Multidimensional turbulence spectra – identifying properties of turbulent structures
Bibliographic record
Abstract
Development of models for several phenomena occurring in turbulent single and multiphase flows requires improved description and quantification of the turbulent structures. This is needed since often the phenomena are very fast or nonlinear. Previously the authors have presented experimental measurements that show that the breakup of bubbles and drops in turbulence is due to interaction with single turbulent vortices. Hence, it is not sufficient to use average turbulence properties when developing models for CFD simulation of engineering applications. In this paper the results from analysis of individual turbulent structures are presented. Results from analysis of the turbulent kinetic energy in turbulent structures, using Eulerian vortex identification methods, are presented. The amount of turbulent kinetic energy associated with a coherent vortex defined using different vortex identification methods is quantified. It is shown that the peak turbulent kinetic energy is located near the edge of the region identified as coherent, making the analysis challenging and development of models difficult. However, detailed analysis of a small number of coherent vortices from LES of turbulent pipe flow reveals new information about their life history. The growth (i.e. entrainment of the surrounding liquid), enstrophy, lifetime, and energy of a specific coherent vortex are tracked over time.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".