assumed parameters. As a result of this study, two primary cross sections with a depth of 203 mm (8.0 in.) (A8s) were established for a 6.1-m (20-ft) square grid for a live load of 1.9 kPa (40 psf) and 4.8 kPa (100 psf). The heavier A8 cross section [when supporting 1.9 kPa (40 psf) live loading] satisfies all limit states for a beam length of 6.1 m (20 ft) and spacing of 8.5 m (28 ft), which allows for large open spaces between columns. The methodology developed was also utilized to size four additional A-shapes (two A10s and two A12s) and can be used to size A-shapes for other facilities. [ABSTRACT FROM AUTHOR]

Surface defect detection of hot-rolled steel strip is a crucial process in its production. Aiming at the problem of poor detection accuracy caused by complex shape of defect features and imbalance between object scale and feature scale, this paper proposes a multi-scale sensing and multi-dimensional feature enhancement algorithm. Firstly, a multi-branch residual aggregation module (MRAM) is proposed, which uses the interactive features of different receptive fields between layers to capture global and local texture features, improving the feature extraction capability for defects of different scales. Then, the multi-dimensional attention enhancement head (MAEH) is proposed, which integrates feature information from different prediction branches and realises feature information enhancement in scale, space and channel dimensions for the aggregated information to improve the accuracy and robustness of steel surface defect detection. The results show that the proposed algorithm achieves 82.7% mAP and 89 FPS on the NEU-DET dataset, and 73.3% mAP and 94 FPS on the GC10-DET dataset. Compared with state-of-the-art algorithms, the proposed algorithm has the highest mAP, strong generalisation ability, and good real-time performance, which proves its effectiveness in detecting hot-rolled steel strip surface defects. [ABSTRACT FROM AUTHOR]

Commercial 0.31 wt.% Ti 443 ferritic stainless steel (FSS) hot rolled plate was selected as experiment object. Microstructures and state of the second phase of steels annealed at different temperatures from 880 to 1080 °C were researched. The tensile and impact properties were tested, the microstructure was characterized, and the fracture morphology was observed. The results indicated that annealing temperature had a significant impact on the properties and second phase characteristics of hot-rolled 443 FSS plates containing titanium. The annealed microstructure of steel exhibited a ferrite structure with bcc crystal structure. As the annealing temperature increased, both strength and elongation decreased the trends hardness and impact value showed decreased at first, then increased and decreased at last. The fracture morphology gradually transitions from ductile fracture to brittle fracture characteristics. The fracture morphology gradually transformed from ductile fracture to brittle fracture characteristics. After annealing at 980 °C, the grain recrystallization was relatively complete with uniform size and mostly presented equiaxed grains. The (110) diffraction peak were weaken. Resorption of the second phase particle caused matrix lattice distortion and induced dislocation entanglement and blockage. The second phase particles determined by SEM-EDS were TiN and TiCN, which weakened the solid solution strengthening and increased the dispersion strengthening of the steels. [ABSTRACT FROM AUTHOR]

Copyright of Steel Pipe is the property of Steel Pipe Magazine and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Herein, the interaction between hydrogen, microstructure, and mechanical properties in low-alloy high-strength marine steel was elucidated via microstructural characterization, internal friction analysis, hydrogen diffusion, and hydrogen-embrittlement sensitivity evaluation. Results indicated that the bainite structure of hot-rolled steel transformed into a coarse ferrite–pearlite structure after normalizing, and the hydrogen trap density decreased with decreasing grain boundary and dislocation densities. Therefore, the effective diffusion coefficient of hydrogen in the normalized steel plates increased with decreasing hydrogen permeation time. Owing to the coarsening of the microstructure, the normalized steel plates exhibited higher sensitivity to hydrogen embrittlement. The diffusion of a large amount of hydrogen into the steel considerably deteriorated its plasticity, resulting in a transition of its fracture mode from microvoid coalescence fracture to cleavage fracture. The internal friction behavior indicated that hydrogen in the microstructure generated a hydrogen-induced Snoek peak, as well as reduced the activation energy of Snoek–Kê–Köster and Kê peaks. Finally, the internal friction spectra revealed that the interaction between hydrogen and point defects, dislocations, grain boundaries, and precipitates was sequentially enhanced due to the increase in activation energy. [ABSTRACT FROM AUTHOR]

