steel research international最新文献_第7页

Impact of Radial Position on Iron Ore Sinter Reduction and Microstructure at 700–1100 °C 700-1100 °C时径向位置对铁矿烧结还原和微观结构的影响

IF 2.2 3区材料科学 Q2 METALLURGY & METALLURGICAL ENGINEERING

steel research international

Pub Date : 2024-08-26 DOI: 10.1002/srin.202400339

Ahmed Abdelrahim, Mikko Iljana, Matti Aula, Timo Fabritius

In this research, the reduction of iron ore sinter in a blast furnace (BF) simulator in CO–CO2–N2‐reducing gas, simulating conditions at the BF center and wall, is investigated. Measurements from an operating BF guide the study, ensuring realistic reduction parameters. Reduction rate and extent, along with physical properties, are assessed under a temperature range of 700–1100 °C. In isothermal reduction experiments, the BF center exhibits superior conditions, particularly at 900 °C, achieving an 83.78% reduction degree compared to 27.17% at the wall for the same temperature. In this study, it is highlighted that basic iron ore sinter demonstrates higher reduction efficiency compared to acid iron ore pellets under identical BF center reducing conditions. Specific surface area and porosity measurements unveil a contrasting trend in specific surface area and porosity evolution between the BF wall and center. Surface morphology analysis reveals that the reduction in specific surface area and porosity of sinter samples at the BF center conditions at 1000–1100 °C is attributed to the sintering of the formed metallic iron. Carbon analysis confirms no carbon deposition took place during reduction. Mineralogical and physical property analyses provide detailed insights into the evolving phase composition during sinter reduction.

本研究调查了高炉（BF）模拟器在 CO-CO2-N2 还原气体中还原铁矿烧结矿的情况，模拟了高炉中心和炉壁的条件。通过对运行中的高炉进行测量来指导研究，确保还原参数符合实际情况。在 700-1100 °C 的温度范围内，对还原速率和程度以及物理性质进行了评估。在等温还原实验中，BF 中心显示出优越的条件，尤其是在 900 ℃ 时，在相同温度下，BF 中心的还原度达到 83.78%，而壁的还原度仅为 27.17%。这项研究强调，在相同的 BF 中心还原条件下，碱性铁矿烧结矿的还原效率高于酸性铁矿球团矿。比表面积和孔隙率测量结果表明，碱性铁矿烧结矿壁和中心的比表面积和孔隙率变化趋势截然不同。表面形态分析表明，在 1000-1100 °C 的烧结炉中心条件下，烧结样品比表面积和孔隙率的减少是由于形成的金属铁烧结所致。碳分析证实在还原过程中没有碳沉积。矿物学和物理性质分析提供了烧结矿还原过程中相组成演变的详细情况。

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引用次数: 0

Microstructural Evolution, Mechanical and Electrochemical Performance of Duplex Stainless Steel Fabricated by Wire Arc Additive Manufacturing with ER2209 Filler Wire 使用 ER2209 填充线的线弧快速成型技术制造的双相不锈钢的微结构演变、机械和电化学性能

IF 2.2 3区材料科学 Q2 METALLURGY & METALLURGICAL ENGINEERING

steel research international

Pub Date : 2024-08-24 DOI: 10.1002/srin.202400425

Sanjeevi Prakash Karunanithi, Rajesh Kannan Arasappan, Siva Shanmugam Nallathambi

This study examines the dependent relationship between microstructure, mechanical properties, and corrosion performance on the wire arc additive manufactured (WAAM) ER2209 duplex stainless steel (DSS). DSS is renowned for its corrosion resistance and mechanical strength, making it favorable for various applications. This study uses the gas metal arc welding (GMAW)‐ based WAAM technique to fabricate the wall structure using ER2209 DSS filler wire. Fine, equiaxed dendrites are formed along the build direction, with the austenite phase exceeding 70% due to the repeated heating and slow cooling inherent to WAAM process. X‐ray diffraction (XRD) confirms no brittle intermetallic phases. The results shows that varying austenite‐ferrite fractions significantly influences the anisotropy in mechanical properties between build and deposit directions. Along the build direction, the varying phase fraction causes difference in hardness of 19.59 HV0.3 and tensile strength of 20 MPa. The maximum tensile strength (787.08 MPa) is observed in the deposit direction, with a 52 MPa difference between the build and deposit directions. Tafel and EIS measurements indicated that WAAM samples corrosion resistance was almost close to wrought 2205 DSS. This study highlights WAAM's potential for defect‐free DSS parts and suggests post‐heat treatment to optimize microstructure and mechanical properties.

