Analysing the degree of sensitisation in 5xxx series aluminium alloys using artificial neural networks: A tool for alloy design

Ruifeng Zhang, Jinfeng Li*, Qian Li, Yuanshen Qi, Zhuoran Zeng, Yao Qiu, Xiaobo Chen, Shravan K. Kairy, Sebastian Thomas, Nick Birbilis

*Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review

    29 Citations (Scopus)

    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.

    Original languageEnglish
    Pages (from-to)268-278
    Number of pages11
    JournalCorrosion Science
    Volume150
    DOIs
    Publication statusPublished - 15 Apr 2019

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