GE Aviation and Ohio State team up on LIFT titanium project

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The third technology project announced by LIFT (Lightweight Innovations for Tomorrow) will focus on titanium – a lightweight metal that has potential for more uses in aircraft engines and other aerospace designs if new technologies can reduce the cost of designing and testing new parts. Lead partners on the project, GE Aviation and The Ohio State University will focus first on advancing computer analytics to better understand and predict the performance of titanium alloys.

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“Titanium is expensive, and engineers have to ‘make and break’ a lot of test parts before they can be sure the design is right for a critical component of an airplane engine,” said Alan Taub, chief technology officer at LIFT. “If we can advance the abilities of our computer models to better predict how a particular design will perform, we can test less. That cuts material and testing costs and the lead time for developing new designs.”

Ohio Regents Eminent Scholar and Professor of Materials Science and Engineering Hamish Fraser heads up Ohio State’s involvement in the project.

“Professor Fraser brings deep experience in the physical metallurgy of Ti alloys, has unique facilities through CEMAS for the full 3-D characterization of microstructure, and is supported by new ICME modeling capabilities that can accurately predict solid state weld properties,” said LIFT Chief Innovation & Transition Officer Dennis Harwig.

According to GE Aviation Senior Staff Engineer Thomas F. Broderick, the company's interests emphasize development of computational means to predict fatigue and ballistic impact resistance within the highly transformed microstructures that are formed about the solid state weld interface.

Boeing and Scientific Forming Technologies Corporation are the other industry partners on the project. EWI, Purdue University, Southwest Research Institute, University of Michigan, and the University of North Texas will contribute to the project as research participants.

“This project aims to develop computer models that will reduce by 50% both the time and cost for materials development, component design, and manufacture,” said Taub. “In addition, the new computational tools will help us manufacture components that perform better."

Category: Research