Investigation of the working mechanism and unsteady effects inside a single-outlet vortex tube by implementing unsteady computational fluid dynamics and spectral proper orthogonal decomposition
Bibliographic record
Abstract
Although the working mechanisms of energy separation inside Ranque–Hilsch vortex tubes have been studied since the 1930s, a consensus on the topic has not been reached. The significance of unsteady flow effects has been shown in previous studies and attributed to various causes. In this research, the single-outlet vortex tube is modelled by applying both steady and unsteady Computational Fluid Dynamics (CFD). The unsteady CFD simulations are conducted with the Detached Eddy Simulation, and the steady simulations are performed with the Reynolds Stress Model. The energy separation performance of a vortex tube obtained in experiments reported in the literature, with and without damping the unsteady disturbances, is reproduced numerically. However, the results of tangential velocity profiles do not support the acoustic streaming theory. The unsteady effect is further studied by implementing Spectral Proper Orthogonal Decomposition (SPOD) on the CFD data. By analyzing the dominant SPOD modes, it is found that different unsteady mechanisms exist within the flow field, including the radial motion and dissipation of unsteady vortices and the rotation of semi “blades” of Rossby vortices. The combination of these unsteady mechanisms is responsible for the energy separation in a single-outlet vortex tube.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".