Design and Development of Cost-Effective Equipment for Tribological Evaluation of Thermally Sprayed Abradable Coatings
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Thermally sprayed abradable coatings are essential for improving the performance of gas turbine engines. They act as a protective barrier between the stationary casing and rotating blades. Though a lot of research has been done on abradable coatings, little attention has been paid to comprehending wear mechanisms in the abradable-blade tip interaction. The goal of this project is to create a cost-effective test rig that can evaluate different thermally sprayed abradable coatings and understand how they interact with titanium blade tips under application-relevant conditions. Blade tip velocity, incursion rates, incursion depths, reaction forces, and interfacial temperatures are some of the inputs and outputs that the testing rig can provide. Aiming to validate the rig, this study examined the wear behavior of aluminum, thermally sprayed polyester, and AlSi-40Polyester abradable coating. The reaction forces for aluminum and polyester were overall higher when compared to AlSi-40Polyester. However, thermally sprayed polyester showed the highest interfacial temperatures of all materials tested. The difference in the reaction forces and interfacial temperature correlates well with the different wear mechanisms and thermal conductivities. Overall, the equipment showed to be a promising pre-screening methodology to evaluate and develop novel thermal spray abradable coatings.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 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) | 0.001 | 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 it