An RLV-Based Plume Impingement Test Bed: Terrestrial Evaluation of Landing Pads Constructed of Granular Materials
Bibliographic record
Abstract
Uncertainty regarding the consequences of a rocket engine's plume interaction with a landing surface is a fundamental challenge posed by extraterrestrial vehicle landings. Prior research has established that a vehicle's landing thrusters can undermine the stability of the landing surface, putting the exploration vehicle at risk of an off-nominal landing or an altogether mission loss - this is known as "the plume problem." Analysis and experimentation have yielded several categories of design solutions to the plume problem through various treatments or configurations of the surface to create a landing pad using in situ materials. In support of research to enable missions to other celestial bodies, the authors have developed the Plume Impingement Test Bed (PITB) to provide a means of i) gathering data relating to plume effects upon prepared and unprepared soil media and ii) evaluating the effectiveness of design solutions to the plume problem. The PITB provides a terrestrial means of evaluating realistic plume effects by incorporating a flight-rated reusable launch vehicle (RLV), equipped with a liquid-propellant rocket engine. The PITB combines a Masten Space Systems, Inc. (Masten) vertical take-off and vertical landing (VTVL) RLV with a suite of instruments and a procedural framework to gather data and characterize the effects of a plume's interaction with a surface. The PITB is well-equipped to evaluate landing surfaces that have been prepared using robotic or other experimental methods to stabilize a surface for use as a landing pad. In operation, the instrumentation suite is deployed at a test site, calibrated and then the test surface is exposed to the VTVL RLV rocket plume. This paper will describe the design, operations and capabilities of the PITB.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".