Application of artificial neural networks for modelling correlations in titanium alloys

被引:133
作者
Malinov, S [1 ]
Sha, W [1 ]
机构
[1] Queens Univ Belfast, Sch Civil Engn, Belfast BT7 1NN, Antrim, North Ireland
来源
MATERIALS SCIENCE AND ENGINEERING A-STRUCTURAL MATERIALS PROPERTIES MICROSTRUCTURE AND PROCESSING | 2004年 / 365卷 / 1-2期
基金
英国工程与自然科学研究理事会;
关键词
modelling; titanium alloys; neural network; titanium aluminides; mechanical properties; TTT diagrams;
D O I
10.1016/j.msea.2003.09.029
中图分类号
TB3 [工程材料学];
学科分类号
0805 ; 080502 ;
摘要
This paper is dedicated to the application of artificial neural networks (ANN) in titanium alloys research, including: (i) time-temperature transformation (TTT) diagrams for titanium alloys; (ii) correlation between processing parameters and properties in titanium alloys and gamma-TiAl-based alloys; (iii) fatigue stress life diagrams for Ti-6Al-4V alloy; (iv) corrosion resistance of titanium alloys. For each particular case, appropriate combination of inputs and outputs is chosen. Standard multilayer feedforward networks are created and trained using comprehensive datasets from published literature. Very good performances of the neural networks are achieved. Different effects are modelled, among which are: (i) influence of the alloying elements on the transformation kinetics in titanium alloys; (ii) influence of the processing parameters, alloy composition and the work temperature on the mechanical properties for titanium alloys and titanium aluminides; (iii) influence of the microstructure, temperature, environment, surface treatment and the stress ratio on the fatigue life. The artificial neural networks models are combined with computer programmes for optimisation of the inputs in order to achieve desirable combination of outputs. Graphical user interfaces are developed for use of the models. These models are convenient and powerful tools for practical applications in solving various problems in titanium alloys. (C) 2003 Elsevier B.V. All rights reserved.
引用
收藏
页码:202 / 211
页数:10
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