Brett Ley

This study investigates elastic anisotropy in thick-walled 316LSi stainless steel deposits fabricated by Wire Arc Additive Manufacturing (WAAM). Four deposition conditions were evaluated by varying heat input (10 and 15 kJ/in.) and interpass temperature (121 and 399 °C), while maintaining a consistent alternating parallel toolpath strategy with 45% bead overlap. Optical metallography revealed that this tool path promoted cyclic partial remelting and produced a distinct periodic, wavy columnar grain morphology. Electron Backscatter Diffraction (EBSD) indicated corresponding crystallographic texture tendencies, with ⟨100⟩ alignment along the deposition direction (X-axis) and ⟨111⟩ alignment along the transverse direction (Y-axis). Since ⟨111⟩ is the stiffest and ⟨100⟩ is the most compliant crystallographic direction in FCC 316L/316LSi, these texture tendencies provide a mechanistic basis for the observed macroscopic elastic anisotropy. Room-temperature tensile testing and resonant frequency and damping analysis (RFDA) from 23 °C to 400 °C confirmed a consistent orientation-dependent modulus hierarchy of EY > EZ > EX. The lowest Young’s modulus values were consistently measured along the deposition direction (X-axis: 146 to 150 GPa), while the highest values were observed along the transverse direction (Y-axis: 187 to 197 GPa). Overall, elastic anisotropy was governed primarily by the toolpath-induced microstructure and crystallographic texture, rather than by variations in heat input or interpass temperature within the processing window studied. The modulus hierarchy also persisted up to 400 °C, indicating stable anisotropic elastic behavior under the tested thermal exposure conditions.

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 (10⁷ 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.