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Dataset on Fatigue Results and Fatigue Fracture Initiation Site Characterization in Stress-Relieved PBF-LB/M Ti-6Al-4V Four-Point Bend and Axial Specimens: Part I (High Power, Variable Scan Velocities)

Author

Listed:
  • Brett E. Ley

    (Department of Materials Science and Engineering, Case Western Reserve University, Cleveland, OH 44106, USA)

  • Austin Q. Ngo

    (Department of Materials Science and Engineering, Case Western Reserve University, Cleveland, OH 44106, USA
    Naval Surface Warfare Center Carderock Division (NSWCCD), Bethesda, MD 20817, USA)

  • John J. Lewandowski

    (Department of Materials Science and Engineering, Case Western Reserve University, Cleveland, OH 44106, USA)

Abstract

As part of a NASA University Leadership Initiative (ULI) program, this work supports the continued development and evaluation of a fatigue-based process window for stress-relieved Ti-6Al-4V specimens produced via laser powder bed fusion (PBF-LB/M). Four-point bend and axial fatigue specimens were fabricated by NASA ULI collaborators across a range of scan velocities (800–2000 mm/s) at a constant power of 370 W using an EOS M290 system. All fatigue specimens were low-stress-ground by a commercial vendor and tested at Case Western Reserve University (CWRU) under load-controlled cyclic loading at a stress ratio of R = 0.1. This paper presents a curated dataset linking PBF-LB/M process parameters to fatigue outcomes across 175 specimens. Of these, 136 fractured and this study includes fatigue crack initiation site identification and defect morphology metrics derived from post mortem SEM analysis. Specimens that reached runout (10 7 cycles) and did not fracture under subsequent fatigue testing are retained in the dataset, with fractographic fields marked as ‘NA’ to indicate non-applicability. The dataset includes specimen metadata, processing parameters, fatigue life data, fatigue initiation site classification (e.g., keyhole, gas-entrapped pore (GeP), lack-of-fusion (LoF), contamination), defect size and shape descriptors, and spatial location relative to the free surface. These data are intended to support defect-based fatigue life prediction, probabilistic modeling, process–structure–property studies, and machine learning frameworks linking process parameters to fatigue performance in PBF-LB/M Ti-6Al-4V.

Suggested Citation

  • Brett E. Ley & Austin Q. Ngo & John J. Lewandowski, 2026. "Dataset on Fatigue Results and Fatigue Fracture Initiation Site Characterization in Stress-Relieved PBF-LB/M Ti-6Al-4V Four-Point Bend and Axial Specimens: Part I (High Power, Variable Scan Velocities)," Data, MDPI, vol. 11(4), pages 1-21, April.
  • Handle: RePEc:gam:jdataj:v:11:y:2026:i:4:p:81-:d:1916138
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