Waste Compaction Technology Development for Human Space Exploration Missions
Bibliographic record
Abstract
Waste management is a critical component of life support systems for manned space exploration. Human occupied spacecraft and extraterrestrial habitats must be able to effectively manage the waste generated throughout the entire mission duration. The requirements for waste systems may vary according to specific mission scenarios but all waste management operations must allow for the effective collection, containment, processing, and storage of unwanted materials. NASA's Crew Exploration Vehicle usually referred to as the CEV, will have limited volume for equipment and crew. Technologies that reduce waste storage volume free up valuable space for other equipment. Waste storage volume is a major driver for the Orion waste compactor design. Current efforts at NASA Ames Research Center involve the development of two different prototype compactors designed to minimize trash storage space. The design specifications of the compactors being developed at NASA Ames Research Center are based on NASA's initial 18-day lunar sortie missions using the Orion spacecraft as outlined in the new Space Exploration Initiative. This paper describes the compactor design methodology and concepts as well as a description of the current prototype hardware developed at NASA Ames for the Orion Crew Exploration Vehicle.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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".