本研究探讨了线弧添加剂制造（WAAM）的 ER2209 双相不锈钢（DSS）的微观结构、机械性能和腐蚀性能之间的依存关系。双相不锈钢以其耐腐蚀性和机械强度而闻名，因此适合各种应用。本研究采用基于气体金属弧焊（GMAW）的 WAAM 技术，使用 ER2209 DSS 焊丝制造壁结构。由于 WAAM 工艺固有的反复加热和缓慢冷却特性，沿构建方向形成了细小的等轴树枝状晶，奥氏体相超过 70%。X 射线衍射 (XRD) 证实没有脆性金属间相。研究结果表明，奥氏体-铁素体比例的变化极大地影响了构建方向和沉积方向之间机械性能的各向异性。沿着构建方向，不同的相分数会导致 19.59 HV0.3 的硬度差异和 20 兆帕的抗拉强度差异。最大拉伸强度（787.08 兆帕）出现在沉积方向，构建方向和沉积方向之间相差 52 兆帕。Tafel 和 EIS 测量表明，WAAM 样品的耐腐蚀性几乎接近锻造 2205 DSS。这项研究强调了 WAAM 在制造无缺陷 DSS 零件方面的潜力，并建议进行后热处理以优化微观结构和机械性能。

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引用次数: 0

Optimization of Blast Furnace Ironmaking Using Machine Learning and Genetic Algorithms 利用机器学习和遗传算法优化高炉炼铁工艺

IF 2.2 3区材料科学 Q2 METALLURGY & METALLURGICAL ENGINEERING

steel research international

Pub Date : 2024-08-23 DOI: 10.1002/srin.202300788

Manendra Singh Parihar, Sri Harsha Nistala, Rajan Kumar, Sristy Raj, Adity Ganguly, Venkataramana Runkana

Blast furnace is a multiphase counter‐current packed bed reactor that converts iron‐bearing materials such as lumps, sinter, and pellets into hot metal using metallurgical coke and pulverized coal. The quality of input materials has a significant impact on furnace performance, hot metal quality and steel plant economics. It is difficult for operators to identify the optimal settings required for efficient and safe operation based on their experience alone, given the large number of furnace parameters. A multiobjective optimization problem for maximizing furnace productivity (PROD) and minimizing fuel rate (FR) with constraints on hot metal silicon (HMSi) and temperature (HMT) is formulated and solved using a genetic algorithm. Machine learning (ML) models are developed for PROD, FR, HMSi, and HMT and tested with data from an industrial blast furnace. Pareto‐optimal solutions along with optimal settings for key manipulated variables are obtained. It is demonstrated that PROD and FR can be improved by ≈3–5% at steady state. The overall ML model‐based optimization framework can be used as part of a blast furnace digital twin system to operate the furnace efficiently in real‐time for the given quality of raw materials.

