Hybrid Rocket Engine Research In Support Of Prototype Development & Testing
Bibliographic record
Abstract
This thesis gives a detailed overview of the design of a small hybrid rocket engine (HRE) that is being built in support of propulsion research activities at Ryerson University, and examines the various research-related issues surrounding the operation and performance of an HRE. The engine design work is undertaken with gaseous oxygen (GOX) as the oxidizer and paraffin and polyethylene as the intended fuels, but the system is readily adaptable to other propellant combinations for future investigations. Particular emphasis was placed on the design and analysis of the GOX injector and the nozzle. The injector orifice design was supported by CFD analysis as well as cold-flow testing. The nozzle was initially designed and fabricated from graphite, but a water-cooled copper design is also considered for those occasions when a fully reusable, non-eroding nozzle is desirable for accurate engine performance measurements. The preliminary nozzle design is supported by a steady-state CFD analysis of the nozzle flows and associated heat fluxes. The overall engine design is further evaluated by examination of internal ballistic simulation results, with respect to such factors as expected performance (chamber pressure, thrust, specific and total impulse) for a given oxidizer mass flow rate and nozzle throat size. The requirements for expected future studies, such as for evaluating engine operation and performance below and above the stoichiometric length of the given engine, have been incorporated where possible into the present design.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".