The lodide/lodate Actinometer in UV Disinfection: Determination of the Fluence Rate Distribution in UV Reactors
Bibliographic record
Abstract
Thirty-seven Suprasil quartz spheres, each approximately 1 cm in diameter and containing an iodide-iodate actinometric solution, were attached to a metal rack and inserted into a bench-scale UV reactor filled with water. The spheres were located at various distances and heights around a 12.4 W low-pressure Hg lamp housed inside a 3.2 cm-radius quartz sleeve in the middle of an annular batch reactor. UV light exposure at 254 nm was performed with the percent transmittance of the water present in the reactor at either 73% or 100% defined over a 1 cm path length. The spheres were simultaneously exposed to the UV light for a given period of time, after which the solutions were removed from the spheres and the yield of triiodide determined from the increase in absorbance at 352 nm. The resulting fluence rate at each site was then calculated on basis of the yield of triiodide. These results were compared with the predictions of a mathematical model based on the multiple point source summation approximation, including reflection and refraction at the air-quartz-water interface. Initially, the agreement was not satisfactory, especially in regions at an oblique angle to the lamp. The model was modified from a multiple point source model to a multiple cylindrical segment model by incorporating a cosine factor. The agreement between the new model and the experimental data was excellent and these experiments provide a strong validation of the model, even under conditions in which the fluence rate varied by >1000-fold between extreme sites in the reactor.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 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".