The Neural Network Modeling of Titanium Alloy Phase Transformation and Mechanical Properties

被引：10
|
作者：
Malinov, S. [1 ]
Sha, W. [2 ]
机构：
[1] Queens Univ Belfast, Sch Mech & Aerosp Engn, Belfast, Antrim, North Ireland
[2] Queens Univ Belfast, Sch Planning Architecture & Civil Engn, Met Res Grp, Belfast BT7 1NN, Antrim, North Ireland
来源：
JOM | 2005年 / 57卷 / 11期
关键词：
Titanium Alloy; Neural Network Model; Trained Neural Network; Increase Aluminum Content; Fine Lamellar;
D O I：
10.1007/s11837-005-0028-y
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
This paper is a summary of titanium research developments involving the use of artificial neural networks. Several models and modules have been designed, trained, and integrated into software products for simulating, monitoring, and predicting a variety of correlations and phenomena between chemistry and processing conditions and end properties in titanium alloys. The models are based on literature data, the results of which are compared with experimental data. The models are used to trace and analyze the influence of different parameters such as alloy composition and processing conditions on the beta-to-alpha phase transformation characteristics and properties in titanium alloys.
引用
收藏
页码：54 / 57
页数：4
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