Search Results - "Beckett, Darren"

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  1. 1

    On the process of designing material qualification type specimens manufactured using laser powder bed fusion by Tekerek, Emine, Perumal, Vignesh, Jacquemetton, Lars, Beckett, Darren, Scott Halliday, H., Wisner, Brian, Kontsos, Antonios

    Published in Materials & design (01-05-2023)
    “…[Display omitted] •A methodology for designing specimen geometries for laser powder bed fusion to be used for material qualification investigations is…”
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    Journal Article
  2. 2

    In Situ, Parallel Monitoring of Relative Temperature, Material Emission, and Laser Reflection in Powder-Blown Directed Energy Deposition by Webster, Samantha, Jeong, Jihoon, Zha, Rujing, Liao, Shuheng, Castro, Alberto, Jacquemetton, Lars, Beckett, Darren, Ehmann, Kornel, Cao, Jian

    Published in JOM (1989) (01-11-2024)
    “…In situ monitoring is critical for developing new control methods, advanced materials and toolpath planning strategies in laser beam directed energy deposition…”
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    Journal Article
  3. 3

    A deep learning framework for layer-wise porosity prediction in metal powder bed fusion using thermal signatures by Mao, Yuwei, Lin, Hui, Yu, Christina Xuan, Frye, Roger, Beckett, Darren, Anderson, Kevin, Jacquemetton, Lars, Carter, Fred, Gao, Zhangyuan, Liao, Wei-keng, Choudhary, Alok N., Ehmann, Kornel, Agrawal, Ankit

    “…Part quality manufactured by the laser powder bed fusion process is significantly affected by porosity. Existing works of process–property relationships for…”
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    Journal Article
  4. 4

    A deep learning framework for layer-wise porosity prediction in metal powder bed fusion using thermal signatures by Mao, Yuwei, Lin, Hui, Yu, Christina Xuan, Frye, Roger, Beckett, Darren, Anderson, Kevin, Jacquemetton, Lars, Carter, Fred, Gao, Zhangyuan, Liao, Wei-keng, Choudhary, Alok N., Ehmann, Kornel, Agrawal, Ankit

    Published in Journal of intelligent manufacturing (14-10-2022)
    “…Part quality manufactured by the laser powder bed fusion process is significantly affected by porosity. Existing works of process–property relationships for…”
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    Journal Article
  5. 5

    A deep learning framework for layer-wise porosity prediction in metal powder bed fusion using thermal signatures by Mao, Yuwei, Lin, Hui, Yu, Christina Xuan, Frye, Roger, Beckett, Darren, Anderson, Kevin, Jacquemetton, Lars, Carter, Fred, Gao, Zhangyuan, Liao, Wei-keng, Choudhary, Alok N., Ehmann, Kornel, Agrawal, Ankit

    Published in Journal of intelligent manufacturing (14-10-2022)
    “…Abstract Part quality manufactured by the laser powder bed fusion process is significantly affected by porosity. Existing works of process–property…”
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    Journal Article