High Temperature Radiation Heat Transfer Performance of Thermal Barrier Coatings With Multiple Layered Structures
Bibliographic record
Abstract
Meeting the demands for ever increasing operating temperatures in gas turbines requires concurrent development in cooling technologies, new generations of superalloys, and thermal barrier coatings (TBCs) with increased insulation capability. In the case of the latter, considerable research continues to focus on new coating material compositions, alloying/doping existing yttria stabilized zirconia ceramics, and the development of improved coating microstructures. The advent of the EB-PVD coating process has made it possible to consider the creation of multiple layered coating structures to meet specific performance requirements. In this paper, the advantages of layered structures are first reviewed in terms of their functions in impeding thermal conduction (via phonons) and thermal radiation (via photons). Subsequently, the design and performance of new multiple layered coating structures based on multiple layered stacks will be detailed. Designed with the primary objective to reduce thermal radiation transport through TBC systems, the multiple layered structures consist of several highly reflective multiple layered stacks, with each stack used to reflect a targeted radiation wavelength range. Two ceramic materials with alternating high and low refractive indices are used in the stacks to provide multiple-beam interference. A broadband reflection of the required wavelength range is obtained using a sufficient number of stacks. In order to achieve 80% reflectance to thermal radiation in the wavelength range of 0.3 ∼ 5.3 μm, 12 stacks, each containing 12 layers, are needed, resulting in a total thickness of 44.9 μm. Using a one dimensional heat transfer model, steady state heat transfer through the multiple layered TBC system is computed. Various coating configurations combining multiple layered stacks along with a single layer are evaluated in terms of the temperature profile in the TBC system. When compared to a baseline single layered coating structure of the same thickness, it is estimated that the temperature on the metal surface can be reduced by as much as 90°C due to the use of multiple layered coating configurations. This reduction in metal surface temperature, however, diminishes with increasing scattering coefficient of the coating and total coating thickness. It is also apparent that using a multiple layered structure throughout the coating thickness may not offer the best thermal insulation; rather, placing multiple layered stacks on top of a single layer can provide a more efficient approach to reduce the heat transport of the TBC system.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".