Numerical simulation on the larger concentration difference characteristics of dense granular jet in a coaxial gas stream
Bibliographic record
Abstract
Abstract This work is devoted to the numerical study of particle dispersion prediction of gas–solid coaxial jet with a larger concentration difference. In pulverized coal gasifier, the pulverized coal is very dense at the nozzle outlet, and its volume fraction can reach 0.3. Then, it is dispersed rapidly under the action of high‐speed annular gas, and the particle volume fraction in the space is less than 0.002. In order to better predict the motion characteristics of a gas–solid jet with a high concentration gradient, the applicability of the three models is compared. The results show that the dense discrete phase model (DDPM) and Eulerian two‐fluid model (TFM) models considering particles collision can accurately predict the dense jet flow at low annular gas velocity. The DDPM and discrete phase model (DPM) show a good simulation for the dispersion characteristics of particles at high annular velocities where the particles' collision could be ignored. Therefore, DDPM has better adaptability for coaxial jet with large concentration gradient. The DDPM was used to predict the particle velocity and concentration for different annular gas velocities and different particle mass loads. It is found that particle flow is contracted first and then dispersed gradually under the action of airflow. The particle dispersion range increases with the increase of solid loading rate, and the corresponding radial distribution of particle velocity is greater.
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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 | 0.001 |
| 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".