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Record W2062654813 · doi:10.1121/1.4784836

Computation of the dynamic thermal properties of a three-dimensional unit cell of porous media by Brownian motion simulation

2004· article· en· W2062654813 on OpenAlexaff
Camille Perrot, Xavier Olny, Raymond Panneton, Richard R. Bouchard

Bibliographic record

VenueThe Journal of the Acoustical Society of America · 2004
Typearticle
Languageen
FieldEngineering
TopicHeat and Mass Transfer in Porous Media
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsPoromechanicsPorous mediumAnisotropyMechanicsMaterials scienceMicrostructureBrownian motionComputationThermalTortuosityPorosityDissipationPermeability (electromagnetism)PhysicsComposite materialThermodynamicsMathematicsOptics

Abstract

fetched live from OpenAlex

Acoustic dissipation in porous media is mainly due to viscous and thermal mechanisms that occur in the pores of the microstructure. The purpose of this study is the determination of the macroscopic dynamic acoustic bulk modulus and thermal permeability of real foams from a local scale approach. To achieve this goal, two distinct steps are followed. First, the local geometry of a real foam is obtained using computed microtomography (μCT), then a periodic and regularly paving space tetrakaidecahedron cell is identified from the microstructure. Second, the heat equation is solved for the geometrical model. The paper provides a three-dimensional application of the efficient simulation technique of Brownian motion proposed by Torquato et al. for steady state diffusion-controlled problems [Appl. Phys. Lett. 55, 1847–1849 (1989)] and adapted by Lafarge [Poromechanics II, 708 (2002)] in a bi-dimensional case. The influence of the model’s microstructural details (anisotropy, and struts junction and cross-section) on the macroscopic properties are studied. The predictions of the macroscopic properties using this local scale approach are then compared to experimental measurements.

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 score0.201
Threshold uncertainty score0.238

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 studies0.0000.001
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 head0.012
GPT teacher head0.212
Teacher spread0.200 · 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

Citations1
Published2004
Admission routes1
Has abstractyes

Explore more

Same venueThe Journal of the Acoustical Society of AmericaSame topicHeat and Mass Transfer in Porous MediaFrench-language works237,207