Extended-field electromagnetic model for inductively coupled plasma
Bibliographic record
Abstract
An extended-field (EF), two dimensional (2D) model formulation is proposed for inductively coupled plasma. By extending the calculating domain of the electromagnetic (EM) field outside of the plasma discharge region, the boundary conditions of vector potential used by the standard (ST) 2D model are replaced by simpler far field boundary conditions. The extended model converges faster than the standard formulation and gives rise to consistent solutions throughout the computational domain. Vector potential equations are solved with corresponding continuity, momentum, and energy transfer equations using the commercial code `FLUENT'. The computational domain for vector potential equations are extended well beyond the induction coil region, while for all the other equations, computations are limited to the discharge region inside the plasma confinement tube. The computational results are compared with those obtained using the ST 2D model. The difference between the results of the two models is noted mostly in the entrance regions of the flow, and close to the induction coil. To validate the EF model, a load with constant electric conductivity is placed centrally in the coil region and the calculated radial profile of the axial magnetic field is compared with existing analytical solutions. The results are in good agreement within an uncertainty of 1%.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".