Correlating manufacturing strategies to material performance in Laser Powder Bed Fusion of Titanium 6Al 4V

Abstract

Additive manufacturing (AM) (also known as 3D printing) of aerospace alloys has enabled opportunities for gas turbine engine developers to increase the design space, and thus potential efficiency, of future systems. However, before AM components are put into service it is vital to be able to accurately predict how long they will last. The repeated loading and unloading of a component such as a turbine blade can cause cracks to develop and grow, and eventually the component to fail. Cracks in AM components are often found to start at small voids introduced during manufacture. Unfortunately, the limited data regarding the occurrence of these voids means their appearance in a component, and hence the life of that component, cannot be determined to the accuracy required to certify it for aerospace applications. This project aims to help better understand the material performance of titanium alloy Ti 6Al 4V manufactured using laser powder bed AM. To do this, X ray computed tomography will be used, which allows differences in X ray absorption to be determined in 3D, and enables statistically significant measurements of void sizes, morphologies and locations. Furthermore, the location can be used to infer the laser behavior at the moment the void was created. By building samples with a range of laser parameters, the aim is to minimize the occurrence of these voids. In addition, samples will be subjected to X ray imaging prior to mechanical testing to identify potential crack initiation locations. Such an approach will allow the characteristics of voids that are most dangerous, i.e. led to a fatal crack, to be identified. Combined with the knowledge about how process parameters alter the frequency of different void types, this will lay the basis for improving manufacturing strategies to maximize the materials mechanical properties.

Document Details

Document Type
DoD Grant Award
Publication Date
Jan 14, 2022
Source ID
FA95501927001

Entities

People

  • Samuel Tammas Williams

Organizations

  • Air Force Office of Scientific Research
  • Liverpool John Moores University
  • United States Air Force

Tags

Fields of Study

  • Engineering

Readers

  • Powder metallurgy of Titanium alloys.
  • Structural Health Monitoring of Composite Structures.
  • Systems Analysis and Design

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • Directed Energy
  • Space