SBIR-STTR Award

Thermal barrier coatings (TBCs) are widely being used in gas-turbine engines to thermally protect metal components such as turbine blades from hot combustion gases. One of the primary concerns of using TBC as a protective coating is its long term durability. Premature failure of TBCs during service can expose the bare metal to dangerously hot gases leading to material failure. Failure to remove critical aircraft turbine engine components prior to failure can lead to catastrophic failures and premature removal is costly in terms of lowered part utilization. Therefore, it is critical to develop analytical models that could predict the remaining durable life of TBC coatings thereby significantly improving the reliability and utilization of engine components. In the proposed research, Karta Technologies, Inc. (Karta) proposes to develop an analytical approach that takes into consideration multiple NDI parameters in determining remaining durable life of TBC engine components. The proposed research involves design and development of a PC-compatible user-friendly software for estimating the remaining durable life for TBC coated turbine engine components. Karta proposed to use neural network analysis for calculating the remaining life of coatings. Results from this research program will enhance the reliability, durability, and overall performance of TBC coatings

Durability of Thermal Barrier Coatings (TBCs) used in gas-turbine engines to thermally protect metal components such as turbine blades from hot combustion gases is a major concern to the aerospace industry and in particular the Air Force. The objective of this project is to develop an analytical approach to determining remaining durable life of thermal barrier coated engine components using Nondestructive Inspection data input. In Phase I, Karta identified oxidation of bond coat as a dominant factor leading to TBC failure. Determining the thickness of the thermally grown oxide (TGO) layer and measuring residual stresses in the TGO layer are critical to developing reliable remaining-life prediction models. Karta will measure the TGO thickness using Impedance Spectroscopy and measure the residual stresses using the Photo-Stimulated Luminescence Piezospectroscopy technique. Analytical models developed in Phase I will be validated by extensive laboratory testing. The proposed NDI techniques will be validated by laboratory tests. Remaining life models developed in Phase I will be validated by burner rig tests to simulate actual engine environments and by testing service run engine components, such as airfoils. The models will use neural network analysis for calculating the remaining life of coatings.

Keywords:
Thermal Barrier Coatings, Life-Prediction, Nondestructive Inspection, Cyclic Oxidation, Bond Coat, Impedance Spectroscopy, Photo-Stimulated Luminescen