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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: jlamb@ucsb.edu

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

Harrison, NJ et al. , Acta Materialia 94 (2015), p. 59-68. doi:10.1016/j.actamat.2015.04.035CrossRefGoogle Scholar
Zhang, B, Li, Y, and Bai, Q, Chinese Journal of Mechanical Engineering 30 (2017), p. 515–527.doi:10.1007/s10033-017-0121-5CrossRefGoogle Scholar
Bian, P, Shao, X, and Du, J, Applied Sciences 9 (2019), p. 2231. doi:10.3390/app9112231CrossRefGoogle Scholar
Qiu, C, Chen, H, Liu, Q, Yuea, S, Wang, H, Materials Characterization 148 (2019), p. 330-344. doi:10.1016/j.matchar.2018.12.032CrossRefGoogle Scholar
Echlin, MP et al. , Rev. of Sci. Instrum. 83 (2012), p. 023701, doi:10.1063/1.3680111CrossRefGoogle Scholar
Zhang, YB, Elbrønd, A, and Lin, FX, Materials Characterization 96 (2014), p. 158–165. doi:10.1016/j.matchar.2014.08.003CrossRefGoogle Scholar
Landi, A, Piaggi, P, Laurino, M, and Menicucci, D, Proc. 2010 10th Int. Conf. Intell. Syst. Des. Appl. Proceedings (2010), p.115–120. doi:10.1109/ISDA.2010.5687280.CrossRefGoogle Scholar