Phases Management for Advanced Life Support Processes
Bibliographic record
Abstract
<div class="htmlview paragraph">For a planetary base, a reliable life support system including food and water supply, gas generation and waste management is a condition <i>sine qua non</i>. While for a short-term period the life support system may be an open loop, i.e. water, gases and food provided from the Earth, for long-term missions the system has to become more and more regenerative. Advanced life support systems with biological regenerative processes have been studied for many years and the processes within the different compartments are rather complete and known to a certain extent. The knowledge of the associated interfaces, the management of the input and output phases: liquid, solid, gas, between compartments, has been limited. Nowadays, it is well accepted that the management of these phases induces generic problems like capture, separation, transfer, mixing, and buffering.</div> <div class="htmlview paragraph">A first ESA study on these subjects started mid 2003. This study, performed by Stork, TNO, Stirling and the University of Guelph, is limited to the main gas components, oxygen, water vapour and carbon dioxide. Ammonia was included as a contaminant component. The study has been started with the establishment of a simulation model (closed loop) to identify the critical items, which is followed by the selection of the gas capture and recovery technologies, the development of a breadboard model and is finished by a set of experiments.</div> <div class="htmlview paragraph">For the control of carbon dioxide (CO<sub>2</sub>), a dedicated activated carbon will be applied. This material, produced by Norit, is applied to control the CO<sub>2</sub> at fruit storage, and pressure swing adsorption is applied for regeneration. In the breadboard set-up, electrical swing adsorption will be applied. This rather new technique has been selected to enable the development of a compact system which can be operated within almost any range atmospheric pressure, resulting in a safe system having a low mass.</div> <div class="htmlview paragraph">This paper will report the status of these activities.</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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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 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".