Study of passive plume mixing due to two line source emission in isotropic turbulence
Bibliographic record
Abstract
Direct numerical simulations are performed to investigate the mixing and dispersion of passive plumes emitted from two parallel line sources into a homogeneous isotropic turbulent flow. The focus of this study is on the turbulent convective regime of plume mixing, where the bulk meandering of the instantaneous plumes makes the primary contribution to the plume dispersion and concentration fluctuations. The quality of mixing and the interference between the two plumes have been studied in both physical and spectral spaces. It is found that the exceedance probability of high concentrations for the total plume released from dual sources is much smaller than that released from a single line source. The reduction in the exceedance probability across high concentration levels for the total plume is quantified using a reduction factor, whose value approaches unity as the cross correlation coefficient between the two concentration fields becomes increasingly positive. It is observed that the scatterplots of the normalized third- and fourth-order concentration moments against the normalized second-order concentration moment collapse onto a single curve, indicating that higher order concentration moments of the total plume can be determined effectively from the information on lower order concentration moments. Furthermore, it is demonstrated that the concentration probability density function for the total plume can be properly evaluated using a clipped-gamma model. In the spectral analysis, the results of the pre-multiplied co-spectra and coherency spectra reveal that the mixing process is the strongest and fastest at large scales for the turbulent convective regime of plume mixing.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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 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".