Presently, the main trend in thin-sheet steel production, including the high-strength automobile steel, is to reduce production costs while retaining essential properties and quality. A considerable part of the cost of high-strength steel comes from alloying with expensive chemical elements such as vanadium and niobium. Simply reducing the content of these elements in finished products would compromise the mechanical properties of rolled products, leading to inferior quality and defects. This work, based on statistical analysis for steel grade S355MC, demonstrated the potential to reduce alloying while maintaining the required yield strength by adjusting the hot rolling conditions. It was also revealed that, in addition to the concentration of chemical elements and the hot rolling mode, the thickness of the finished product affects the tensile strength. Therefore, the analysis was performed exclusively on products with a thickness of 4 mm. The study resulted in a regression equation that illustrates the dependence of yield strength on vanadium content and hot rolling parameters. [ABSTRACT FROM AUTHOR]

Cold-formed steel (CFS) sections, increasingly favored in the construction industry due to their numerous advantages over hot-rolled steel, have received limited attention in research concerning the flexural behavior of galvanized iron (GI)-based CFS at elevated temperatures. Understanding how these materials and structures behave under elevated temperatures is crucial for fire safety. The authors have performed experimental studies previously on GI-based CFS under elevated temperatures. In that study, CFS sections made of GI of grade E350 of 1.5 m long and 2 mm thickness were used. Built-up beam sections were tested under two-point loading after heating to 60 and 90 min durations and subsequently cooling them down using air and water. This study aims to uncover the influence of different stiffener configurations on the load carrying capacity of sections under elevated temperature parametrically. With the experimental study results from previous studies as a reference, authors used FEM analysis to comprehensively study the behavior of GI-based CFS sections under fire. Vertical, horizontal, and not providing a stiffener were the configurations selected to study the beams parametrically. Parametric analysis confirmed that different stiffener configurations did not alter the predominant failure mode, which remained distortional buckling across all specimens. Beams with vertical stiffeners demonstrated superior performance compared to those with horizontal stiffeners in parametric analysis. Lateral–torsional buckling was observed in the reference specimen, lacking stiffeners due to inadequate restraint at the supports. [ABSTRACT FROM AUTHOR]

For industry image data, this paper proposes an image classification method based on stochastic configuration networks and multi-scale feature extraction. The multi-scale features are extracted from images of different scales using deep 2DSCN, and the hidden features of multiple layers are also connected together to obtain more informational features. The integrated features are fed into SCNs to learn a classifier which improves the recognition rate for different categories. In the experiments, a handwritten digit database and an industry hot-rolled steel strip database are used, and the comparison results demonstrate the proposed method can effectively improve the classification accuracy. [ABSTRACT FROM AUTHOR]

Copyright of Steel Pipe is the property of Steel Pipe Magazine and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Smart manufacturing is a process that optimizes factory performance and production quality by utilizing various technologies including the Internet of Things (IoT) and artificial intelligence (AI). Quality control is an important part of today's smart manufacturing process, effectively reducing costs and enhancing operational efficiency. As technology in the industry becomes more advanced, identifying and classifying defects has become an essential element in ensuring the quality of products during the manufacturing process. In this study, we introduce a CNN model for classifying defects on hot-rolled steel strip surfaces using hybrid deep learning techniques, incorporating a global average pooling (GAP) layer and a machine learning-based SVM classifier, with the aim of enhancing accuracy. Initially, features are extracted by the VGG19 convolutional block. Then, after processing through the GAP layer, the extracted features are fed to the SVM classifier for classification. For this purpose, we collected images from publicly available datasets, including the Xsteel surface defect dataset (XSDD) and the NEU surface defect (NEU-CLS) datasets, and we employed offline data augmentation techniques to balance and increase the size of the datasets. The outcome of experiments shows that the proposed methodology achieves the highest metrics score, with 99.79% accuracy, 99.80% precision, 99.79% recall, and a 99.79% F1-score for the NEU-CLS dataset. Similarly, it achieves 99.64% accuracy, 99.65% precision, 99.63% recall, and a 99.64% F1-score for the XSDD dataset. A comparison of the proposed methodology to the most recent study showed that it achieved superior results as compared to the other studies. [ABSTRACT FROM AUTHOR]

