Modeling of a new UV test cell for evaluation of lamp fluence rate effects in regard to water treatment, and comparison to collimated beam tests
Bibliographic record
Abstract
Collimated beam (CB) tests allow for consistent, easily calculated and reproducible measurements of UV fluence, and are widely used in UV treatment research and validation testing. However, because CB tests employ distance to provide collimation, the irradiance at the test sample is much lower than in UV treatment systems. A potential benefit of pulsed light may arise from the high fluence rate it produces. A new high-irradiance (HI) test cell approach and modeling technique are presented for use in evaluating these effects. The model is shown to correctly predict the fluence in the HI test cell by benchmarking it to CB measurements. This demonstrates that the HI cell is a useful tool in evaluating the effect of high fluence rate in UV treatment. This modeling technique also has application in reactor design.Key words: pulsed UV, collimated beam, modeling, disinfection, remediation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 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) | 0.000 | 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 teacher head, 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".