Effect of Anisotropy on Particle Deposition in Impinging Jet Flow
Bibliographic record
Abstract
This study presents a numerical prediction of particle deposition on an impingement wall for nozzle-tosurface distance, L/D = 2. The continuous phase flow was solved using Reynolds-averaged Navier Stokes (RANS) along with Baseline Reynolds stress turbulence model (RSM-BSL). The particulate phase was simulated using a one-way coupling Lagrangian random-walk eddy-interaction model (EIM). The particle deposition density using turbulent tracking and mean flow tracking was predicted and the effect of the near-wall correction of the normal Reynolds stress component was evaluated. The effect of anisotropic flow using the minimum eddy lifetime is examined. To assess the accuracy of EIM in framework of RANS, large eddy simulation (LES) with Lagrangian particle tracking was used to predict the particle deposition in impinging jet flow. LES prediction was compared to RANS/EIM predictions and experimental data. Moreover, simulation findings demonstrate the superiority of LES compared to RANS/EIM in predicting the particle deposition. The results obtained using RANS/EIM showed that the deposition of the particles using the minimum eddy lifetime and near-wall correction yields close results to LES prediction and the experimental data. In addition, the deposition exhibits a ring-like pattern similar to experiments.
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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 | 0.001 | 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".