高炉是一种多相逆流填料床反应器，利用冶金焦和煤粉将块料、烧结矿和球团等含铁材料转化为热金属。投入材料的质量对高炉性能、热金属质量和炼钢厂经济效益有重大影响。由于熔炉参数众多，操作员很难仅凭经验确定高效安全运行所需的最佳设置。在热金属硅（HMSi）和温度（HMT）的约束下，制定并使用遗传算法解决了最大化高炉生产率（PROD）和最小化燃料率（FR）的多目标优化问题。针对 PROD、FR、HMSi 和 HMT 开发了机器学习 (ML) 模型，并使用工业高炉的数据进行了测试。获得了帕累托最优解以及关键操作变量的最优设置。结果表明，在稳定状态下，PROD 和 FR 可提高 ≈3-5%。基于 ML 模型的整体优化框架可作为高炉数字孪生系统的一部分，针对给定的原材料质量实时有效地操作高炉。

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引用次数: 0

Effects of Pre‐Placed Nano‐TiC Powder on the Performance of Steel/Aluminum Laser Welded Joints 预铺纳米钛碳粉对钢/铝激光焊接接头性能的影响

IF 2.2 3区材料科学 Q2 METALLURGY & METALLURGICAL ENGINEERING

steel research international

Pub Date : 2024-08-23 DOI: 10.1002/srin.202400470

Zhiwei Zhu, Yonghuan Guo, Xinran Zhang, Xiangning Lu, Xiwen Wang

The steel/aluminum dissimilar metal welding plays a significant role in lightweighting automotive structures. However, the formation of hard and brittle intermetallic compounds (IMCs) in steel/aluminum welded joints severely compromises their mechanical performance. Nano ceramic particles such as TiC possess characteristics that inhibit the diffusion of Fe and Al, thereby exhibiting a significant advantage in suppressing IMCs formation in steel/aluminum welded joints. In this study, an optimized laser‐welding process is employed to investigate the mechanical properties of steel/aluminum dissimilar metal joints with different concentrations of TiC nanoparticles. It is aimed to determine the optimal TiC addition concentration by comparing the mechanical performance. Additionally, the inhibitory effect of TiC particles on the formation and growth of brittle Fe–Al IMCs is explored through an analysis of IMCs growth kinetics. In the research results, it is shown that the optimal TiC addition concentration is 1%. At this concentration, the tensile strength of the steel/aluminum welded joint reaches 98.29 MPa, showing a remarkable improvement of 32.65% compared to the sample without TiC addition. The addition of TiC particles suppresses the mutual diffusion between Fe and Al, reduces the generation of brittle IMCs, and enhances the mechanical performance of the steel/aluminum joint.

钢/铝异种金属焊接在汽车结构轻量化方面发挥着重要作用。然而，在钢/铝焊接接头中形成的硬脆金属间化合物（IMC）会严重影响其机械性能。TiC 等纳米陶瓷颗粒具有抑制铁和铝扩散的特性，因此在抑制钢/铝焊接接头中 IMC 的形成方面具有显著优势。在本研究中，采用了优化的激光焊接工艺来研究含有不同浓度 TiC 纳米粒子的钢/铝异种金属焊点的机械性能。目的是通过比较机械性能确定最佳的 TiC 添加浓度。此外，还通过分析 IMCs 生长动力学，探讨了 TiC 颗粒对脆性铁铝 IMCs 的形成和生长的抑制作用。研究结果表明，TiC 的最佳添加浓度为 1%。在此浓度下，钢/铝焊接接头的抗拉强度达到 98.29 MPa，与未添加 TiC 的样品相比，显著提高了 32.65%。TiC 颗粒的添加抑制了铁和铝之间的相互扩散，减少了脆性 IMC 的产生，提高了钢/铝接头的机械性能。

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引用次数: 0

Isothermal Reduction Behavior of Oxide Scale on the Surface of Hot‐Rolled Strip Steel Under Different Hydrogen Concentrations 不同氢气浓度下热轧带钢表面氧化皮的等温还原行为

