Numerical Simulation of the Effects of the Helical Angle on the Decaying Swirl Flow of the Hole Cleaning Device
Bibliographic record
Abstract
The application of the hole cleaning device in downhole is a new technology that can improve the problem of cuttings accumulation in the annulus and improve the hole cleaning effect of the wellbore during drilling. In this paper, the Reynolds Averaged Navier–Stokes model, together with the Realizable k-ε turbulence model, are used to perform transient simulations. The effects of rotational speed, blade shape, and helical angle on the initial swirl intensity and its decay behavior along the flow direction are studied. The swirl number, the initial swirl intensity, the decay rate, the tangential velocity distribution, and the variation of pressure are analyzed. The results indicate that the swirl number of the swirl flow exponentially decays along the flow direction. The straight blade and V-shaped blade have different swirl flow induction mechanisms. Under specific drilling parameters, the critical helical angle is determined for both types of blades. When the selection of the helical angle is close to the critical value, the swirl flow will be close to the axial flow, which is of little help in hole cleaning. Moreover, the rotation direction of swirl flow will change when the helical angle exceeds the critical value.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".