| About this Abstract |
| Meeting |
6th World Congress on Integrated Computational Materials Engineering (ICME 2022)
|
| Symposium
|
6th World Congress on Integrated Computational Materials Engineering (ICME 2022)
|
| Presentation Title |
Prediction of Corrosion Behaviour of Additively Manufactured Nickel Based Super Alloy Using Machine Learning |
| Author(s) |
Mythreyi Opadhrishta Venkataramana, Rohith Srinivaas M, R Jayaganthan |
| On-Site Speaker (Planned) |
Mythreyi Opadhrishta Venkataramana |
| Abstract Scope |
This research work focuses on machine learning assisted prediction of corrosion behavior of selective laser melted (SLM) and post processed INCONEL 718. Inconel 718, a nickel based super alloy, fabricated using SLM technique with optimized process parameters was subjected to post processing treatments such as heat treatment and shot peening. Corrosion testing was performed in these specimens in both as built and post processed conditions using electrochemical techniques. Potentiodynamic polarization and electrochemical impedance spectroscopy analysis were employed to test the corrosion behavior in a 3.5 wt% NaCl environment. Corrosion data from these experiments were fit into various machine learning algorithms and the prediction models were built. The prediction efficiency of the built models was assessed by comparing the experimental and predicted results.The models’ performance was evaluated by standard metrics. The feature importance analysis was executed in order to determine the post processing parameters that influenced the corrosion behavior the most. |
| Proceedings Inclusion? |
Definite: Other |