IF 2.2 3区材料科学 Q2 METALLURGY & METALLURGICAL ENGINEERING

steel research international

Pub Date : 2024-08-23 DOI: 10.1002/srin.202400375

Shuai He, Zhi‐Feng Li, Xin Liu, Xu‐Ming Liu, Jun‐Sheng Wang

The oxide scale on the surface of hot‐rolled low‐carbon steel strips is subjected to isothermal reduction in 10 vol%H2–Ar and 20 vol%H2–Ar environments to simulate the reduction process that occurs in a continuous annealing furnace. The influence of hydrogen concentration on the reduction kinetics and the microstructural evolution of the oxide scale after reduction at temperatures ranging from 450 to 850 °C for a duration of 20 min are investigated in detail. The mass changes of the oxide scale in the two gases are quantified using a thermogravimetric analyzer. This data is then employed to calculate the reduction rate constant and the apparent activation energy. To examine the microstructure and element distribution, electron probe microanalysis and energy‐dispersive spectrometry are employed. An novel approach is also undertaken to assess the reduction degree of the oxide scale by measuring surface microhardness. In the findings, it is indicated that an increase in hydrogen concentration served primarily to accelerate the reduction reaction within the temperature ranges of 450–550 and 800–850 °C. Meanwhile, the mechanism of physical transformation of oxide scale, the microstructure of reduction layer, and hydrogen concentration on reduction efficiency under different reaction stages are proposed.

在 10 vol%H2-Ar 和 20 vol%H2-Ar 环境中对热轧低碳钢带表面的氧化鳞进行等温还原，以模拟连续退火炉中的还原过程。详细研究了氢浓度对还原动力学的影响以及氧化鳞片在 450 至 850 °C 温度下持续 20 分钟还原后的微观结构演变。使用热重分析仪对两种气体中氧化鳞片的质量变化进行了量化。然后利用这些数据计算还原速率常数和表观活化能。为了检查微观结构和元素分布，采用了电子探针显微分析法和能量色散光谱法。此外，还采用了一种新方法，通过测量表面微硬度来评估氧化鳞片的还原程度。研究结果表明，在 450-550 ℃ 和 800-850 ℃ 的温度范围内，氢浓度的增加主要起到加速还原反应的作用。同时，提出了不同反应阶段下氧化鳞的物理变化、还原层的微观结构和氢浓度对还原效率的影响机理。

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引用次数: 0

Implementing Single‐Roller Hard Reduction Technology for High‐Speed Production of High‐Carbon Hard Wire Steel Billets 实施单辊减硬技术，高速生产高碳硬线钢钢坯

IF 2.2 3区材料科学 Q2 METALLURGY & METALLURGICAL ENGINEERING

steel research international

Pub Date : 2024-08-23 DOI: 10.1002/srin.202400250

Wen‐Xing Gao, Chang‐Chuan Xie, Jianke Li, Richeng Liang, Jiaming Liu, Liang Qian

The production of high‐carbon hard wire steel at high speeds necessitates the use of appropriate technical support to ensure cost‐efficiency and optimal performance of the special steel casting machine. This study investigates the industrial application of single‐roller hard reduction technology in a domestic steel plant for the production of high‐carbon hard wire steel billets, specifically of section 165 × 165 mm. The produced billets meet all customer specifications and demonstrate the benefits of this approach, including lower comprehensive costs, suitability for modification, and advanced technical concepts. These features make this method compatible with a wide range of billet casting machines, from standard to specialized. In this research, discussion is done on the reduction process, the layout of withdrawal and straightening units (WSUs), and the optimal casting speed. It is concluded that bow‐type billet casting machines using rigid dummy bars can achieve single‐roller hard reduction by only three WSUs, offering lower comprehensive costs and suitability for modification. This approach is particularly beneficial for small billet casting machines undergoing an upgrade from general to high‐quality and ultimately to special steel. During the process of increasing the central density of the billet and improving central defects using single‐roller hard reduction technology, it is observed that defects in the central region gravitated toward the center. For billet casting machines with a bow radius of 10 m, considering process tolerance, the maximum casting speeds achievable with single‐roller hard reduction are 2.95–3.40 m min−1 for a section of 150 × 150 mm, 2.60–3.0 m min−1 for a section of 160 × 160 mm, and 2.45–2.80 m min−1 for a section of 165 × 165 mm. To achieve higher casting speeds for high‐carbon hard wire steel, it is necessary to modify the machine configuration to flexible dummy bars.