The low-carbon steel revealed the presence of ferrite-pearlite and ferrite-martensite microstructures after being subjected to different thermomechanical routes. These routes involved two distinct stages: 1) reheating hot-rolled steel at 1473 K, followed by cooling via step quenching, intermediate quenching, and furnace cooling, and 2) cold rolling and subsequently annealing at 873 K for 2 and 8 h. The quenching schedules finally developed a ferrite-martensite structure with different martensitic morphology, whereas furnace cooling promotes a ferrite-pearlite structure. The prolonged annealing assists in carbide precipitation from deformed ferrite-martensite microstructure while pre-existing carbides coarsen after 8 h of annealing in furnace-cooled specimens. The sudden phase disintegration contributes to the changes in the recrystallized kinetics and evolution of precipitates, tailoring the final grain size. Additionally, the development of textures after cold rolling and annealing is studied through the emergence of α and γ fiber in BCC phase. Finally, detailed microscopic technique has been employed to correlate the overall tensile response of the investigated samples with their interrelated microstructures. [ABSTRACT FROM AUTHOR]

Earthquakes cause nonstructural, if not structural, damage to buildings. This damage is proportional to interstory drift (ISD). Concentric braced frames (CBFs) are one of the most effective measures to limit the ISD in steel buildings. When compressed, conventional concentric hot-rolled (HR) steel braces tend to buckle when slender and are aesthetically unpleasant if stocky. This limitation of conventional concentric hot-rolled steel braces motivates the present work to use pretensioned carbon-fiber-reinforced polymer (CFRP) cables as braces in CBFs. The theoretically proposed self-balancing pretensioned CFRP cable braces (SPCCBs) in CBFs eliminate buckling in braces and provide a comparable elastic strain energy reserve for earthquake resistance design. Being slender, SPCCBs will add to the aesthetic beauty of buildings. The performance of the SPCCB system was evaluated by comparing it with conventional CBFs using stocky HR. CFRP cables with two different tensile strengths were used as braces in the SPCCB system, i.e., CFRP cable with tensile strength of 4,700 MPa (CB4700) and 3,600 MPa (CB3600). Fifty-seven models (19 each for HR, CB4700, and CB3600) were prepared using a commercially available code and were designed using Indian standards, keeping the compressive capacity of the braces similar for all three systems. The performance of all of the aforementioned systems was evaluated on the basis of energy dissipation (through total strain energy capacity of braces), fundamental time period, base shear attracted, ISD, and size of braces. This study showed that the SPCCB system has not only improved the strain energy capacity but also reduced the base shear compared to conventional hot-rolled steel brace CBFs. The overall performance of the building with CB4700 braces was found to be the best, followed by CB3600 and HR braces. Finally, a design guideline for the SPCCB system was proposed by following the Indian standards. [ABSTRACT FROM AUTHOR]

In this study, high-carbon Nb microalloyed hot rolled steel plates are subjected to quenching and partitioning (Q&P) treatment at different temperatures and time durations. Dilatometry results show that increasing cooling rate (CR) leads to suppression of transformation start and finish temperatures of high-temperature transformation products like pearlite (P) or bainite (B), whereas martensite (M) transformation triggers with increasing cooling rate from 5 to 50 °C/s. The observations made by optical (OM), scanning (SEM), and transmission electron microscopy (TEM) reveal mixed-phase microstructures consisting of preformed/tempered martensite (PTM), retained austenite (RA), twin martensite (TM), and lower bainite (LB) for the isothermally heat-treated (IHT) samples subjected to Q&P at 200 °C and 180 °C for 30 minutes. The maximum volume percentage of RA ( V γ ) and C content in RA ( C γ ) is witnessed in the IHT samples subjected to Q&P for 30 minutes at 200 °C and 180 °C, respectively, followed by the hot rolled air-cooled (HRAC) sample. The formation of very fine NbC precipitates (~17 to 33 nm) is also evident in HRAC and Q&P at 160 °C for 30 minutes samples, which are expected to contribute significantly to precipitation strengthening. Hardness shows an increasing trend from 36 HRC to 65 HRC with increasing CR from 0.5 to 50 °C/s. The best combinations of the ultimate tensile strength (UTS) and total elongation (TEL) in Q&P 200 samples (36043 MPa pct) followed by Q&P 180 samples (32759 MPa pct) can be correlated with their higher values of V γ and C γ . [ABSTRACT FROM AUTHOR]

