About this Abstract |
Meeting |
1st World Congress on Artificial Intelligence in Materials and Manufacturing (AIM 2022)
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Symposium
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First World Congress on Artificial Intelligence in Materials and Manufacturing (AIM 2022)
|
Presentation Title |
Multi-scale Structure-Property Relationships in Low Carbon Steels |
Author(s) |
Johan Westraadt, Lindsay Westraadt |
On-Site Speaker (Planned) |
Johan Westraadt |
Abstract Scope |
Small-punch creep (SPC) testing is currently used to evaluate the creep-rupture properties of steels used in the petrochemical and power generating industries. This study explores microstructure-property relationships in service-exposed low carbon steels using ML. These models can be used to rank the microstructural features in terms of their importance on the SPC-test and prioritize/reduce SPC testing requirements. A dataset consisting of 120x3 steel microstructures and their associated SPC-rupture time was collected. Optical micrographs of the etched surfaces were quantified using various feature extraction methods including 1- and 2-point statistics, and convolutional neural networks. The extracted microstructural features were then reduced using PCA and used as inputs for training regression models using different ML techniques. A selection of 10 samples with the largest testing errors were then investigated using secondary electron imaging to incorporate the finer pearlite sub-structures. This multi-scale model had a lower training error for the outlier samples. |
Proceedings Inclusion? |
Undecided |