Skip to main content
eScholarship
Open Access Publications from the University of California

UC Santa Barbara

UC Santa Barbara Electronic Theses and Dissertations bannerUC Santa Barbara

Adaptive Photothermal Emission Analysis Techniques for Robust Thermal Property Measurements of Thermal Barrier Coatings

Abstract

The characterization of thermal barrier coating (TBC) systems is increasingly important because they enable gas turbine engines to operate at high temperatures and efficiency. Phase of photothermal emission analysis (PopTea) has been developed to analyze the thermal behavior of the ceramic top-coat of TBCs, as a nondestructive and noncontact method for measuring thermal diffusivity and thermal conductivity. Most TBC allocations are on actively-cooled high temperature turbine blades, which makes it difficult to precisely model heat transfer in the metallic subsystem. This reduces the ability of rote thermal modeling to reflect the actual physical conditions of the system and can lead to higher uncertainty in measured thermal properties. This dissertation investigates fundamental issues underpinning robust thermal property measurements that are adaptive to non-specific, complex, and evolving system characteristics using the PopTea method.

A generic and adaptive subsystem PopTea thermal model was developed to account for complex geometry beyond a well-defined coating and substrate system. Without a priori knowledge of the subsystem characteristics, two different measurement techniques were implemented using the subsystem model. In the first technique, the properties of the subsystem were resolved as part of the PopTea parameter estimation algorithm; and, the second technique independently resolved the subsystem properties using a differential “bare” subsystem. The confidence in thermal properties measured using the generic subsystem model is similar to that from a standard PopTea measurement on a “well-defined” TBC system.

Non-systematic bias-error on experimental observations in PopTea measurements due to generic thermal model discrepancies was also mitigated using a regression-based sensitivity analysis. The sensitivity analysis reported measurement uncertainty and was developed into a data reduction method to filter out these “erroneous” observations. It was found that the adverse impact of bias-error can be greatly reduced, leaving measurement observations with only random Gaussian noise in PopTea thermal property measurements.

Quantifying the influence of the coating-substrate interface in PopTea measurements is important to resolving the thermal conductivity of the coating. However, the reduced significance of this interface in thicker coating systems can give rise to large uncertainties in thermal conductivity measurements. A first step towards improving PopTea measurements for such circumstances has been taken by implementing absolute temperature measurements using harmonically-sustained two-color pyrometry. Although promising, even small uncertainties in thermal emission observations were found to lead to significant noise in temperature measurements. However, PopTea analysis on bulk graphite samples were able to resolve its thermal conductivity to the expected literature values.

Main Content
For improved accessibility of PDF content, download the file to your device.
Current View