Commercial dual-phase steels are typically synonymous with a banded distribution of martensite in their microstructures, which can degrade ductility and increase the anisotropy of mechanical properties. The concept of neutralizing the effect of Mn segregation is employed to change the distribution of martensite to a non-banded distribution. To this end, the ratio of austenite and ferrite stabilizer elements has been changed in the composition of dual-phase steel. Microstructural analysis has been carried out on both hot-rolled (ferrite + pearlite) and heat-treated (ferrite + martensite) microstructures by optical microscope and EBSD, respectively. The microstructural examinations have confirmed the non-banded distribution of second phase and more equiaxed ferrite grains in the segregated neutralized grade microstructures compared to a commercially benchmarked dual-phase steel. Tensile properties of two grades have also been assessed in hot-rolled and heat-treated conditions in RD, TD, and 45 deg tensile directions. In the case of heat-treated condition, total elongation in RD direction has been improved from 20.9 pct in benchmark dual-phase steel to 25.4 pct in segregated neutralized dual-phase steel. Tensile anisotropy results showed a significant difference in tensile strength by tensile direction in benchmark dual-phase steel in both hot-rolled (~ 85 MPa) and heat-treated conditions (~ 48 MPa), while the corresponding differences for the segregated neutralized grades were 14 and 15 MPa, respectively. [ABSTRACT FROM AUTHOR]

Arbitrage spread prediction can provide valuable insights into the identification of arbitrage signals and assessing associated risks in algorithmic trading. However, achieving precise forecasts by increasing model complexity remains a challenging task. Moreover, uncertainty in the development and maintenance of model often results in extremely unstable returns. To address these challenges, we propose a K-fold cross-search algorithm-optimized LSTM (KCS-LSTM) network for arbitrage spread prediction. The KCS heuristic algorithm incorporates an iterative updating mechanism of the search space with intervals as the basic unit into the traditional ant colony optimization. It optimized the hyperparameters of the LSTM model with a modified fitness function to automatically adapt to various data sets, thereby simplified and enhanced the efficiency of model development. The KCS-LSTM network was validated using real spread data of rebar and hot-rolled coil from the past three years. The results demonstrate that the proposed model outperforms several common models on sMAPE by improving up to 12.6% to 72.4%. The KCS-LSTM network is shown to be competitive in predicting arbitrage spreads compared to complex neural network models. [ABSTRACT FROM AUTHOR]

This study investigated the effects of partially replacing expensive Mo with cheaper Nb on the microstructure and properties of high-strength low-alloy (HSLA) steel during reverse austenisation. The mechanical properties of the steel in the hot-rolled state were lower with a partial replacement of Mo by Nb. However, after pre-tempering and reheating and quenching, the strength increased greatly while the ductility and toughness did not decrease much. Thus, the negative effects of replacing Mo with Nb were mostly alleviated, and a good balance between strength, ductility and toughness was achieved. After heat treatment, the mass percentage of precipitates increased substantially, which helped to pin grain boundaries during austenisation. The percent of high-angle grain boundaries greatly increased while the average effective grain size decreased, which improved grain refinement. The results showed that combining a partial replacement of Mo by Nb with heat treatment allows the microstructure and mechanical properties of HSLA steel to be effectively controlled while improving the balance between cost and performance. These findings provide valuable insights into the preparation and design of steels with similar microstructures. [ABSTRACT FROM AUTHOR]

