Plasma flow and acceleration in the magnetic mirror and nozzle geometries
Bibliographic record
Abstract
This thesis investigates key physics governing transonic plasma flow within converging-diverging magnetic field (magnetic nozzle) configurations as used in fusion open mirror systems and plasma propulsion applications. In such configurations, plasma is accelerated from subsonic to supersonic velocities somewhat similar to the effects of the Laval nozzle. The Magnetohydrodynamic (MHD) fluid code {\it PLUTO} and the Particle-in-Cell (PIC) code {\it {\it VSim}} are employed to simulate plasma dynamics in both the nozzle and its expander region. The first part of the study utilizes the {\it PLUTO} MHD code to analyze the axial acceleration and density gradients characteristic of the magnetic nozzle. Not much work has been done on the analysis of the transonic acceleration in the magnetic nozzle using the MHD description. The observed acceleration profile demonstrates strong and remarkable agreement with a theoretical one-dimensional model, remaining valid for radii up to half the nozzle's injection width. To extend the analysis, an azimuthal velocity component was introduced in the injected plasma to simulate centrifugal confinement, a mechanism used in magnetic confinement devices to enhance confinement. Preliminary results indicate improved plasma confinement near the nozzle axis and increased axial acceleration along the centerline. The investigation continues with {\it {\it VSim}}, where a trapping condition for particles was derived, and the mirror effect was confirmed using test particles. Simulations of ion injection into the nozzle reveal transonic acceleration and density gradients across three energy injection scenarios. Notably, the acceleration profiles reached the sound speed at the nozzle throat, a phenomenon typically observed in fluid models but remarkable in the particle framework, where collisions and electromagnetic interactions are not explicitly included. In the final section, the dynamics of ions in the expander region are explored with {\it {\it VSim}}. An external electric field was introduced to account for the presence of electrons. Including electrons results in an enhanced azimuthal velocity due to the {$\mathbf{E \times B}$} drift. Theoretical calculations of the modified flux surface are validated by simulations, which further reveal increased ion confinement near the nozzle axis and detachment from magnetic field lines.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".