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Record W6980133882

Axial Evolution of a Sheared-Flow-Stabilized Z Pinch

2020· dissertation· en· W6980133882 on OpenAlexfundno aff

Bibliographic record

VenueResearchWorks at the University of Washington (University of Washington) · 2020
Typedissertation
Languageen
FieldEngineering
TopicFluid Dynamics and Thin Films
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsZ-pinchPinchWork (physics)Field (mathematics)Acceleration
DOInot available

Abstract

fetched live from OpenAlex

The Fusion Z-pinch Experiment (FuZE) is a sheared-flow-stabilized Z pinch based on the ZaP and ZaP-HD experiments. The FuZE device generates neutron-producing, 50-cm-long Z pinches formed from plasma accelerated through coaxial electrodes. The Z pinches are sustained between a nose cone at the tip of the plasma gun and an end wall at the end of the assembly region flux conserver. The end wall geometry is modified from a central hole to a spoked design and it is found that plasma exhaust is limited, but can be increased by increasing the ratio of ram and thermal pressures to the magnetic field pressure. The limited plasma exhaust results in a stagnation wave in the assembly region, increasing the plasma axial current and changing the shear flow profiles from a hollow to a peaked velocity distribution. The instantaneous neutron scaling with pinch current is investigated and it is found that the scaling corresponds to an adiabatic pinch where linear density increases with axial current. Lastly, the termination of plasma acceleration is found to be triggered by a blow-by instability starting at the insulator located at the breech end of the coaxial accelerator.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0090.001

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.

Opus teacher head0.009
GPT teacher head0.193
Teacher spread0.184 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2020
Admission routes1
Has abstractyes

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