With the addition of microalloy elements to a high-strength low-alloy (HSLA) steel, various fine particles of carbides and nitrides are formed, which increase the matrix strength. These precipitates play a crucial role in precipitation strengthening. However, the role of precipitates in microstructural refinement is frequently overlooked. In this study, a series of hot-rolled HSLA steel samples were reheated to different temperatures above the austenite transformation point for a specified period to refine austenite grains via precipitation, then cooled to a dual-phase (austenitic/ferritic) region, and finally air-cooled to room temperature. The influences of different austenitising conditions on the microstructure and mechanical properties of the HSLA steel were examined. When a hot-rolled sample was reheated to 15 °C above the austenitic transition temperature for 20 min and then cooled to 25 °C below the austenitic transition temperature for 25 min, the most low-angle boundaries were formed, and the smallest effective grain size was achieved. Meanwhile, compared with the hot-rolled sample, the tensile and yield strengths of the reheated sample increased by 12.3% and 3.4%, respectively, while the elongation increased by 162.5%, exhibiting a good strength–ductility balance. By adopting an appropriate austenitising process, precipitates can refine the crystalline grains during austenitisation, thereby enhancing the comprehensive mechanical properties of the steel. Meanwhile, excessively high austenitising temperatures lead to the coarsening of the steel microstructure, decreasing the microstructural refinement efficiency via precipitation and consequently degrading the comprehensive mechanical properties of the steel. The findings provide valuable insights into the preparation process design of such steels or other steels with similar microstructures. [ABSTRACT FROM AUTHOR]

Dual-phase (DP) steels with their dual phase microstructures (hard martensite and soft ferrite) are used in many industrial applications, especially in the automotive industry, thanks to their desired mechanical properties and formability. These properties are directly related to their phase distribution in microstructure obtained as a result of the production conditions. The most important step of the production of cold rolled DP steels is the annealing process. In this study, the effect of boron alloying with line scale heat treatment cycle on the microstructure and mechanical properties of cold rolled DP steel was investigated. For this purpose, mechanical test, formability and weldability tests were carried out. The materials were characterized by optical microscopy (OM) and scanning electron microscopy (SEM/EBSD) studies. According to the results, alloying with boron delays the formation of ferrite and pearlite/bainite during the cooling process and increases the martensite formation rate. Boron alloyed cold rolled DP steel shows improved yield and tensile strength without significant loss of elongation. On the other hand, alloying with boron does not have a detrimental effect on the weld properties. [ABSTRACT FROM AUTHOR]

The effect of processing on the microstructure and mechanical properties of cast duplex stainless steel 2507 is studied. It is established that the structure of hot-rolled steel contains δ-ferrite and austenite (γ) bands that change due to 50% cold rolling to form microstructural constituents of a more refined and fragmented nature of a duplex (γ +δ) phase. Austenite grains are most effectively refined (up to 5 μm) because of the recrystallization occurring during aging treatment. The cold-rolled steel has maximum strength and minimum elongation. The best combination of strength and ductility is achieved after hot deformation + solution treatment at 1040°C with water cooling and after hot deformation + solution treatment at 1300°C with water cooling followed by isothermal aging at 1000°C. Such processing ensures a good formability of the steel. [ABSTRACT FROM AUTHOR]

Hot-rolled strip steel is a material widely used in production activities and daily life. However, the appearance of surface defects during its production process is inevitable. To address this issue, we introduce a new detection method using Gold-Yolo to detect surface defects on hot-rolled strip steel. Our method effectively balances accuracy and real-time performance while detecting four common types of surface defects, achieving an average accuracy rate of 82,2 % for detecting individual types of surface defects. Experimental data prove that our method excels in classifying and locating surface defects on hot-rolled steel strip, demonstrating broad application prospects and promotional value. [ABSTRACT FROM AUTHOR]

In response to the inevitable surface defects in the manufacturing process of hot-rolled steel, this paper proposes an improved steel surface defect detection model based on YOLOv7. In the Extended Efficient Large Aggregation Network (E-ELAN), the model replaces conventional convolution with Omni-Dimensional Dynamic Convolution (ODConv) to enhance the network's sensitivity to feature extraction using a combination of various attention mechanisms. Additionally, the detection head in the head section is replaced with an Efficient Decoupled Detection Head, enhancing the model's capability to classify and locate small defects. The proposed model is tested on the public dataset NEU-DET, achieving a high mAP of 76,5 %. This effectively enhances the model's ability to detect surface defects in steel while maintaining a fast detection speed. [ABSTRACT FROM AUTHOR]

