Aerothermal and flight mechanic considerations by development of small launchers for low orbit payloads started from lorentz rail accelerator
Bibliographic record
Abstract
The injection of small payloads in Low Earth Orbit (LEO) by means of propelled launchers starting from a Lorentz Rail Accelerator (LRA) is a concept that may enable the access to space at extremely low cost. A propelled launcher is required since today a LRA is only able to launch a total mass of a few kilograms with a velocity up to 4.4 km/s but LEOpayloads require approximately 10 km/s at higher launch mass. Velocity difference must be assured with another propulsion system. Furthermore and independent of the type of selected propulsion, such solution has serious consequences on launcher design. Reasons are, e.g., the harsh mechanical loads like high acceleration on the LRA ramp, high deceleration due to pressure drag, unsteady phenomena during the transition from the LRA ramp into the free atmosphere and also due to extreme thermal loads in the first 30 s of flight. The study presents a conceptual design of a nominal payload of 3 kg, including dimensions, mass- and velocitybudget estimations. In the focus of the analysis are several concepts for the thermal protection of critical system like the nose cap, the front part of the fuselage which houses a hybrid kick-off engine, flares, and the attitude control engines. Additionally, the potential of plug nozzles in comparison to classical Laval nozzles as well as trajectory calculations are discussed. They underline that an elliptical orbit between 300 and 400 km is possible.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".