C60-fullerene composite plasma jets formation and acceleration for application to disruption mitigation and magneto-inertial fusion
Bibliographic record
Abstract
Summary form only given. We present the progress on the development of a new idea of using high-Mach number high-density composite plasma jets from coaxial plasma guns for disruption mitigation in tokamak1 and magneto-inertial fusion2 (MIF). The key element of the idea is the solid state pulsed power source with TiH2 (or TiDT) grains and C6o micron size powder3. Very fast injection of the molecular gas mixture provided by hydrogen release and sublimation of Cgo into the plasma gun is achieved by a special filter grid with supersonic Laval nozzles. The estimations based on the physical models of TiH2 grains heating, C6o powder sublimation, molecular gas injection, mass separation, and plasma slug acceleration will be detailed. For disruption mitigation, our calculations show that the plasma gun is able to provide the required impurity mass1 (~l-2 g) and the ram pressure to penetrate the tokamak hot plasma and to overcome the confining magnetic field pressure. Core tokamak plasma penetration can be achieved and impurity mass delivered in less than 1 ms, as required by ITER tokamak. The magnetized target fusion (MTF) plasma for MIF is created by injecting two high-Mach number (M>5) high-density (>1017 cm"3) plasma jets composed of fuel (D-T) and "pusher" (C6o/C) along the axis of a pulsed magnetic (~l-2 T) mirror into a metallic cylindrical liner. The high-density (~1018 cm"3) cylindrical MTF created by head- on collision and stagnation in the magnetic field is compressed radially by the Z-pinch of the liner and prevented to expand axially by the incoming C6o/C end-plugs. We estimated that, due to the much longer MTF axial dimension (~30 cm) as compared to other inertial confinement fusion plasmas, the electron thermal conduction time to the Cgo/C end-plugs is longer than liner implosion time.
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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) | 0.000 | 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) | 0.002 | 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".