Physics-Based Data Augmentation Enables Accurate Machine Learning Prediction of Melt Pool Geometry

Physics-Based Data Augmentation Enables Accurate Machine Learning Prediction of Melt Pool Geometry

Accurate melt pool geometry prediction is essential for ensuring quality and reliability in Laser Powder Bed Fusion (L-PBF). However, small experimental datasets and limited physical interpretability often restrict the effectiveness of traditional machine learning (ML) models. This study proposes a...

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Bibliographic Details
Main Authors: Siqi Liu, Ruina Li, Jiayi Zhou, Chaoyuan Dai, Jingui Yu, Qiaoxin Zhang
Format: Article
Language:English
Published: MDPI AG 2025-08-01
Series:Applied Sciences
Subjects:
additive manufacturing
explicit model
machine learning
melt pool
Online Access:https://www.mdpi.com/2076-3417/15/15/8587
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