کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
5455253 | 1514636 | 2017 | 21 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Artificial neural network application to microstructure design of Nb-Si alloy to improve ultimate tensile strength
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی مواد
دانش مواد (عمومی)
پیش نمایش صفحه اول مقاله
چکیده انگلیسی
In this paper, a feed forward neural network with back propagation artificial neural network (BP ANN) was developed to predict ultimate tensile strength (UTS) and optimize microstructure. The alloys were produced by directional solidification and heat treatment. The UTS was measured for ANN output. Five characteristic factors used for ANN input were abstracted and measured. As the result of this study, the ANN model with high accuracy and good generalization ability to predict UTS within the range of 343.5-1063.3Â MPa was established and mutual verified with sensitivity analysis. Based on the optimized ANN model, a new way to design microstructure of Nb-Si alloy to obtain required UTS was proposed. With silicide design maps made by ANN model, the microstructure of the sample of 343.5Â MPa was optimized and the UTS reached the target UTS (600Â MPa) successfully.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Materials Science and Engineering: A - Volume 707, 7 November 2017, Pages 452-458
Journal: Materials Science and Engineering: A - Volume 707, 7 November 2017, Pages 452-458
نویسندگان
Guangxu Liu, Lina Jia, Bin Kong, Shangbin Feng, Huarui Zhang, Hu Zhang,