Investigations on the Influence of Chemical Compounds on Fog Microphysical Parameters
Bibliographic record
Abstract
Lab experiments related to artificial fog studies are limited due to instrument sensitivity to small fog and aerosol particles; therefore, the goal of this work is to evaluate aerosol solute effects on fog physical properties in a lab environment. To reach the goal, an automated fog-generating system was designed and that includes controlled chemical compounds dissolved in pure water. In the analysis, the impact of changing the mass concentration of potassium dihydrogen phosphate—KH2PO4, urea-CO(NH2)2, and potassium hexacyanoferrate trihydrate-K3(Fe(CN)6) on fog droplet size spectra is studied, because visibility is directly related to fog droplet spectra and aerosol composition. In the experiment, various microphysical conditions, including fog droplet size and volume concentration, were analyzed as a function of changing aerosol composition/spectra and fixed thermodynamic conditions. The results showed that fog droplet size spectra vary with the addition of chemical impurities to the pure water volume. For example, increasing KH2PO4 concentration compared to distilled water volume resulted in a higher mean particle size, which led to faster droplet settlement, and that resulted in cleaning air more efficiently compared to pure water fog. Overall, both issues and challenges of the experimental fog generating system with respect to water and aerosol solutions resembling CRBN (chemical, radiological, biological, and nuclear agents) characteristics are provided and evaluated.
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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 | 0.000 | 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 | 0.001 |
| 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 | 0.001 |
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 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".