Laser-Induced Keyhole Defect Dynamics during Metal Additive Manufacturing

被引:63
|
作者
Kiss, Andrew M. [1 ]
Fong, Anthony Y. [1 ]
Calta, Nicholas P. [2 ]
Thampy, Vivek [1 ]
Martin, Aiden A. [2 ]
Depond, Philip J. [2 ]
Wang, Jenny [2 ]
Matthews, Manyalibo J. [2 ]
Ott, Ryan T. [3 ]
Tassone, Christopher J. [1 ]
Stone, Kevin H. [1 ]
Kramer, Matthew J. [3 ]
van Buuren, Anthony [2 ]
Toney, Michael F. [1 ]
Weker, Johanna Nelson [1 ]
机构
[1] SLAC Natl Accelerator Lab, Stanford Synchrotron Radiat Lightsource, 2575 Sand Hill Rd, Menlo Pk, CA 94025 USA
[2] Lawrence Livermore Natl Lab, Phys & Life Sci Directorate, Livermore, CA 94550 USA
[3] Iowa State Univ, Ames Lab, Div Mat Sci & Engn, Ames, IA 50011 USA
关键词
additive manufacturing; laser powder bed fusion; titanium; X-ray imaging; BED FUSION PROCESS; MECHANICAL-PROPERTIES; POROSITY FORMATION; MELT FLOW; POWDER; MICROSTRUCTURE; TEMPERATURE; DENUDATION; TI-6AL-4V; QUALITY;
D O I
10.1002/adem.201900455
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Laser powder bed fusion (LPBF) metal additive manufacturing provides distinct advantages for aerospace and biomedical applications. However, widespread industrial adoption is limited by a lack of confidence in part properties driven by an incomplete understanding of how unique process parameters relate to defect formation and ultimately mechanical properties. To address that gap, high-speed X-ray imaging is used to probe subsurface melt pool dynamics and void-formation mechanisms inaccessible to other monitoring approaches. This technique directly observes the depth and dynamic behavior of the vapor depression, also known as the keyhole depression, which is formed by recoil pressure from laser-driven metal vaporization. Also, vapor bubble formation and motion due to melt pool currents is observed, including instances of bubbles splitting before solidification into clusters of smaller voids while the material rapidly cools. Other phenomena include bubbles being formed from and then recaptured by the vapor depression, leaving no voids in the final part. Such events complicate attempts to identify defect formation using surface-sensitive process-monitoring tools. Finally, once the void defects form, they cannot be repaired by simple laser scans, without introducing new defects, thus emphasizing the importance of understanding processing parameters to develop robust defect-mitigation strategies based on experimentally validated models.
引用
收藏
页数:7
相关论文
共 50 条
  • [41] Machine learning algorithms for defect detection in metal laser-based additive manufacturing: A review
    Fu, Yanzhou
    Downey, Austin R. J.
    Yuan, Lang
    Zhang, Tianyu
    Pratt, Avery
    Balogun, Yunusa
    JOURNAL OF MANUFACTURING PROCESSES, 2022, 75 : 693 - 710
  • [42] In-Situ Morphology and Temperature Monitoring of Laser Based Metal Additive Manufacturing for Defect Detection
    Nestor, Stephen G. L.
    Kanko, Jordan A.
    Sibley, Allison P.
    Fraser, James M.
    2017 CONFERENCE ON LASERS AND ELECTRO-OPTICS EUROPE & EUROPEAN QUANTUM ELECTRONICS CONFERENCE (CLEO/EUROPE-EQEC), 2017,
  • [43] Laser scan strategy descriptor for defect prognosis in metal additive manufacturing using neural networks
    Demir, Kahraman
    Zhang, Zhizhou
    Ben-Artzy, Adi
    Hosemann, Peter
    Gu, Grace X.
    JOURNAL OF MANUFACTURING PROCESSES, 2021, 67 : 628 - 634
  • [44] Recent trend on laser metal additive manufacturing
    Kyogoku H.
    Seimitsu Kogaku Kaishi/Journal of the Japan Society for Precision Engineering, 2016, 82 (07): : 619 - 623
  • [45] Dynamics of pore formation during laser powder bed fusion additive manufacturing
    Martin, Aiden A.
    Calta, Nicholas P.
    Khairallah, Saad A.
    Wang, Jenny
    Depond, Phillip J.
    Fong, Anthony Y.
    Thampy, Vivek
    Guss, Gabe M.
    Kiss, Andrew M.
    Stone, Kevin H.
    Tassone, Christopher J.
    Weker, Johanna Nelson
    Toney, Michael F.
    van Buuren, Tony
    Matthews, Manyalibo J.
    NATURE COMMUNICATIONS, 2019, 10 (1)
  • [46] Dynamics of pore formation during laser powder bed fusion additive manufacturing
    Aiden A. Martin
    Nicholas P. Calta
    Saad A. Khairallah
    Jenny Wang
    Phillip J. Depond
    Anthony Y. Fong
    Vivek Thampy
    Gabe M. Guss
    Andrew M. Kiss
    Kevin H. Stone
    Christopher J. Tassone
    Johanna Nelson Weker
    Michael F. Toney
    Tony van Buuren
    Manyalibo J. Matthews
    Nature Communications, 10
  • [47] Microstructure Characteristics and Their Influence Factors During Laser Additive Manufacturing of Metal Materials
    Li Shichun
    Mo Bin
    Xiao Gang
    Sun Fujian
    LASER & OPTOELECTRONICS PROGRESS, 2021, 58 (01)
  • [48] Laser-induced magnetization dynamics
    Koopmans, B
    SPIN DYNAMICS IN CONFINED MAGNETIC STRUCTURES II, 2003, 87 : 253 - 316
  • [49] Microcavity dynamics during laser-induced spallation of liquids and gels
    Paltauf, G
    SchmidtKloiber, H
    APPLIED PHYSICS A-MATERIALS SCIENCE & PROCESSING, 1996, 62 (04): : 303 - 311
  • [50] Localized dynamics during laser-induced damage in optical materials
    Carr, CW
    Radousky, HB
    Rubenchik, AM
    Feit, MD
    Demos, SG
    PHYSICAL REVIEW LETTERS, 2004, 92 (08)