Shear-keyed inter-modular connections (IMCs) are integral components of high-rise modular steel structures (MSSs), providing robust interconnectivity to support grouped tubular columns across modules, thereby introducing column discontinuities and distinctive structural behavior. This study conducted a comprehensive numerical assessment and theoretical analysis of the axial compression behavior of grouped tubular columns based on a validated finite element model (FEM), which captured the member-to-structural level behavior of steel hollow section (SHS) columns and accommodated geometric imperfections. An FEM was initially developed and validated using 28 axial compression tests documented in the literature, comprising 15 tests on cold-formed and 13 on hot-rolled steel hollow section (SHS) columns. The primary parameters explored in tests included material properties (stainless/carbon), processing methods (cold-formed/hot-rolled), cross-section sizes (D/B), cross-sectional or member slenderness ratios (D/tc, B/tc, or Lc/r), and the number of columns (1, 7, and 11). A comprehensive parametric numerical study involving 103 grouped tubular column FEMs then investigated the influence of initial imperfection, shear-key height (Lt), thickness (tt), steel tube length (D), width (B), thickness (tc), and height (Lc) alongside the effects of space between tube and key, and the gap between tubes. The results indicated that the load-shortening behavior of the grouped columns consists of linear elastic, inelastic, and recession stages. The failure modes observed primarily displayed an S-shaped pair of inward and outward local buckling on the outer sides and double S-shaped local buckling on the interior sides. The buckling arose near the shear key or at 1/4 or 1/2 of the column height. None of the considered models experienced global buckling. Increasing tt, Lt, tc, D, or B enhances strength and stiffness, while Lc or Lc/r linearly affects stiffness and ductility. The columns' nominal axial strength was reduced because of the shear keys, which decreased compression yielding and caused localized elastic buckling. Subsequently, the theoretical analysis revealed that the design codes do not capture this behavior, and thus, their capacity estimate yields inaccurate findings. This discrepancy renders existing code prediction equations, including those from Indian (IS800), New Zealand (NZS400), European (EC3:1-1), Canadian (CSA S16), American (AISC360-16), and Chinese (GB50017) standards, as well as the model proposed by Li et al., non-conservative. To assure conservative results, the paper recommended modification of existing standards and proposed prediction equations based on a fourth-order differential equation that describes the actual behavior of modular steel columns grouped with shear keys. The proposed design approach accurately predicted the axial compression capacity of modular steel-grouped columns, proving conservative yet effective. This provides valuable data that could transform design and construction techniques for MSSs, extending to various column and IMC forms through adaptable design parameters. This enhancement in structural performance and safety significantly contributes to the advancement of modular construction practices. [ABSTRACT FROM AUTHOR]

Microstructure is an important factor affecting hydrogen diffusion in pipeline steels. Due to the different stress and heat conditions, the surface and internal microstructure of the rolled pipeline steels is different. The ferrite grain size in surface layer of X42 pipeline steel is smaller than other locations, while the surface layer of X52 pipeline steel has continuous banded ferrite/pearlite structure and grains with uneven size. Hydrogen permeation behavior is investigated at different positions in the normal direction of X42 and X52 pipeline steels using the electrochemical hydrogen permeation technique. The results show that the values of the effective diffusion coefficient of surface layer in X42 and X52 pipeline steels are the smallest, while the values of the subsurface hydrogen concentration at steady state are the largest. Hydrogen microprint experiment results indicate hydrogen atoms mainly escape at pearlite, ferrite grain boundaries and near inclusions in X42 and X52 pipeline steels. • The surface and interior microstructure of rolled pipeline steel is inconsistent. • Hydrogen diffusion is hindered by grain boundaries. • The continuous banded ferrite/pearlite structure impedes hydrogen diffusion. • Hydrogen atoms mainly escape at pearlite and ferrite grain boundaries. [ABSTRACT FROM AUTHOR]

A comprehensive experimental study was conducted on EN8 steel samples subjected to hot rolling at various temperatures and with different numbers of passes. The research investigates the influence of these rolling parameters on the material's microstructure, hardness, and magnetic properties. The study includes controlled heating to specific temperatures, precise adjustments of roll spacing, and meticulous monitoring of rolling parameters. Key findings include the microstructural evolution during hot rolling, with grain refinement and phase transition, notably influenced by temperature. The data also reveals the relationship between rolling conditions, material hardness, and percentage of recrystallization, offering insights into optimizing material properties. Furthermore, the study presents an in-depth analysis of the Barkhausen peak's behavior concerning temperature, showcasing its potential for non-destructive hardness evaluation. Overall, this research provides valuable knowledge for material engineers and manufacturers aiming to tailor EN8 steel properties through optimized rolling and heat treatment processes. [ABSTRACT FROM AUTHOR]

