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Experimental, computational, and machine learning methods for prediction of residual stresses in laser additive manufacturing: A critical review
In recent decades, laser additive manufacturing has seen rapid development and has been
applied to various fields, including the aerospace, automotive, and biomedical industries …
applied to various fields, including the aerospace, automotive, and biomedical industries …
[HTML][HTML] Weight Factor as a Parameter for Optimal Part Orientation in the L-PBF Printing Process Using Numerical Simulation
The L-PBF process belongs to the most modern methods of manufacturing complex-shaped
parts. It is used especially in the automotive, aviation industries, and in the consumer …
parts. It is used especially in the automotive, aviation industries, and in the consumer …
Thermal-Mechanical Physics Informed Deep Learning For Fast Prediction of Thermal Stress Evolution in Laser Metal Deposition
R Sharma, YB Guo - arxiv preprint arxiv:2412.18786, 2024 - arxiv.org
Understanding thermal stress evolution in metal additive manufacturing (AM) is crucial for
producing high-quality components. Recent advancements in machine learning (ML) have …
producing high-quality components. Recent advancements in machine learning (ML) have …