Analysing the degree of sensitisation in 5xxx series aluminium alloys using artificial neural networks: A tool for alloy design
Loading...
Date
Authors
Zhang, Ruifeng
Li, Jinfeng
Li, Qian
Qi, Yuanshen
Zeng, Zhouran
Qiu, Y.
Chen, Xiao-Bo
Kairy, Shravan K.
Thomas, S.
Birbilis, Nick
Journal Title
Journal ISSN
Volume Title
Publisher
Elsevier
Abstract
The 5xxx series aluminium alloys are susceptible to sensitisation during service at elevated temperatures. Sensitisation refers to deleterious grain boundary precipitation resulting in rapid intergranular corrosion in moist environments. A holistic understanding of the variables that can influence the degree of sensitisation in Al-Mg-Mn alloys is presented herein, including the exploration of some custom produced 5xxx series alloys that were prepared to create a significant dataset for which an artificial neural network (ANN) could be applied. An ANN model could reveal complex interactions between various factors that influence sensitisation, with the view to designing sensitisation resistant Al-Mg-Mn alloys.
Description
Keywords
Citation
Collections
Source
Corrosion Science
Type
Book Title
Entity type
Access Statement
License Rights
Restricted until
2037-12-31
Downloads
File
Description