要高速生产高碳硬线钢，就必须使用适当的技术支持，以确保特种钢铸造机的成本效益和最佳性能。本研究调查了单辊硬减径技术在国内一家钢铁厂生产高碳硬线钢方坯（截面尺寸为 165 × 165 毫米）中的工业应用。所生产的钢坯符合客户的所有规格要求，并证明了这种方法的优势，包括综合成本较低、适合改装以及技术理念先进。这些特点使这种方法与从标准到专用的各种方坯铸造机兼容。在这项研究中，对还原过程、退坯和矫直装置（WSU）的布局以及最佳铸造速度进行了讨论。研究得出结论，使用刚性虚杆的弓形小方坯铸造机只需三个 WSU 即可实现单辊硬减径，综合成本较低，适合改装。这种方法尤其适用于从普通钢升级到优质钢，并最终升级到特种钢的小型方坯铸造机。在使用单辊硬减径技术提高方坯中心密度和改善中心缺陷的过程中，发现中心区域的缺陷向中心倾斜。对于弓形半径为 10 米的方坯铸造机，考虑到工艺公差，采用单辊硬齿面技术实现的最大铸造速度为：截面为 150 × 150 毫米的铸坯，2.95-3.40 m min-1；截面为 160 × 160 毫米的铸坯，2.60-3.0 m min-1；截面为 165 × 165 毫米的铸坯，2.45-2.80 m min-1。为了提高高碳硬线钢的浇铸速度，有必要对机器配置进行修改，使其具有灵活的假棒材。

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引用次数: 0

Machine Learning-Based Prediction of the Martensite Start Temperature 基于机器学习的马氏体起始温度预测

IF 1.9 3区材料科学 Q2 METALLURGY & METALLURGICAL ENGINEERING

steel research international

Pub Date : 2024-08-22 DOI: 10.1002/srin.202400210

Marcel Wentzien, Marcel Koch, Thomas Friedrich, Jerome Ingber, Henning Kempka, Dirk Schmalzried, Maik Kunert

The prediction of the martensite start temperature ( $� � �_{M � s �} �$ ) for steels based on their chemical compositions is a complex problem. Previous work has developed empirical, thermodynamic, and machine learning models to estimate $� � �_{M � s �} �$ . However, the empirical models are limited to specific steel grades, the thermodynamic models rely on different model assumptions, and the machine learning models are based on a small number of data, are limited to specific steel grades, as well or are not available for easy use to the public. Herein, a new machine learning model for the prediction of $� � �_{M � s �} �$ is developed on the basis of two publicly available datasets consisting of 1800 steels from different steel grades. Extensive hyperparameter tuning is performed to find the best artificial neural network for the dataset. The best model improves prediction accuracy compared to previous state of the art. Despite a very good prediction accuracy of the model, unexpected behavior is observed in specific unseen data. This opens up the discussion for the requirements of new metrics. The dataset and the model are freely available at https://github.com/EAH-Materials. An easy-to-use web tool to estimate $� � �_{M � s �} �$ without the need of programming based on the chemical composition can be found at https://eah-jena-ms-predictor.streamlit.app/.

根据钢的化学成分预测其马氏体开始温度（）是一个复杂的问题。以前的工作已经开发了经验模型、热力学模型和机器学习模型来估计马氏体开始温度（）。然而，经验模型仅限于特定的钢种，热力学模型依赖于不同的模型假设，而机器学习模型则基于少量数据，仅限于特定的钢种，或者不便于公众使用。在此，我们以两个公开数据集为基础，开发了一种新的机器学习模型，用于预测不同钢种的 1800 种钢材。通过广泛的超参数调整，为数据集找到了最佳的人工神经网络。与之前的技术水平相比，最佳模型提高了预测精度。尽管该模型的预测精度非常高，但在特定的未见数据中却出现了意想不到的行为。这引发了对新指标要求的讨论。数据集和模型可在 https://github.com/EAH-Materials 免费获取。根据化学成分进行估算而无需编程的易用网络工具可在 https://eah-jena-ms-predictor.streamlit.app/ 上找到。

