A physical model of an ejection suppressed CPS liquid lithium divertor target
Bibliographic record
Abstract
A physical model has been developed which includes high temperature liquid lithium evaporation, the expanding motion of the liquid lithium vapour cloud, the shielding effects of the vapour cloud on incident plasma particle bombardments, ejection suppressed analysis and a perpendicular field proposal, and photon radiation, heat flux and transport in the lithium vapour cloud plasma. The engineering outline design scheme and the relevant parameters for the liquid lithium surface divertor target plate configured by discrete tiny capillary arrays have been established. Splashing can be suppressed by utilizing discrete and electrical insulating capillary porous systems (CPSs), since the conductivity among the capillary cells has been cut off by adopting a special kind of ceramic composite material made of a non-conducting and unbreakable composite which is able to withstand high temperatures. The formula to describe the temperature-dependent evaporation power has been derived. The maximum temperature increases of the discrete plasma-facing liquid lithium surface divertor target plate have been compared under the high energy flux deposition of 10 MJ m −2 during a 1 ms time duration with or without evaporation power. The results show that a high surface heat load can be withstood by the designed discrete plasma-facing liquid lithium surface divertor target plate due to violent evaporation. The energy deposition of incident energetic particles and weakly relativistic electrons from the scrape-off layer have been calculated. A laboratory experimental facility to simulate liquid lithium surface interactions with plasma has been set up. Research on lithium evaporation, re-deposition and ejection suppressed experiments under high density linear plasma dumping is ongoing.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".