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Record W2105094167 · doi:10.1029/2009jb006375

A multiscale model of partial melts: 1. Effective equations

2010· article· en· W2105094167 on OpenAlexaff
Gideon Simpson, Marc Spiegelman, Michael I. Weinstein

Bibliographic record

VenueJournal of Geophysical Research Atmospheres · 2010
Typearticle
Languageen
FieldComputer Science
TopicAdvanced Mathematical Modeling in Engineering
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsHomogenization (climate)InterphaseMechanicsCompressibilityRelative permeabilityMaterials scienceMicrostructurePermeability (electromagnetism)Macroscopic scaleConstitutive equationMicroscopic scaleStatistical physicsThermodynamicsClassical mechanicsPhysicsFinite element methodChemistryComposite materialPorosity

Abstract

fetched live from OpenAlex

Developing accurate and tractable mathematical models for partially molten systems is critical for understanding the dynamics of magmatic plate boundaries as well as the geochemical evolution of the planet. Because these systems include interacting fluid and solid phases, developing such models can be challenging. The composite material of melt and solid may have emergent properties, such as permeability and compressibility that are absent in each phase alone. Previous work by several authors have used multiphase flow theory to derive macroscopic equations based on conservation principles and assumptions about interphase forces and interactions. Here we present a complementary approach using homogenization, a multiple scale theory. Our point of departure is a model of the microstructure, assumed to possess an arbitrary, but periodic, microscopic geometry of interpenetrating melt and matrix. At this scale, incompressible Stokes flow is assumed to govern both phases, with appropriate interface conditions. Homogenization systematically leads to macroscopic equations for the melt and matrix velocities, as well as the bulk parameters, permeability and bulk viscosity, without requiring ad hoc closures for interphase forces. We show that homogenization can lead to a range of macroscopic models depending on the relative contrast in melt and solid properties such as viscosity or velocity. In particular, we identify a regime that is in good agreement with previous formulations, without including their attendant assumptions. Thus, this work serves as independent verification of these models. In addition, homogenization provides a consistent machinery for computing consistent macroscopic constitutive relations such as permeability and bulk viscosity that are consistent with a given microstructure. These relations are explored numerically in the companion paper.

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: Methods · Consensus signal: Methods
Teacher disagreement score0.005
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.038
GPT teacher head0.349
Teacher spread0.311 · 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
GenreMethods

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

Citations74
Published2010
Admission routes1
Has abstractyes

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