QUESTEK INNOVATIONS LLC — Department of Defense SBIR Phase I: N221-074

Description

Improved turbine engine performance could lead to a host of benefits for both military and commercial applications. More efficient turbine engines can enable cheaper, faster, and more sustainable operation Turbine engine performance is largely driven by two key factors; the maximum temperature at which the engine can operate, and the weight of the engine. Both aspects can be improved by creating new materials and improving design and manufacturing. This can be addressed with a combination of advanced materials development and mechanical designs. Specifically, the maximum temperature at which a turbine engine can operate can be increased by improving the heat removal from components in the hottest stage of the engine with internal cooling passageways and reduced wall thicknesses for Ni-based superalloy turbine blades and heat exchangers. The weight of a turbine engine can be decreased by reducing the material used in turbine engine components with lattice structuring. Additive manufacturing (AM) can produce details of complex shapes that cannot be produced by traditional methods. However, there is a lack of maturity in current AM modeling tools to reliably predict and control microstructure to enable tailored properties. Under this SBIR Program, QuesTek Innovations LLC will develop an Integrated Computational Materials Engineering (ICME) based process-structure-property fatigue modeling framework for additively manufactured Ni-based superalloys in turbine engine applications. QuesTek will partner with Pennsylvania State University’s Advanced Research Lab (PSU-ARL) to fabricate and characterize representative artifact components to validate the modeling framework. In the later phases of this SBIR Program this modeling framework will be integrated into QuesTek’s Integrated Design Engine (QT-IDE). QT-IDE will be offered as a commercial web-based software platform that can be hosted in the cloud or deployed on private servers to enable users to concurrently design and optimize turbine engine components and AM process parameters to achieve improved turbine engine efficiency.