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Record W2036082464 · doi:10.1121/1.4777201

Analytical solutions for characterizing tortuosity and characteristic lengths of porous materials using acoustical measurements: Indirect model

2001· article· en· W2036082464 on OpenAlexaff
Xavier Olny, Jerome Tran Van, Raymond Panneton

Bibliographic record

VenueThe Journal of the Acoustical Society of America · 2001
Typearticle
Languageen
FieldEngineering
TopicAcoustic Wave Phenomena Research
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsTortuosityPorosityCompressibilityPorous mediumMaterials scienceMechanicsHomogenization (climate)AirflowThermalMeasure (data warehouse)ThermodynamicsPhysicsComposite materialComputer science

Abstract

fetched live from OpenAlex

Under the homogenization hypothesis, wave propagation in porous materials can be described using, for example, macroscopic dynamic density and bulk modulus. These functions depend on statistical geometrical parameters. Classically, five parameters are used: porosity, static air flow resistance, tortuosity, and viscous and thermal characteristic lengths. The three last parameters are generally difficult to measure with existing direct methods, for a wide range of materials. The proposed method is based on the measurement of dynamic density and compressibility, in order to separate viscous and thermal effects. With prior knowledge of airflow resistance and porosity, it is then possible to find analytical solutions for the missing parameters, fitting Johnson–Allard–Champoux model. In the same way, we also tackle the problem of the determination of static ‘‘thermal permeability’’ introduced to improve the description of thermal dissipation effect. Experimental results, obtained with various materials, using a Kundt’s tube, are presented to show the efficiency, and relative simplicity of the method. Moreover, the relevance of using a three parameters model for describing the bulk modulus is discussed.

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)0.002
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.897
Threshold uncertainty score0.584

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.077
GPT teacher head0.295
Teacher spread0.218 · 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

Citations8
Published2001
Admission routes1
Has abstractyes

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Same venueThe Journal of the Acoustical Society of AmericaSame topicAcoustic Wave Phenomena ResearchFrench-language works237,207