Bibliographic record
Abstract
"There is growing international interest in space exploration. Going back to the moon where we will build a sustainable long-term human presence with new spacecraft, robotics and life-sustaining technologies, will prepare humans for future exploration of other planets in our solar system and asteroids and for space mining" [1]. The moon will serve as a base to develop and test new technologies, experience living on an extraterrestrial surface and will provide clues about the origin of the universe. Returning to the moon however, is not easy. The harsh lunar environment, solar radiation, the large amplitude of the temperature fluctuation and the negligible atmosphere and therefore low atmospheric pressure will challenge future manned and unmanned missions. One of the most pervasive limits to lunar surface exploration is the presence of lunar dust, which is electrostatically charged and adheres to everything with which it comes into contact. Lunar dust is very fine and also highly abrasive [2]. In this work, two abrasive wear test devices were designed and manufactured to study the volume wear rate of different materials when subjected to lunar dust simulant of different size ranges. There were three additional objectives to this research. First, the potential of using electrostatic and dielectrophoretic forces to remove and transport small particles away from surfaces was investigated by manufacturing several devices comprising series of parallel electrodes connected to single or multiple AC power source(s). The traveling electric field created then served as an invisible brush to clean surfaces and prevent dust from entering joints in space applications (e.g. bearing, solar panels, camera, etc.). Second, discrete element models were created and calibrated based on the experimental results to study the capacity of this technique to clean dust from surfaces in the lunar environment. Third, evaluated the idea of sorting and transporting regolith (i.e., the loose, heterogeneous material covering solid rock) into the journal bearing (i.e., a plain bearing designed to reduce friction by supporting radial loads) and employing it as a solid lubricant. Experimental outcomes demonstrate satisfactory performance of the electric curtain in terms of dust removal from surfaces, with low power consumption. They also indicate the need for standardization of wear and abrasion tests for space applications at low temperature and pressure. One recommendation resulting from this research is investment by the Canadian Space Agency on infrastructure and equipment such as "dirty chambers" to enable performance of similar experiments in dusty moon-like environments. This research was conducted with support from an NSERC Collaborative Research and Development Grant involving Neptec Design Group, the Canadian Space Agency, and McGill University.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".