Predicting stress–strain relationships of additively manufactured materials under compression and tension using transfer learning and Wasserstein distance-based dataset pruning
Additive manufacturing enables the design of materials and structures with tunable mechanical properties. However, predicting the stress–strain relationships of additively manufactured materials remains a challenge due to complex process-structure–property relationships in additive manufacturing. Wh...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-08-01
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| Series: | Materials & Design |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S026412752500629X |
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