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About this Abstract
Meeting 2021 TMS Annual Meeting & Exhibition
Symposium Algorithm Development in Materials Science and Engineering
Presentation Title Predicting Mechanical Property Parameters from Load-displacement Curve of Nanoindentation Test by Using Machine Learning Model
Author(s) Jin Myoung Jeon, Jungwook Cho, Kyojun Hwang
On-Site Speaker (Planned) Jin Myoung Jeon
Abstract Scope Nanoindentation test is a method that can measure the mechanical properties of the local region by applying compressive force. This method is effective on measuring the material properties of the multi-phase material or film layer. In this study, an artificial neural network model was trained to extract a stress-strain curve from load-displacement curve of a nanoindentation experiment using finite element method simulation. Target parameters were four mechanical property parameters of Ludwik's equation and the performance of model has been improved through strain distribution and load-displacement curve analysis. The performance of the artificial neural network model was verified with nanoindentation experiments on 304L stainless steel.
Proceedings Inclusion? Planned:
Keywords Computational Materials Science & Engineering, Machine Learning, Mechanical Properties

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