Performance Trends For Aerospikes & Supersonic Nozzles With Center-Bodies
Bibliographic record
Abstract
The aim of this report is to examine performance trends for Aerospikes and Supersonic nozzles with center – bodies. The initial case that was tested is a convergent – divergent conical nozzle with a geometry and inlet flow conditions obtained from a NASA technical note. The technical note mentions that air was used as the working fluid for the nozzle. This case served as the base case for comparison with the performance of later nozzle designs. Nozzle flow for all the cases that were tested was simulated using ANSYS Fluent, for ambient conditions at 20km standard atmosphere. The convergent – divergent conical nozzle has the following calculated performance parameters using results from ANSYS Fluent: mass flow rate of 9.660 kg/s, axial Thrust of 10,583.5 N, and a specific impulse of 111.7s. All of the Supersonic nozzles with center – bodies have calculated specific impulse values lower than 111.7s by 0.4 – 1.6s, for approximately the same calculated mass flow rates as the base case. Adding a center – body to the original conical nozzle, was simply detrimental to performance. With regards to the Aerospike nozzles, 18 of them were tested. Aerospike 18 has the highest calculated specific impulse, at 115.3s for a calculated mass flow rate of 9.671kg/s. Aerospike 13 came in second at 114.6s, for a calculated mass flow rate of 9.676 kg/s. Several of the Aerospike designs did not out-perform the base case in terms of specific impulse. For those Aerospikes, the convergent – divergent section had a significantly lower thrust than the base case and the center – body was not able to over-compensate for the lower thrust. This report also looks at trends in thrust contribution by the convergent – divergent sections and center – bodies of Aerospikes at different nozzle geometries. The working fluid for all the cases tested in ANSYS Fluent including the base case, is air at a ratio of specific heats equal to 1.4.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".