Study of Low Carbon Low Alloy Steel Annealing Process Parameters Optimization

التفاصيل البيبلوغرافية
العنوان: Study of Low Carbon Low Alloy Steel Annealing Process Parameters Optimization
المؤلفون: Mao Yu Zhao, Qian Wang Chen
المصدر: Advanced Materials Research. :649-659
بيانات النشر: Trans Tech Publications, Ltd., 2013.
سنة النشر: 2013
مصطلحات موضوعية: Toughness, Materials science, Annealing (metallurgy), Alloy steel, Metallurgy, General Engineering, engineering, Lamellar structure, engineering.material, Pearlite, Plasticity, Microstructure, Tensile testing
الوصف: A suitable match of annealing process parameters is critical for obtaining the fine microstructure of material. Low carbon low alloy steel (20CrMnTi) was heated for various durations near Ac temperature to achieve fine pearlite and ferrite grains. Annealing temperature and time were used as independent variables, and material property data were acquired by orthogonal experiment under intercritical annealing followed by subcritical annealing process (IASAP). The weights of plasticity (hardness, yield strength, section shrinkage, and elongation) of annealing material were calculated by analytic hierarchy process, and then the process parameters were optimized by using the grey theory system. The results observed by SEM images show that the optimized material microstructure consists of refining and distributing uniformly ferrite-pearlite grains, and smaller lamellar cementites. Morphologies on tension fracture surface of the optimized material indicates that the numbers of dimple fracture show more finer toughness obviously comparing with other annealing materials. Moreover, the yield strength value of the optimized material decreases apparently measured by tensile test. Thus, the new optimized strategy is accurate and feasible.
تدمد: 1662-8985
URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_________::01108d2904d1839106e32e3bd2488b30
https://doi.org/10.4028/www.scientific.net/amr.631-632.649
حقوق: CLOSED
رقم الأكسشن: edsair.doi...........01108d2904d1839106e32e3bd2488b30
قاعدة البيانات: OpenAIRE