Study of Atmospheric Plasma-Based Mass Separation System for High-Level Radioactive Waste Treatment
Bibliographic record
Abstract
Solid spent nuclear fuel from nuclear power plants contains 3.4% fission products (80–160 amu), contributing to a radioactivity level of over 99.8%. On the other hand, liquid high-level radioactive waste (HLRW) from spent fuel reprocessing is composed of 98.9% bulk elements (0–60 amu) with 0.1% radioactivity. A separation mechanism for the mass categories into groups presents unique opportunities for managing HLRW in the long term with a considerable cost reduction. This paper proposes a thermal plasma-based separation system incorporating atmospheric-pressure plasma torches for HLRW mass separation into low-resolution mass groups. Several engineering issues must be addressed, such as waste preparation, waste injection into the plasma, and waste collecting after mass separation. Using the COMSOL Multiphysics simulation, the generic system can be studied using noble gas mass separation, and the mass filter capabilities can be further analyzed. This paper provides the history of plasma-based mass separation. The functional modelling of a thermal plasma mass separation system is proposed under atmospheric pressure. Finally, aspects of mass separation simulation using the noble gases argon and helium inside the plasma mass separation system are studied via COMSOL Multiphysics.
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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 | 0.000 |
| 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".