Optimization of a Multiphase Mixed Flow Field in Backfill Slurry Preparation Based on Multiphase Flow Interaction
Bibliographic record
Abstract
The paper analyzes the dynamic behavior during the preparation of cemented backfill slurry by combining the structural performance analysis of the double-shaft mixer and the Euler multiphase flow field computational fluid dynamics model. Considering the interaction between phases and gas phase disturbances, the transient kinetic parameters and the interaction between gas and liquid phases were introduced. According to the modified lift model, the user-defined function of the net lateral lift coefficient and the turbulence energy equation was adjusted. Taking the parameters of flow field velocity, gas phase mixing, uniformity, and turbulent energy dissipation as the evaluation indexes of the mixing effect, the double-shaft mixer at a rotation velocity of 45 rpm and with a blade installation angle of 25° is the optimal design in this study. Experimental tests were carried out and confirmed that the refined two-fluid model of interphase interaction can provide a basis for the performance evaluation of material mixing equipment.
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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 | 0.000 | 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".