Developing solid-surface plasma facing components for pilot plants and reactors with replenishable wall claddings and continuous surface conditioning. Part B: required research in present tokamaks
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract The companion part A paper (Stangeby et al 2022) reports a number of independent estimates indicating that high-duty-cycle DT tokamaks starting with pilot plants will likely experience rates of net erosion and deposition of solid PFC, plasma facing component, material in the range of 10 3 to 10 4 kg yr −1 , regardless of the material used. The subsequent redeposition of such large quantities of material has the potential for major interference with tokamak operation. Similar levels and issues will be involved if ∼continuous low-Z powder dropping is used for surface conditioning of DT tokamaks, independent of the material used for the PFC armor. In Stangeby et al (2022) (part A) it is proposed that for high-duty-cycle DT tokamaks, non-metallic low-Z refractory materials such as ceramics (graphite, SiC, etc) used as in situ replenishable, relatively thin—of order mm—claddings on a substrate which is resistant to neutron damage could provide a potential solution for protecting the main walls, while reducing the risk of degrading the confined plasma. Assessment of whether such an approach is viable will require information, much of which is not available today. Section 6 of part A identifies a partial list of major physics questions that will need to be answered in order to make an informed assessment. This part B report describes R&D needed to be done in present tokamaks in order to answer many of these questions. Most of the required R&D is to establish better understanding of low-Z slag generation and to identify means to safely manage it. Powder droppers provide a unique opportunity to carry out controlled studies on the management of low-Z slag in current tokamaks, independent of whether their protection tiles use low-Z or high-Z material.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 it