Aluminum-incorporated medium-manganese steel (MMnS) has potential for lightweight transport applications owing to its impressive mechanical properties. Increasing the austenite volume fraction and making microstructural changes are key to manufacturing MMnS. However, the grain boundary character and strain distribution of intercritically annealed low-density MMnS have not been extensively scrutinized, and the effects of crystallographic texture orientation on tensile properties remain ambiguous. Therefore, in this study, the microstructure, microtexture, strain distribution, and grain boundary characteristics of a hot-rolled medium-Mn steel (Fe–0.2 C–4.3 Al–9.4 Mn (wt%)) were investigated after intercritical annealing (IA) at 750, 800, or 850 °C for 1 h. The results show that the 800 °C annealed sample exhibited the highest austenite volume fraction among the specimens (60%). The duplex microstructure comprised lath-type γ-austenite, fine α-ferrite, and coarse δ-ferrite. As the IA temperature increased, the body-centered cubic phase orientation shifted from <001> to <111>. At higher temperatures, the face-centered cubic phase was oriented in directions ranging from <101> to <111>, and the sums of the fractions of high-angle grain boundaries and coincidence–site–lattice special boundaries were significantly increased. The 800 °C annealed sample with a high austenite content and strong γ-fiber {111}//RD orientation demonstrated a noteworthy tensile strength (1095 MPa) and tensile elongation (30%). [ABSTRACT FROM AUTHOR]

The quality of the hot-rolled steel strips is essential, as they are involved in many industries, including vehicle manufacturing, electrical machines, engines, and packaging, among others. However, these products are susceptible to defects during the fabrication process and lifetime, such as cracks, holes, and scratches, leading to significant financial and reputation losses. To this end, the development of powerful AI algorithms to detect and identify possible defects in hot-rolled steel strips has gained immense attention from researchers. In the current study, we proposed various AlexNet-based models for hot-rolled steel strips' surface defect recognition, including three modified AlexNet models and 12 hybrid models. The modified AlexNet models are obtained using the transfer learning technique and replacing the classifier part with one or more new fully connected layers. On the other hand, we combined the AlexNet model, the transfer learning technique, and various machine learning algorithms like KNN, LDA, DT, and NB to obtain the hybrid models. The proposed hybrid models provide excellent classification rates, achieving an accuracy that can reach 100% in the case of Alexnet-drop7-KNN and Alexnet-drop7-DT. In addition, this work investigates the effectiveness of selecting feature extraction layers and the type of classifier on the classification accuracy rate and its training and testing time. Moreover, to further illustrate the proposed model's effectiveness, the results are compared with recent studies showing their superiority. [ABSTRACT FROM AUTHOR]

This study investigated austenite formation in a cold‐rolled dual‐phase steel through thermal experiments in a dilatometer and a Gleeble machine, applying various intercritical annealing temperatures and different heating rates in a 60 % cold‐rolled ferrite‐pearlite banded microstructure. The microstructural characterization revealed that the transformation of lamellar pearlite into ferrite and spheroidized cementite aggregates started before the onset of austenite formation. Different degrees of overlap between the recrystallization of ferrite‐pearlite structure and austenite formation processes were observed, depending on the applied heating rates, which affected the austenite formation mechanisms and the microstructure morphology. [ABSTRACT FROM AUTHOR]

To study the effect of high-temperature environment on the properties of titanium steel composite plate, the normalized heat treatment of rolled titanium steel composite plate was carried out at 800-1000 °C for 1 h in this work. Then, the microstructure and element diffusion of the bonding interface were studied by various microscopic instruments. Furthermore, the mechanical properties of the bonding interface of the composite plate were tested by hardness test and shear tensile test. The results demonstrated that the normalizing process greatly enhances the interatomic diffusion and microstructure transformation at the bonding interface. With the increase in temperature, a new microstructure appeared on the titanium side of the bonding interface, and the average grain size of the steel side increased. TiC was formed at the interface at 900 °C and partially dissolved at 950 °C. After the partial melting of TiC in the interface reaction layer, the element diffusion accelerated and the content of Ti/Fe series intermetallic compounds increased, which improved the microhardness at the interface and significantly reduced the interfacial shear strength. The morphology of the peeled surface of titanium steel was characterized by microcracks, cleavage surfaces and pits, mainly brittle fracture, and some areas were ductile fracture. [ABSTRACT FROM AUTHOR]

