Estimation of Effects of Filtration and Ventilation on Worker Inhalation Dose from Aerosols Produced during Nuclear Decommissioning Processes
Bibliographic record
Abstract
ABSTRACT: During the decommissioning of nuclear power plants, radioactive contaminants may be released into the work environment in the form of aerosols, which can expose workers through inhalation, ingestion, and submersion pathways. During dismantlement work, aerosol concentrations may increase due to release from materials. Typical engineering controls to reduce concentrations include air exchange as well as air filtration, which captures aerosols at their source. This work presents a model of radioactive aerosol concentration to estimate the reduction of (a) effluent aerosol concentration into the environment and (b) worker committed effective dose. Controlling the aerosol concentration mitigates the dose that the workers receive. Given that there exists a variety of filtration methods of varying efficiencies and throughputs, a method of estimating dose reduction for a variety of work scenarios is desirable. This work models the time-evolution of radionuclide aerosol concentration as a function of dismantlement work parameters such as work time, aerosol source rate, air exchange, and air filtration. The committed effective dose to a worker as well as the environmental radionuclide aerosol emissions are estimated over a typical 10-h work shift.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 | 0.000 |
| 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".