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引用次数: 0

The Steelmaking Transformation Process and Its Consequences for Slag Utilization 炼钢转变过程及其对炉渣利用的影响

IF 2.2 3区材料科学 Q2 METALLURGY & METALLURGICAL ENGINEERING

steel research international

Pub Date : 2024-08-19 DOI: 10.1002/srin.202400234

Andreas Ehrenberg

The main challenge of the European steel industry for the next decade is the steel production transformation process. Many steel producers aim to avoid their CO2 emissions by substituting the CO2‐intensive blast furnace/basic oxygen furnace route by a gas‐based direct reduced iron (DRI) process combined with an electric smelting process. Thus, the well‐known latent hydraulic granulated blast furnace slag (GBS) will vanish step by step. For more than 140 years, this slag has been used as a supplementary cementitious material due to its clinker reduction potential and from there its CO2 reduction potential for the cement and concrete production. Moreover, slag cements offer some special technical advantages. Whereas the solid‐state DRI process itself does not generate any slag, the different electric smelting processes will produce liquid steel or “electric” pig iron, respectively, together with very different types of slags. However, specific slag/metal ratios, resulting slag volumes, chemical and mineralogical composition, and physical properties of the new slags are yet unknown. Therefore, their cementitious and environmental properties are also still unknown. Different current and scheduled projects aim mainly to enable the different types of new slags to substitute GBS to continue the successful cross‐industrial cooperation between steel and cement industry.

未来十年，欧洲钢铁工业面临的主要挑战是钢铁生产转型过程。许多钢铁生产商的目标是，用气体直接还原铁（DRI）工艺结合电炉冶炼工艺，取代二氧化碳密集型高炉/碱性氧气炉工艺，从而避免二氧化碳排放。因此，众所周知的水力造粒高炉渣（GBS）将逐步消失。140 多年来，由于矿渣具有减少熟料的潜力，因此在水泥和混凝土生产中具有减少二氧化碳排放的潜力，一直被用作水泥基辅材料。此外，矿渣水泥还具有一些特殊的技术优势。固态 DRI 工艺本身不会产生炉渣，而不同的电炉冶炼工艺则会分别产生液态钢或 "电 "生铁，同时产生不同类型的炉渣。然而，新炉渣的具体炉渣/金属比例、产生的炉渣量、化学和矿物成分以及物理性质尚不清楚。因此，它们的胶凝特性和环境特性也仍然未知。目前正在进行和计划进行的不同项目的主要目的是使不同类型的新炉渣能够替代 GBS，以继续钢铁和水泥行业之间成功的跨行业合作。

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引用次数: 0

Microstructural Evolution and Hot Deformation Behavior of Cu-Containing Twinning-Induced Plasticity Steel 含铜孪晶诱导塑性钢的微观结构演变和热变形行为

IF 1.9 3区材料科学 Q2 METALLURGY & METALLURGICAL ENGINEERING

steel research international

Pub Date : 2024-08-19 DOI: 10.1002/srin.202400335

Yang Feng, Xiaoyun Yuan, Yang Zhao, Liqing Chen

High manganese twinning-induced plasticity (TWIP) steels with excellent strength and plasticity have promising applications in automotive manufacturing, but limited corrosion resistance affects their further development. Alloying with Cu is a viable solution to improve corrosion resistance. However, there remains a paucity of research concerning the effect of Cu on the hot deformation behavior of TWIP steels. So, the investigation of the recrystallization behavior and microstructural evolution in Fe-23Mn-6Cr-3Al-0.2C-xCu (x = 0, 2.5) TWIP steels has been conducted using uniaxial hot compression test. The results reveal that Cu alloying exerts minimal influence on the high-temperatur flow behavior, with dynamic recrystallization emerging as the predominant softening mechanism in Cu-containing TWIP steels. However, owing to the drag effect of solute atoms, Cu alloying increases the activation energy for hot deformation and marginally reduces hot workability. Fine recrystallized grains in Cu-containing TWIP steels can be achieved by hot deformation at lower temperatures and strain rate regions. The recrystallization behavior of Cu-containing TWIP steels hot deformed at low temperatures and high strain rates is obviously inhibited by the increase of the activation energy and stacking fault energy, coupled with the hindering effect of Cu solute atoms clustered at grain boundaries on grain boundary migration.