The expanded web depth of steel beams leads to improved strength and stiffness. In some design scenarios, such as cellular, castellated, or expanded steel beams, increasing the depth of the web improves the strength and performance of the steel beam. The expanded web of steel beams can be accomplished by creating a horizontal cutting in the web and then adding a plate between the two web section halves, which are called spacer plates. This method leads to improved stiffness and strength. Numerical models have been developed to accurately predict the properties of these beams. This study investigates the use of incremental plates to increase the depth of hot-rolled wide-flange steel beams. The experimental results were validated first with the Finite Element (FE) numerical model created by ABAQUS software, and then Finite Element Analysis (FEA) methods were used to create and analyze new numerical models by considering parameters that provided more models at a lower cost. The load-mid-span deflection curve behavior of both models (experimental and theoretical) was similar. Also, the load-deflection behavior of steel beams with two types of openings was studied. For the first type of opening (B1 NUM), with a smaller opening width of 30 mm and a higher hole number (24), the ultimate load increased by 53%, 111%, and 184%, the deflection at 0.95 Pu increased by 160%, 293%, and 81% of beams with ratio 150%, 200%, and 250% compared with the reference beam. For the second type of opening (B2 NUM), with a larger opening width of 60 mm and smaller hole number (12), the ultimate load capacity increased by 51%, 147%, and 177%, for beams with a ratio of 150%, 200%, and 250%, compared with the reference beam. The deflection at 0.95 Pu increased by 46% and 15% for beams with a ratio of 150%, and 200%, and decreased by 8% for beams with a ratio of 250%. Accordingly, for the first type of opening, the expanded ratios of 150% and 200% performed best with a reduction of only 1%-12% in the ultimate load capacity. However, for the second type of opening, the beam with a ratio of 250% performed better than the first type. Using prestress strands may highly improve steel beams' performance with the expanded webs containing openings by creating a stronger section that can withstand higher loads and exhibit improved structural performance, especially from beams with a ratio of 150%. [ABSTRACT FROM AUTHOR]

Burr formation on the edge of the machined part during face milling is a common phenomenon. Highly precise and accurate parts are required to be burr free. Generally, deburring (secondary operation) is performed to remove the burr, which leads to the cost of the part. The aim of this study is to obtain minimum exit burr by optimising the input parameters at primary stage of the face milling operation. Effect of machining parameters (cutting velocity, feed per tooth, axial depth of cut), and machining strategies (rolling direction, cutter offset, soaking time during heat treatment) are taken into consideration. Taguchi's L27 matrix is selected for the design of experiments. Face milling of rolled steel (AISI 1040) is performed on vertical milling centre using titanium nitride coated carbide inserts. Exit burr is evaluated as a signal to noise ratio. The significance level and percentage contribution of parameters are calculated using analysis of variance. Cutter offset has shown maximum contribution followed by cutting velocity. Burr reduction of 58.4% is observed during a confirmation test. Finally, multi-variable linear regression is employed to generate second-order empirical model. Adequacy of model is checked by residual analysis. [ABSTRACT FROM AUTHOR]

The degree of austenite grain refinement in steel for ultra ‐ heavy ships is limited by conventional processes, resulting in the effect of very small‑size austenite grains on the organization and properties of the steel plate being unclear. The effect of austenite grain refinement on the microstructure evolution and mechanical properties of ultra‐heavy EH47 crack arrest steel was investigated by using the secondary austenitization method and thermo mechanical control process. The results showed that the prior‐austenite grain size increased from 14 μm to 28 μm, with the reheating temperature of the test rolled steels rising from 890 ℃ to 1 050 ℃; the decrease of ferrite content reduced the proportion of large angle grain boundary from 57. 4% to 40. 5%; the volume fraction of martenite/austenite (M/A) islands increased from 2. 0% to 6. 5%; the yield strength of the steels increased from 440 MPa to 488 MPa. The effective interfacial area per unit volume of 890 ℃ rolled steel was 269. 0 mm-1, which was the key reason for its microstructure refinement, homogenization, and 241 J impact energy at -100 ℃. [ABSTRACT FROM AUTHOR]