Damage Assessment and Fracture Resistance of Functionally Graded Advanced Thermal Barrier Coating Systems: Experimental and Analytical Modeling Approach
Bibliographic record
Abstract
Enhancement of stability, durability, and performance of thermal barrier coating (TBC) systems providing thermal insulation to aero-propulsion hot-section components is a pressing industrial need. An experimental program was undertaken with thermally cycled eight wt.% yttria stabilized zirconia (YSZ) TBC to examine the progressive and sequential physical damage and coating failure. A linear relation for parameterized thermally grown oxide (TGO) growth rate and crack length was evident when plotted against parameterized thermal cycling up to 430 cycles. An exponential function thereafter with the thermal cycling observed irrespective of coating processing. A phenomenological model for the TBC delamination is proposed based on TGO initiation, growth, and profile changes. An isostrain-based simplistic fracture mechanical model is presented and simulations carried out for functionally graded (FG) TBC systems to analyze the cracking instability and fracture resistance. A few realistic FG TBCs architectures were considered, exploiting the compositional, dimensional, and other parameters for simulations using the model. Normalized stress intensity factor, K1/K0 as an effective design parameter in evaluating the fracture resistance of the interfaces is proposed. The elastic modulus difference between adjacent FG layers showed stronger influence on K1/K0 than the layer thickness. Two advanced and promising TBC materials were also taken into consideration, namely gadolinium zirconate and lanthanum zirconate. Fracture resistance of both double layer and trilayer hybrid architectures were also simulated and analyzed.
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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".