Experiments on Flow-Distributed Oscillations in the Belousov−Zhabotinsky Reaction
Bibliographic record
Abstract
This paper presents an overview of the waves and patterns that are formed when the oscillatory Belousov−Zhabotinsky medium flows through a packed bed reactor. At a sufficiently high flow velocity, this flow-distributed oscillation (FDO) gives rise to stationary waves with constant forcing at the inflow and to traveling waves with periodic forcing at the inflow. The wavelength of the stationary FDO wave is found to depend on flow velocity and on the effective diffusion coefficient (diameter of packing medium). We demonstrate the breakdown of stationary FDO waves at low flow velocity at which the space-periodic structure is replaced by irregular waves. At high flow velocity, periodic boundary forcing is found to give FDO waves that propagate either with a constant or with an oscillatory velocity. The wavelength and the velocity of the constant velocity upstream or downstream propagating waves are found to agree quantitatively with those predicted theoretically. Finally, we investigate the effect of a frequency gradient on FDO waves. When the oscillation period of the medium increases with the distance from the reactor inlet, it is observed that waves propagate downstream with a decreasing width and velocity. The behavior of both the waves propagating with an oscillatory velocity and those formed in the presence of a frequency gradient can also be understood in terms of phase dynamics.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".