Reliable Measurements of UV Lamp Performance Using a Near-Field Technique
Bibliographic record
Abstract
Low pressure mercury arc lamps are an effective ultraviolet light source for disinfection of water. Critical lamp operating parameters such as the decrease in UV output with time, effect of water temperature on lamp output, and the effect of lamp dimming should be determined using a lamp in water. The reliable operation of a near-field test apparatus is described that is capable of measuring these quantities. The use of a radiometer with fiber optic light collection and standard reference lamp results in the reproducible measurement of these values using the near-field system. The stability of measurement is obtained using the reference lamp, which compensates for variations in the response of the fiber optic assembly. For sample lamps, a decrease of 11% output over 12,000 hours was observed. For the same lamp type, the relative calibrated output of the lamp increases between 5 and 50°C, with a ±10% change in lamp output relative to the reference temperature of 20°C. The apparatus samples the irradiance at a local point on the lamp, but the UV output of low pressure amalgam lamps as determined by the near-field technique is shown to be uniform over the entire lamp, except for within 1 cm of the lamp filament. This is shown for both new and 12,000 hour aged lamps, so that accurate lamp aging data can be determined. The change in UV output with water temperature change was demonstrated to be similar for both new and aged lamps in this study, except for the expected decrease in peak lamp UV output noted for the aged lamp.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".