کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
1563964 999627 2008 13 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Neural network analysis of the influence of chemical composition on surface cracking during hot rolling of AISI D2 tool steel
موضوعات مرتبط
مهندسی و علوم پایه سایر رشته های مهندسی مکانیک محاسباتی
پیش نمایش صفحه اول مقاله
Neural network analysis of the influence of chemical composition on surface cracking during hot rolling of AISI D2 tool steel
چکیده انگلیسی

The reasons for the formation of surface cracks during the hot rolling of tool steels are not well understood. However, we know that apart from the parameters of the thermo-mechanical processing, the chemical composition of the tool steel has a big influence on the formation of these surface cracks. The majority of examinations of the hot deformability (appearance of surface cracks) of various steel grades made so far were limited to studying the influence of a minor number of chemical elements on the formation of the surface cracks, where the databases were based on laboratory tests. This paper proposes a new approach to the study of hot workability by analysing crack formation during the hot rolling of AISI D2 tool steel. The database was formed on the results from the surface cracking of rolling stock in an industrial rolling process and the rolling stock’s chemical composition. The analysis of the spatial influence was performed with CAE neural networks, and included an analysis of the influence of carbon and carbide-forming elements, of manganese and sulphur, copper, tin, aluminium, etc. The results of the analyses revealed a new understanding of the influences, and thus also the possibility to reduce the amount of surface cracking if the chemical concentrations of the elements were to be closer to the exactly determined values, or closer to the more exactly determined ratios.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computational Materials Science - Volume 42, Issue 4, June 2008, Pages 625–637
نویسندگان
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