Conduits of steady-state autocatalytic plumes
Bibliographic record
Abstract
Plumes are typically formed when a continuous source of buoyancy is supplied at a localized source. We studied laminar plumes where buoyancy is supplied by an autocatalytic chemical reaction: The iodate-arsenous acid (IAA) reaction. The nonlinear kinetics of the IAA reaction produces a sharp propagating front at which buoyancy is produced by exothermicity and compositional change. When the reaction is initiated in an unconfined volume of reactant, a starting plume with a mushroom shaped head connected to the initiation point by a long conduit is formed. After the initial transient during the ascent of the head, we observed the emergence of a steady state in the conduit morphology and flow. Autocatalytic plumes were compared to nonreacting, compositionally buoyant plumes using the Gradient Echo Rapid Velocity and Acceleration Imaging Sequence (GERVAIS), an MRI velocimetric technique. Autocatalytic conduits had axisymmetric bimodal velocity profiles and cone-shaped morphologies, in contrast to the Gaussian profiles and cylindrical shapes of nonreacting conduits. The bimodal distribution for autocatalytic plumes is a consequence of the unique effect of entrainment in this system. Rather than the usual effect of entrainment in nonreacting plumes, where less buoyant fluid is incorporated into the plumes, entrainment in autocatalytic plumes provides a buoyancy flux along the entire conduit by means of chemical reaction, thereby delocalizing the buoyancy source.
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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 | 0.000 |
| 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) | 0.001 | 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".