Investigation of turbulence characteristics in a gas cyclone by stereoscopic PIV
Bibliographic record
Abstract
Abstract Stereoscopic particle image velocimetry (Stereo‐PIV) was used as the tool to observe the turbulence characteristics in a gas cyclone. In the cylindrical and conical parts of the cyclone, intensive fluctuation occurs in the inner quasi‐forced vortex, especially in its core where the precessing vortex core dominates. In the dust hopper, strong turbulence is observed at the interface between the downward flow and the upward flow, as well as in the centerline of the cyclone. Turbulence intensity in the tangential, axial, and radial directions and the Reynolds stresses are seen to be anisotropic: this anisotropy provides the evidence of more appropriateness of the Reynolds stress model (RSM) than the standard k‐ε model, and the renormalization‐group k‐ε model for numerical simulations in gas cyclones. Due to flow instability and back‐mixing caused by the turbulence, separated particles could disperse into and be re‐entrained by the upward flow from the bin to degrade the separation efficiency of the cyclone. © 2006 American Institute of Chemical Engineers AIChE J, 2006
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 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 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".