Lunar Lander Configurations Incorporating Accessibility, Mobility, and Centaur Cryogenic Propulsion Experience
Bibliographic record
Abstract
As part of the Vision for Space Exploration, NASA plans to develop a human lunar lander, known as the Lunar Surface Access Module (LSAM). A practical lunar lander must transport astronauts to the Moon, then facilitate their activities on the lunar surface. Propulsion systems using LO2/LH2 propellants have several advantages, including high specific impulse main propulsion, the opportunity for synergistic application in fuel cells and life support, and compatibility with In Situ Resource Utilization (ISRU). However, due to their very low boiling points, it is difficult to design systems which retain LO2 and LH2 for long mission durations. This paper describes design principles based on development and operational experience with the Centaur upper stage which can be applied to build practical LO2/LH2 lunar landers. These include the use of a minimum number of large propellant tanks with common bulkheads and thin-wall structure. Consideration has been given to crew and cargo operations on the lunar surface, which drive needs for lander mobility and ease of transfer between the lander cabin or cargo mounts and the ground. The low density of LH2 means that LO2/LH2 landers will have large fuel tanks which can impede crew access to the lunar surface. Three innovative design concepts are presented which incorporate the suggested propulsion design principles and address mobility and access. Concept 1 is a two-stage Dual Thrust Axis lander, which uses an axial main engine for primary descent, then rotates to land with its long axis parallel to the ground. As a result, the crew
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".