Innovative Approach to Rapidly Qualify Ti-6Al-4V Metallic Aircraft Parts Manufactured by Additive Manufacturing (AM) Techniques
Navy SBIR FY2015.1


Sol No.: Navy SBIR FY2015.1
Topic No.: N151-012
Topic Title: Innovative Approach to Rapidly Qualify Ti-6Al-4V Metallic Aircraft Parts Manufactured by Additive Manufacturing (AM) Techniques
Proposal No.: N151-012-0296
Firm: 3DSIM LLC
1794 Olympic Parkway
Park City, Utah 84089
Contact: Deepankar Pal
Phone: (317) 421-7168
Web Site: www.3dsim.com
Abstract: Additive Manufacturing (AM) is of increasing interest for production of Naval aircraft components. The geometric complexity, mechanical properties, and cost competitiveness for small lot production make AM techniques particularly suited for Ti-6Al-4V aircraft applications. However, microstructural and material property variability issues inherent to AM make rapid qualification of metal AM parts difficult. 3DSIM has significant experience with thermal modeling of metal laser sintering of Ti64, including prediction of Ti64 phases and phase transitions. These models have been validated experimentally over several years of research at the University of Louisville. To fully predict microstructural evolution in Ti64, accurate prediction of the initial crystal microstructure and subsequent solid state phase transitions is required. However, accurate prediction of initial microstructure is difficult to validate using Ti64 due to solid state phase transformations. To address Phase I objectives, 3DSIM proposes to: develop algorithms which predict microstructural characteristics, including phase evolution, grain size and grain orientation, from metal AM thermal histories; conduct validation of the predicted microstructural characteristics by comparison with as-built microstructures for metal laser sintered CoCrMoC parts; and conduct validation of the predicted microstructural characteristics by comparison with as-built microstructures for LENS-deposited Ti64 parts.
Benefits: Development and demonstration of the feasibility of new algorithms which predict microstructural features directly from process thermal history information will provide a modeling framework supporting the rapid qualification of aircraft parts formed form Ti64.

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