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Record W2804363535

Effects of Stellar Rotation in Parker's Hydrodynamic Stellar Wind Model.

2016· preprint· en· W2804363535 on OpenAlexaboutno aff
Bhimsen K. Shivamoggi

Bibliographic record

VenuearXiv (Cornell University) · 2016
Typepreprint
Languageen
FieldEarth and Planetary Sciences
TopicGeophysics and Gravity Measurements
Canadian institutionsnot available
Fundersnot available
KeywordsPhysicsStellar rotationRocket engine nozzleProtostarAstrophysicsRotation (mathematics)Stellar mass lossStellar massStellar collisionAngular momentumAstronomyStellar evolutionStar formationStarsNozzleClassical mechanics
DOInot available

Abstract

fetched live from OpenAlex

The effects of the stellar rotation and the consequent azimuthal stellar wind flow in Parker's [9] hydrodynamic stellar wind model are discussed. Of special interest is the emergence of a whole new hydrodynamic physics via a new critical point in the stellar wind flow, which supersedes the critical point in Parker's [9] hydrodynamic model. The effect of the stellar rotation is shown to cause the new critical point to occur lower in the corona, so the stellar wind experiences a stronger afterburner (as in an aircraft jet engine) action in the corona. For strong rotators, the new critical point is shown to occur at a fixed location for a given star, determined only by the basic stellar parameters like the mass M and the angular velocity, the variations in the stellar wind environment notwithstanding. The stellar rotation leads to stronger density fall-off and enhanced acceleration of the stellar wind at large distances from the star - this effect materializes even close to the star, for strong rotators. The stellar rotation causes the physical throat section of the effective de Laval nozzle associated with the stellar wind flow to become narrower, indicative of an enhanced flow acceleration. Thus, the stellar rotation leads to tenuous and faster stellar wind flows without change in the mass flux, and hence provides an efficient physical mechanism for protostars and strong rotators to lose their angular momentum quickly.

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 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 score0.075
Threshold uncertainty score0.990

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 head0.031
GPT teacher head0.160
Teacher spread0.129 · 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 teacher head, 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
Published2016
Admission routes1
Has abstractyes

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