高锰孪晶诱导塑性钢（TWIP）具有优异的强度和塑性，在汽车制造领域有着广阔的应用前景，但有限的耐腐蚀性影响了其进一步发展。与铜进行合金化是提高耐腐蚀性的可行解决方案。然而，有关 Cu 对 TWIP 钢热变形行为影响的研究仍然很少。因此，我们使用单轴热压缩试验对 Fe-23Mn-6Cr-3Al-0.2C-xCu (x = 0, 2.5) TWIP 钢的再结晶行为和微观结构演变进行了研究。结果表明，铜合金对高温流动行为的影响微乎其微，动态再结晶是含铜 TWIP 钢的主要软化机制。然而，由于溶质原子的拖曳效应，铜合金增加了热变形的活化能，并略微降低了热加工性能。含铜 TWIP 钢中的细小再结晶晶粒可通过在较低温度和应变率区域进行热变形来实现。在低温和高应变率下热变形的含铜 TWIP 钢的再结晶行为明显受到活化能和堆积断层能增加的抑制，再加上晶界上聚集的铜溶质原子对晶界迁移的阻碍作用。

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引用次数: 0

Modeling of Arcing, Scrap Melting, and Temperature Evolution in the Refractory of a Lab‐Scale Direct Current‐Electric Arc Furnace 实验室规模直流电弧炉耐火材料中的电弧、废料熔化和温度变化建模

IF 2.2 3区材料科学 Q2 METALLURGY & METALLURGICAL ENGINEERING

steel research international

Pub Date : 2024-08-19 DOI: 10.1002/srin.202300696

Dinesh Nath, Sumanta Maji, Amarendra K. Singh

Refractory linings of electric arc furnaces are subjected to intense thermal loads, leading to occasional failure of the insulating bricks. A numerical model that simulates the phenomena of arcing, scrap melting, and the transient thermal evolution in the refractory lining of a laboratory‐scale direct current‐electric arc furnace (DC‐EAF) is developed. The rise in the temperature of the refractory lining depends on many factors, including the duration of the melting operation, the intensity and duration of arcing, the design of the furnace, thermophysical properties, and the thickness of the lining. Continuum formulation‐based equations for the transport of momentum, energy, and species, auxiliary models of phase changes associated with scrap melting and evaporation of metal under the arc and Maxwell's equations are solved in a conjugate domain to model the progress of the melting of the scarp and temperature evolution in the refractory lining. Combining experimental data from lab‐scale DC‐EAF, the model is enhanced to represent the laboratory experiment. Scrap with high porosity needs more time for melting, and thermal damage of refractory lining is linked to prolonged arcing coupled with the poor quality of refractory materials.

电弧炉的耐火衬承受着强烈的热负荷，导致绝缘砖偶尔失效。本研究开发了一个数值模型，用于模拟实验室规模的直流电弧炉（DC-EAF）耐火衬的起弧、废料熔化和瞬态热演变现象。耐火内衬温度的升高取决于许多因素，包括熔化操作的持续时间、电弧的强度和持续时间、熔炉的设计、热物理性质以及内衬的厚度。我们在共轭域中求解了基于连续公式的动量、能量和物种传输方程，与电弧下金属废料熔化和蒸发相关的相变辅助模型，以及麦克斯韦方程，以模拟疤痕的熔化过程和耐火衬里的温度变化。结合实验室规模 DC-EAF 的实验数据，增强了模型对实验室实验的代表性。孔隙率高的废料需要更长的熔化时间，耐火衬的热损伤与长时间电弧和耐火材料质量差有关。

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引用次数: 0