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AFRL and Partner Researchers Use Data Science to Improve Aircraft Manufacturing Processes

2016 AFRL MW

The Air Force Research Laboratory (AFRL), along with data science startup Nutonian, Inc., have developed an advanced model that promises to improve the production and performance of metallic aircraft components.

Since metals make up nearly three-fourths of turbine engine components and two-thirds of a typical airframe's weight, their cost and performance have a significant effect on most defense systems. Recognizing the importance of reliable and affordable components, AFRL researcher Dr. Adam Pilchak and Nutonian data scientist Dr. Jay Schuren developed an analytical expression that improved upon existing models to more accurately predict how titanium alloys respond to various stresses at service-relevant conditions following the manufacturing process. Determining the mechanical properties of these materials can allow manufacturers to design and produce optimal engine components.

Drs. Pilchak's and Schuren's work built upon previous models developed by an industry team as part of the Advanced Titanium Alloy Microstructure and Mechanical Property Modeling program. The increased accuracy of their model can help aerospace manufacturers optimize the performance of titanium parts for air structures and high-performance turbine engines while reducing cost by decreasing materials-to-design-to-fly time.

With this breakthrough, companies can begin to produce new components for airframe and engine manufacturers. The model has been incorporated into Scientific Forming Technologies Corporation's DEFORM™ process simulation software and is now commercially available.

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