|SUBJECT:||M.S. Thesis Presentation|
|BY:||Alvaro Espejo Abela|
|TIME:||Tuesday, December 1, 2020, 10:00 a.m.|
|TITLE:||HIGH CYCLE FATIGUE OF ADDITIVELY MANUFACTURED INCONEL 625|
|COMMITTEE:||Dr. Richard W. Neu, Chair (ME)
Dr. Antonia Antoniou (ME)
Dr. Aaron Stebner (ME)
This research aims to investigate the influence of the microstructure, defect features, and surface roughness on the high cycle fatigue (HCF) strength of IN625 manufactured using Selective Laser Melting (SLM) additive manufacturing (AM) process. 11 AM builds each containing several fa-tigue test specimens with axis of specimen oriented in either the z-direction (build direction) or transverse direction were manufactured to explore the influence of variations in laser scan speed, hatch spacing, and SLM machine system. These processing conditions resulted in variations in microstructure, defect features, and surface roughness, all of which can influence fatigue strength. Specimens were tested in either as-is condition, with no further machin-ing or polishing, or in a polished condition to establish the role of surface roughness on fatigue strength. The fatigue strength of each specimen was determined using a step test method. To establish a reference stress-life curve and to validate the step test method, fatigue tests were also conducted on a cold-rolled IN625 sheet having similar strengths as the AM specimens. Stress-life curves that include the influence of microstructure are estimated using the fatigue strength data and the reference stress-life curve from the wrought IN625. The fatigue fracture surfaces were characterized with SEM microscopy to determine the microstructure feature associated with fa-tigue crack nucleation and understand the variability of the fatigue results. Average roughness for all builds was measured to find trends with the high cycle fatigue results. Tensile test results for various mechanical properties including Young Modulus, Yield Strength, Ultimate Tensile Strength and Strain to Failure vertical and horizontal specimens was plotted against fatigue strength to find trends. Fatigue strength was also evaluated against processing parameters to assess the dependence.