MétaCan
Menu
Back to cohort
Record W4289868673 · doi:10.1088/1674-1056/ac8731

Analytical model for Rayleigh-Taylor instability in conical target conduction region

2022· article· en· W4289868673 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueChinese Physics B · 2022
Typearticle
Languageen
FieldPhysics and Astronomy
TopicLaser-Plasma Interactions and Diagnostics
Canadian institutionsGeomechanica (Canada)
Fundersnot available
KeywordsConical surfaceRayleigh–Taylor instabilityThermal conductionInstabilityInertial confinement fusionPhysicsMechanicsWork (physics)Isobaric processPlasmaImplosionIgnition systemClassical mechanicsThermodynamicsNuclear physicsGeometryMathematics

Abstract

fetched live from OpenAlex

This work builds an isobaric steady-state fluid analytical-physical model of the plasma conduction region in a conical target. The hydrodynamic instability in the double-cone ignition scheme [21] for inertial confinement fusion (ICF) proposed by Zhang is studied with the built model. With this idealized model, the relevant parameters, such as density, temperature, and length of the plasma in the conduction region of the conical target under long-pulse conditions are given. The solution of the proposed analytical model dovetails with the trend of the numerical simulation. The model and results in this paper are beneficial for discussing how to attenuate Rayleigh–Taylor instability in ICF processes with conical and spherical targets.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.196
Threshold uncertainty score0.595

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.032
GPT teacher head0.299
Teacher spread0.267 · 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