Comparison between SOLPS-4.3 and the Lengyel Model for ITER baseline neon-seeded plasmas
Bibliographic record
Abstract
Abstract If correct, the Lengyel model offers a simple and powerful tool to predict the conditions required for detachment onset in future fusion reactors. We assess its validity against a comprehensive SOLPS-4.3 simulation database of ITER baseline ( Q = 10) neon-seeded plasmas (Pacher et al 2015 J . Nucl . Mater . 463 591). In absolute terms, the Lengyel Model is found to significantly overpredict the simulated impurity concentration required in the ITER outer divertor for outer target ion flux rollover (by a factor ∼4.3 in this particular case). Importantly though, at detachment onset, and even beyond onset, the Lengyel model does give a remarkably accurate prediction of the scaling interdependencies between the electron density at the outer divertor entrance, the parallel energy flux density at the outer divertor entrance, and the impurity concentration in the outer divertor. However, the generalisation of these two key results to other machines, and in the presence of additional physics not included in these simulations, requires further studies. The analysis techniques described here provide a framework for such studies. Regarding the factor ∼4.3 overprediction of the simulated outer divertor impurity concentration, the main contributors to the disagreement are found to be other energy loss mechanisms besides impurity cooling (primarily neutral losses and radial transport) combined with convective energy fluxes near the target, as well as non-constant electron static pressure due to poloidally variable T i / T e . None of these are included in the Lengyel model. By themselves, these do not strongly influence the scaling interdependencies of the main Lengyel parameters over the explored parameter range. The impurity residence time τ is observed to increase with density, which tends to flatten out the impurity concentration scaling at low density, relative to the Lengyel model (which usually assumes constant τ ). In these simulations, however, this flattening out was cancelled by an accumulation of other effects, so that the scaling prediction of the Lengyel model was still well met. A simple physics model is derived for n e τ that matches the simulation data well. Neon is found to migrate from the inner divertor to the outer divertor with increased puffing, thereby increasing the outer divertor neon enrichment. At outer target ion flux rollover, though, the enrichment is approximately independent of the upstream concentration, so that the Lengyel model predicts well the scaling dependency between the upstream impurity concentration and the upstream electron density, both key quantities dictating the operational range of a tokamak.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".