Spectral Stability of Plasma Flow in Magnetic Nozzle
Bibliographic record
Abstract
In this thesis, spectral stability of plasmas is understood as an eigenvalue problem of linearized plasma equations describing time dynamics near some equilibrium state. Presence of eigenvalues with positive imaginary part would indicate the instability when small fluctuations will grow (typically exponentially) in time. A particular focus is the stability of plasma with stationary flows, in particular, flows in the magnetic nozzle. Magnetic nozzle, or magnetic mirror configurations, with converging-diverging magnetic field are used to accelerate plasma in plasma propulsion systems (magnetic Laval nozzle) and in fusion devices aiming to confine plasma and reach controlled thermonuclear fusion. We consider the linear stability of plasma folws under different boundary conditions. The linearized plasma equations are discretized and spectral stability problem is reduced to a polynomial eigenvalue problem. We found that the subsonic and supersonic folws are stable for Dirichlet boundary conditions. The supersonic flow is unstable for the mixed (fixed-open) boundary conditions. The subsonic flow has conflicting modes; i.e., the ground mode is unstable while the rest are stable. We show that different spectral methods, spectral-collocation and spectral-Galerkin methods agree. Phenomena of spectral pollution resulting in spurious unstable modes is discussed. By studying the convergence of different modes, we successfully eliminated the spurious modes. The stability problem of the transonic velocity profile has an additional difcfiulty due to the singularity at the sonic point, the point when the folw velocity is equal to the local sound velocity. At this point, the coefficient in front of the highest derivative of the differential eigenvalue equation becomes zero. In this case, the direct application of the spectral methods is problematic. To solve this problem, we solve the equation near the singularity by the Frobenius method and then use the regular solution with the shooting method to find the eigenvalues. We find that the transonic accelerating velocity profile is stable.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".