Propulsion tests on ultra-high-temperature ceramic matrix composites for reusable rocket nozzles
Bibliographic record
Abstract
Ultra-high temperature ceramic matrix composites based on a ZrB2/SiC matrix have been investigated for the fabrication of reusable nozzles for propulsion. Three De Laval nozzle prototypes, obtained by sintering with either hot pressing or spark plasma sintering, were tested 2-3 times in a hybrid rocket motor for proving reusability. Sections were extracted after oxidation tests to study the microstructural changes and oxidative and thermomechanical stresses induced by the repeated tests. Compared to a reference graphite nozzle, no measurable erosion was observed for the UHTCMC-based nozzles. The oxidation mechanism consisted in the formation of a ZrO2 intermediate layer, with a liquid SiO2 layer on the surface that was displaced by the action of the gas flux towards the divergent part of the nozzle, protecting it from further oxidation. Both specimens obtained by HP and SPS displayed similar performance, with very slight differences which were attributed to small changes in porosity. These tests demonstrated the capability of complex-shaped prototypes made of the developed UHTCMC to survive repeated exposure to environments representative of a realistic space propulsion application, for an overall operating time up to 30 s, without any failure nor measurable erosion, making a promising step towards the development of reusable rocket components.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| 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 | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), 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".