5541 Fatigue Allowable Curves and Effects of Texture and Thickness (FACETT)

This graphic illustrates the technical approach and impact of the RTRC FACETT project.


Additive manufacturing (AM) machines and materials qualification are major barriers to broad AM adoption. Generating the requisite data and models requires substantial resources to produce statistically significant data. This qualification process requires generating test coupons under a controlled process and testing and analysis of the resulting data. These processes are then “frozen” with no changes to key process variables allowed. Standard-based guidance does not exist for requirements when a process change is needed. This greatly inhibits AM processes from responding to changes in the technology or supply base, allowing only one path to implement change to a qualified process – a total requalification, which may cost over $3M per machine/material combination and take several years.


The project aims to empirically derive and numerically predict high cycle fatigue design allowables for textured thick-and-thin-walled Ti-6Al-4V additively built material. Using these datasets, the goal is to validate the use of an integrated computational materials engineering (ICME) tool that will reduce the time required to generate fatigue allowables by 75%.

Technical Approach

RTX Technologies Research Center (RTRC) will develop a test plan for a set of up to 15-thick-and-15 thin-walled Ti-6Al-4V laser powder bed fusion (LPBF) fatigue specimens with as-printed surface texture built on a SLM 280. Based on the test plan, RTRC will perform the requisite high cycle fatigue testing on the specimens and curate the resulting data into the project’s Material Data System (MDS). Lastly, high cycle fatigue predictions will be generated for textured thick-and thin-walled material based on empirically characterized microstructure and surface profile.

Project Participants

Project Principal

Other Project Participants

  • Collins Aerospace Applied Research & Technology
  • Hexagon Manufacturing Intelligence
  • Sentient Science

Public Participants

  • U.S. Department of Defense

Project Summary

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