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Record W2062289500 · doi:10.1029/2006jb004872

A new model of volatile bubble growth in a magmatic system: Isobaric case

2007· article· en· W2062289500 on OpenAlexaff
Ivan L’Heureux

Bibliographic record

VenueJournal of Geophysical Research Atmospheres · 2007
Typearticle
Languageen
FieldEngineering
TopicMetallurgical Processes and Thermodynamics
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsBubbleCoalescence (physics)AdvectionNucleationGrowth rateMechanicsMagma chamberRADIUSThermodynamicsGeologyMagmaPhysicsVolcanoGeochemistry

Abstract

fetched live from OpenAlex

The nucleation, growth, and, ultimately, coalescence of volatile bubbles in a silicate melt (magma chamber) play a crucial role in the processes leading to volcanic eruptions. A new diffusion‐limited nonlinear growth and nucleation model of volatile bubbles in such a system is proposed here. In contrast to previously existing models, the present one treats the competitive effects of the other randomly located bubbles on the growth dynamics in presence of a hydrodynamic coupling with the melt advection field through its viscous resistance. I consider here cases where the fluid pressure is kept constant. Numerical results pertaining to a basaltic and a rhyolitic melt suggest that for small volatile supersaturations and for small times, bubble growth occurs essentially as in the single‐bubble problem. However, for longer times, the influence of the other bubbles is important. I find that bubble growth rate decreases exponentially with time and propose an approximate expression for the decay rate. Finally, for larger volatile supersaturations, the bubble growth is subjected to transitions to and from an inflationary regime, whereby the bubble radius increases very rapidly during a small time interval.

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)0.001
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 score0.191
Threshold uncertainty score0.444

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.026
GPT teacher head0.291
Teacher spread0.265 · 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

Citations11
Published2007
Admission routes1
Has abstractyes

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