A growing need to reduce the environmental impact and cost of manufacturing stainless steels has led to the development of ferritic stainless steel as an alternative to austenitic and duplex steels. The development of new stainless steels involves the optimization of their hot rolling processes, with the aim of minimizing the occurrence of defects and improving productivity. In this context, numerical simulation using the finite element method (FEM) is presented as a key tool to reduce the time and cost associated with traditional trial-and-error optimization methods. Previous work oriented towards the simulation of stainless steels has been focused on the study of small samples, on the performance of laboratory-scale tests, and on the use of 2D FEM models. In this study, a three-dimensional FEM model is proposed to simulate the hot rolling process of large-scale AISI 430 ferritic stainless-steel slabs using an industrial rolling schedule employed in the actual manufacturing process of flat products. Model optimization is performed in order to reduce the computational cost of the simulations, based on the simulation of the first pass of the hot rolling process of AISI 430 stainless steel. The results show that model optimization reduces the computational time by 90.2% without compromising the accuracy of the results. Thus, it was found that the results for thickness and rolling load showed a good correlation with the experimental values. In addition, the simulations performed allowed for the analysis of the distribution of temperature and effective plastic strain.
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http://dx.doi.org/10.3390/ma18020383 | DOI Listing |
Sci Rep
January 2025
Xingtai Naknor Technology Co., Ltd, Xingtai, 054000, China.
The heating oil circuit plays an essential role in the heating calendering roller for the lithium battery pole piece. To achieve the optimization of the heating oil circuit, a fluid-thermal-structural coupling method and a multi-objective optimization procedure are proposed to obtain the optimal solution. A fluid-thermal-structural coupling flowchart based on the numerical modeling for the calendering roller temperature distribution is created to automate the analysis processes in the optimization iteration.
View Article and Find Full Text PDFMaterials (Basel)
January 2025
Department of Materials Science and Metallurgical Engineering and Inorganic Chemistry, Faculty of Sciences, University of Cadiz, Campus Río San Pedro S/N, 11510 Cadiz, Spain.
A growing need to reduce the environmental impact and cost of manufacturing stainless steels has led to the development of ferritic stainless steel as an alternative to austenitic and duplex steels. The development of new stainless steels involves the optimization of their hot rolling processes, with the aim of minimizing the occurrence of defects and improving productivity. In this context, numerical simulation using the finite element method (FEM) is presented as a key tool to reduce the time and cost associated with traditional trial-and-error optimization methods.
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January 2025
School of Materials Science and Engineering, Shenyang Ligong University, Shenyang, 110159, China.
To enhance the mechanical properties and electrical conductivity of Al-Cu-Mg-based composites, aluminum matrix composites containing scandium (Sc) and graphene nanoplatelets (GNPs) were fabricated by means of stepwise ball milling, vacuum hot pressing sintering, and hot rolling techniques. When Sc and GNPs were incorporated at concentrations of 0.1 wt% and 0.
View Article and Find Full Text PDFHeliyon
January 2025
Department of Chemical Engineering, School of Chemical and Materials Engineering (SCME), National University of Sciences & Technology (NUST), Sector H-12, Islamabad, 44000, Pakistan.
This study examines the viability of using graphitic-Carbon Nitride (g-CN) nanomaterial as shale stabilizer drilling fluid additive having applications in the oil and gas wells drilling. Shale stability is important especially when drilling horizontal and extended reach wells with water-based muds (WBM) to tap unconventional reservoirs namely shale oil and shale gas. For this study, the g-CN nanomaterial was produced by melamine pyrolysis, and characterized by X-Ray Diffraction, Scanning Electron Microscopy and Fourier Transform Infrared spectroscopy techniques.
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January 2025
State Key Laboratory of Metallurgical Intelligent Manufacturing System, Beijing, 100071, China.
At present, the parameters of the controllers in hot rolling roughing microtension control systems are not adaptively adjustable to variations in working conditions, which compromises both width accuracy and production stability. To address this issue, this paper introduces an ATKB-PID adaptive micro tension control method. This method incorporates a linear attention layer and utilizes a K-Nearest Neighbors (KNN) algorithm to predict the optimal learning rate and inertia coefficient under actual operating conditions.
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