Development and Testing of a Breadboard Compactor for Advanced Waste Management Designs
Bibliographic record
Abstract
<div class="htmlview paragraph">Waste management is a vital function of spacecraft life support systems as it is necessary to meet crew health and safety and quality of life requirements. Depending on the specific mission requirements, waste management operations can include waste collection, segregation, containment, processing, storage and disposal. For the Crew Exploration Vehicle (CEV), addressing volume and mass constraints is paramount. Reducing the volume of trash prior to storage is a viable means to recover habitable volume, and is therefore a particularly desirable waste management function to implement in the CEV, and potentially in other spacecraft as well.</div> <div class="htmlview paragraph">Research is currently being performed at NASA Ames Research Center to develop waste compaction systems that can provide both volume and mass savings for the CEV and other missions. To facilitate the design of these mechanical compaction technologies, a breadboard compactor was developed to conduct a broad range of experiments focused on obtaining data regarding multiple design parameters for advanced compaction systems. The breadboard system includes a cylindrical compaction chamber with a pneumatically driven, wall-sealed piston. A data acquisition system was developed to provide real-time data indicating the degree of waste volume reduction as a function of compaction force. Experimentation was conducted using various wastes to mimic the types of trash anticipated on the CEV. Overall, these data will facilitate the selection of the optimum compaction force, materials for hardware construction, and general overall design features for ongoing compactor development efforts. This paper presents the overall design and function of the breadboard compactor, as well as results of experiments that examine the quantitative and qualitative characteristics of various waste materials.</div>
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".