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Iron & Steel Technology最新文献

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How Computers Shaped Steel During the Digital Revolution, With Special Reference to North America 计算机如何在数字革命中塑造钢铁,特别关注北美地区
Pub Date : 2024-07-20 DOI: 10.33313/tr/0824
Nirbhar Neogi
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引用次数: 0
Effect of Recycling Sinter Dust as Calcium Ferrite in the Sintering Process on Sinter Quality and Emissions of CO2, NO, and SO2 在烧结工艺中回收烧结粉尘作为钙铁氧体对烧结质量以及 CO2、NO 和 SO2 排放的影响
Pub Date : 2024-05-20 DOI: 10.33313/tr/0624
L. Tomas Da Rocha, S. Cho, S.W. Kim, S.M. Jun
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引用次数: 0
Investigation of the Thermally Thick Alternative Reducing Agent Behavior in the Raceway Zone 调查热厚替代还原剂在赛道区的行为
Pub Date : 2024-02-20 DOI: 10.33313/tr/0324
Matthias Kiss, M. Bösenhofer, F. Hauzenberger, Hugo Stocker, C. Feilmayr, Michael Harasek
Alternative reducing agents (ARAs) injected into the raceway zone of the blast furnace have diameters in the range of tens to thousands of micrometers. Larger ARA particles can develop significant internal temperature and species concentration gradients. These gradients determine the thermochemical ARA conversion characteristics. To capture these effects, a resolved Lagrangian particle model was developed, which solves mass and energy transport equations on a 1D grid. The influence of the resolved model on the conversion characteristics in the raceway zone is compared to classical unresolved or 0D Lagrangian models using computational fluid dynamics simulations in OpenFOAM ® .
注入高炉滚道区的替代还原剂(ARA)直径在几十到几千微米之间。较大的 ARA 颗粒会产生明显的内部温度和物种浓度梯度。这些梯度决定了 ARA 的热化学转化特性。为了捕捉这些影响,我们开发了一个解析拉格朗日粒子模型,在一维网格上求解质量和能量传输方程。利用 OpenFOAM ® 中的计算流体动力学模拟,比较了解析模型与经典的非解析或 0D 拉格朗日模型对流道区转化特性的影响。
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引用次数: 0
Bubble Size Determination in a Half-Scale Curved Water Model Mold for Various Casting Conditions Using Imaging and Machine Learning 利用成像和机器学习确定各种铸造条件下半刻度曲面水模中的气泡大小
Pub Date : 2024-01-20 DOI: 10.33313/tr/0224
S. Dinda, Donghui Li, Fernando Guerra, Chad Cathcart, M. Barati
Parametric studies were performed in a 1:2 scaled, curved water model using shadowgraphy to estimate bubble sizes for different casting parameters such as gas flow rate, liquid flow rate and mold width. Bubble diameter calculations were based on a machine learning algorithm using ImageJ software. Bubble diameters were correlated with input parameters using a deep-learning algorithm. The model performance was determined based on the coefficient of determination (R 2 ). The model showed significant promise with bootstrapping aggregation, validated with five-fold cross-validation and improved accuracy.
在 1:2 比例的曲面水模型中进行了参数研究,使用阴影图估算不同铸造参数(如气体流速、液体流速和模具宽度)下的气泡大小。气泡直径的计算基于使用 ImageJ 软件的机器学习算法。使用深度学习算法将气泡直径与输入参数相关联。根据判定系数 (R 2 ) 确定模型性能。经五倍交叉验证后,该模型在引导聚合方面显示出了巨大的潜力,并提高了准确性。
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引用次数: 0
Titanium Nitride Nucleation and Growth During Steel Solidification 钢凝固过程中的氮化钛成核与生长
Pub Date : 2023-12-20 DOI: 10.33313/tr/0124
P. Wilkerson, P. Pistorius, B. Webler
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引用次数: 0
Understanding the Behavior of Ti in Ultralow-C Liquid Steel 了解Ti在超低碳钢液中的行为
Pub Date : 2023-10-20 DOI: 10.33313/tr/1123
Youngjeong Kang, Young-Joon Park, Dong-Hyun Kim, Joo-Hyeok Lee
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引用次数: 0
Electroslag Processing of High-Temperature Alloy Shavings 高温合金刨花的电渣处理
Pub Date : 2023-08-20 DOI: 10.33313/tr/0923
F. K. Biktagirov, O.V. Veretilnyk, V. O. Shapovalov, O.V. Hnatushenko, A. Ignatov, V. Barabash
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引用次数: 0
Mixed-Control Kinetic Model of Magnesia-Based Flux Dissolution in BOF Steelmaking Slags: Part 2 Model Validation With Real-Time Plant Data 转炉炼钢渣中镁基熔剂溶解混合控制动力学模型:第二部分:实时工厂数据模型验证
Pub Date : 2023-01-20 DOI: 10.33313/tr/0223
K. Sahoo
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引用次数: 0
Mixed-Control Kinetic Model of Magnesia-Based Flux Dissolution in BOF Steelmaking Slags: Part 1 - Model Formulation and Validation With Literature Data 转炉炼钢渣中镁基熔剂溶解的混合控制动力学模型:第一部分-模型的建立和文献数据的验证
Pub Date : 2022-12-20 DOI: 10.33313/tr/0123
K. Sahoo
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引用次数: 0
Optimization of Aluminum Deoxidation Practice in the Ladle Furnace 钢包炉铝脱氧工艺的优化
Pub Date : 2022-06-20 DOI: 10.33313/tr/0722
K. Sahoo, R. Pathak
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引用次数: 0
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Iron & Steel Technology
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