Machine learning-based prediction of directed energy deposition process with small-size experimental data
The inconstancy in material properties and complex geometry make directed energy deposition (DED) a difficult process to control and optimize. Understanding the process-structure-property relationship and modeling geometry from track, to layer and multi-layer are keys to advancing DED. Experimentati...
Saved in:
Main Author: | |
---|---|
Other Authors: | |
Format: | Thesis-Doctor of Philosophy |
Language: | English |
Published: |
Nanyang Technological University
2024
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/173602 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Language: | English |