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Skip to Search Results- 2Additive Manufacturing
- 1Al-alloys
- 1Convolutional Neural Network
- 1Corrosion
- 1Dissolvable Alloys
- 1Downhole Tools
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Automated semantic segmentation of NiCrBSi-WC optical microscopy images using convolutional neural networks
Download2022-01-01
Rose, D., Forth, J., Henein, H., Wolfe, T., Qureshi, A.
Convolutional neural networks (CNNs) were used for the semantic segmentation of angular monocrystalline WC from NiCrBSi-WC optical microscopy images. This deep learning approach was able to emulate the laborious task of manual segmentation effectively, with a mean intersection over union (IOU)...
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2021-01-01
Ahmed, E., Henein, H., Qureshi, A., Liu, J.
Downhole tools made of dissolvable alloys (DAs) are getting more attractive, especially with the difficulties that arise from drilling wellbores with longer lateral distances. To date, most of the DAs are based on Al alloys (AAs) or Mg alloys, which offer undesirable mechanical properties. This...
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Large-scale Metal Additive Manufacturing: A Holistic Review of the State of the Art and Challenges
Download2021-01-01
Lehmann, T., Rose, D., Ranjbar, E., Ghasri-Khouzani, M., Tavakoli, M., Henein, H., Wolfe, T., Qureshi, A.
Additive Manufacturing (AM) has the potential to completely reshape the manufacturing space by removing the geometrical constraints of commercial manufacturing and reducing component lead time, especially for large-scale parts. Coupling robotic systems with direct energy deposition (DED) additive...