A New Ablative Material Offering SRM Nozzle Design Breakthroughs
Bibliographic record
Abstract
For many decades, Solid Rocket Motor (SRM) nozzle designs have used rayon-based, carbon-fabric-reinforced phenolic liners and insulators to protect the structural parts from the thermal aggression of the high temperature propellant gases, both for small tactical applications and very large military or space SRM applications. These 2D reinforced-plastic materials offer a unique combination of very interesting thermal insulative properties with predictable ablation and char properties together with good in-plane mechanical properties. However, ply-lift & pocketing resistance and orthogonal tensile strength are very sensitive to tape wrapping and autoclave cure manufacturing process parameters. If not mastered, these parameters may lead to nozzle failure. As a result, SRM nozzle design basics have not changed a lot for many years and advances in nozzle designs have only marginally been possible. In order to implement nozzle design simplifications needed to reduce nozzle costs, Snecma Propulsion Solide developed a new generation of carbon phenolic liners, made from a Naxeco ® 3D reinforcement, impregnated with phenolic resin using a Resin Transfer Molding (RTM) Process. The first operational application is the Vega launch vehicle first stage (P80) nozzle of which the development was funded by CNES. Not subjected to inside high pore pressure loads developed during the charring phase that make 2D reinforced-plastic carbon-phenolic materials delamination-sensitive, and with a third direction that increases the interlaminar shear strength, this new material family allows nozzle design simplifications of the exit cone and the flexseal cowl which are now self-standing parts, without requiring any metallic or composite structural shell.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".