Microwave Assisted Rock Breakage for Space Mining
Bibliographic record
Abstract
With the new advancements in space technology and also involvement of private sectors in space programs, space mining became an attractive subject either in In-Situ Recourse Utilization (ISRU) on the moon or mineral extraction from an asteroid. One can imagine that excavation and break-age technique that will be used will mainly be affected by the terrestrial methods which has been tested, tried and proved reliable. Drilling rocks is the first stage in order to extract the resources. It mainly relies on the mass of the drill and the reactive force that comes from the gravity. On the moon or an asteroid, where the gravitational force is one sixth or negligible, the drilling perfor-mance would not be equivalent to that on the earth. In this study, employment of microwave as a mean to reduce strength of the rocks before drilling is investigated. A magnetron can be installed on the drill and emit microwaves on the rock sur-face. Microwave penetrates into the rock and creates macro/micro fractures on the surface of the rocks due to thermal expansion ratio within grains, consequently easing the breakage process. Tests were performed on basalt, a common hard rock sample, when exposed to 3 kW electro-magnetic waves at 2.54 GHz in a 60×60×60 cm confined oven. Temperature was measured at different depth of the rock as its distance varied from the waveguide. Numerical modeling was also carried on to study the power dissipation inside the load and electric filed distribution inside the oven. Experimental experiences show, when exposed to microwaves, the micro-cracks density inside the rock increases which will result in less breakage energy requirement during drilling or crushing. Employing Microwave assisted drilling in space drilling or crushing applications may improve the drilling equipment performance; even though the gravitational forces are very low. Furthermore, microwave assisting drills will weight lighter compare to a conventional drilling rig. This reduces significantly the transportation costs the outer space.
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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 | 0.000 | 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) | 0.003 | 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".