Development of a Flow Controller for Long-Term Sampling of Gases and Vapors Using Evacuated Canisters
Bibliographic record
Abstract
Anthropogenic activities contribute to the release of a wide variety of volatile organic compounds (VOC) into microenvironments. Developing and implementing new air sampling technologies that allow for the characterization of exposures to VOC can be useful for evaluating environmental and health concerns arising from such occurrences. A novel air sampler based on the use of a capillary flow controller connected to evacuated canisters (300 mL, 1 and 6 L) was designed and tested. The capillary tube, used to control the flow of air, is a variation on a sharp-edge orifice flow controller. It essentially controls the velocity of the fluid (air) as a function of the properties of the fluid, tube diameter and length. A model to predict flow rate in this dynamic system was developed. The mathematical model presented here was developed using the Hagen-Poiseuille equation and the ideal gas law to predict flow into the canisters used to sample for long periods of time. The Hagen-Poiseuille equation shows the relationship between flow rate, pressure gradient, capillary resistance, fluid viscosity, capillary length and diameter. The flow rates evaluated were extremely low, ranging from 0.05 to 1 mL min(-1). The model was compared with experimental results and was shown to overestimate the flow rate. Empirical equations were developed to more accurately predict flow for the 300 mL, 1 and 6 L canisters used for sampling periods ranging from several hours to one month. The theoretical and observed flow rates for different capillary geometries were evaluated. Each capillary flow controller geometry that was tested was found to generate very reproducible results, RSD < 2%. Also, the empirical formulas developed to predict flow rate given a specified diameter and capillary length were found to predict flow rate within 6% of the experimental data. The samplers were exposed to a variety of airborne vapors that allowed for comparison of the effectiveness of capillary flow controllers to sorbent samplers and to an online gas chromatograph. The capillary flow controller was found to exceed the performance of the sorbent samplers in this comparison.
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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 | 0.000 |
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".