The flow field characteristics and rock breaking ability of cone-straight abrasive jet, rotary abrasive jet, and straight-rotating mixed abrasive jet
Bibliographic record
Abstract
Radial jet drilling (RJD) technology is expected to be a technology for the efficient exploitation of geothermal resources. However, the low rock-breaking efficiency is the major obstacle hindering the development of RJD technology. The flow field characteristics and rock breaking ability of cone-straight abrasive jet, rotary abrasive jet, and straight-rotating mixed abrasive jet are analyzed by numerical simulations and experiments. Results show that the axial velocity of the cone-straight abrasive jet is high, the tangential velocity is basically zero, the radial velocity is also small, and the jet impact area is concentrated in the center. A deep hole with a diameter of only 25 mm is formed when the cone-straight abrasive jet breaks the granite. Due to the presence of the guiding impeller, the rotary abrasive jet basically has no axial velocity and has the highest tangential and radial velocity, so it can break the granite to form a hole with a diameter of about 55 mm and a central bulge. The straight-rotating mixed abrasive jet has a large axial/tangential/radial velocity at the same time, so it can break the granite to form a hole with a diameter of about 52 mm with a low bulge. The results show that the straight-rotating mixed abrasive jet combines the advantages of the cone-straight jet and the rotary jet, and is more suitable for the RJD technology. The research results can provide reference for the development of efficient rock-breaking and hole-forming technology, and promote the development of RJD technology in the field of geothermal development.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".