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...
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| Format: | Thesis-Doctor of Philosophy |
| Language: | English |
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Nanyang Technological University
2024
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| Online Access: | https://hdl.handle.net/10356/173602 |
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| Institution: | Nanyang Technological University |
| Language: | English |