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Merging Machine Learning and TriBeam Tomography for 3D Defect Detection in an AM CoNi-Based Superalloy

Published online by Cambridge University Press:  22 July 2022

James Lamb ,
McLean Echlin ,
Andrew Polonsky ,
Remco Geurts ,
Kira Pusch ,
Evan Raeker ,
Aurelien Botman ,
Chris Torbet  and
Tresa Pollock
James Lamb*
Affiliation:
University of California Santa Barbara, Materials Department, Santa Barbara, CA, United States
McLean Echlin
Affiliation:
University of California Santa Barbara, Materials Department, Santa Barbara, CA, United States
Andrew Polonsky
Affiliation:
Sandia National Laboratories, Materials Mechanics & Tribology, Albuquerque, NM, United States
Remco Geurts
Affiliation:
Thermo Fisher Scientific, Eindhoven, Netherlands
Kira Pusch
Affiliation:
University of California Santa Barbara, Materials Department, Santa Barbara, CA, United States
Evan Raeker
Affiliation:
University of California Santa Barbara, Materials Department, Santa Barbara, CA, United States
Aurelien Botman
Affiliation:
Thermo Fisher Scientific, Hillsboro, OR, United States
Chris Torbet
Affiliation:
University of California Santa Barbara, Materials Department, Santa Barbara, CA, United States
Tresa Pollock
Affiliation:
University of California Santa Barbara, Materials Department, Santa Barbara, CA, United States
*
*Corresponding author: [email protected]

Abstract

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Type
Ultrashort Pulse Lasers: Microscopy, Simulations, and Material Interactions
Information
Microscopy and Microanalysis , Volume 28 , Supplement S1 , August 2022 , pp. 862 - 863
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Copyright
Copyright © Microscopy Society of America 2022

References

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