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Record W2321513364 · doi:10.1061/9780784412992.276

The Critical Frequency in Biphasic Media: Beyond Biots Approach

2013· article· en· W2321513364 on OpenAlexfundno aff
Patrick Kurzeja, Holger Steeb, Jörg Renner

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicSeismic Imaging and Inversion Techniques
Canadian institutionsnot available
FundersStudienstiftung des Deutschen VolkesYork University
KeywordsMicroscale chemistryBiot numberInertiaStatistical physicsCompressibilityMechanicsElasticity (physics)Porous mediumPhysicsClassical mechanicsMaterials scienceMathematicsGeologyPorosityThermodynamicsGeotechnical engineering

Abstract

fetched live from OpenAlex

Biot's theory for wave propagation in biphasic media is still of great influence on current research and its applications in engineering and geosciences. In particular, the characteristic frequency introduced by Biot is used to distinguish a viscosity-dominated low frequency range from an inertia-dominated high frequency range. An understanding of the transition between these ranges of contrasting dominance of mechanisms is of vital importance for the interpretation of experiments and the basis of new theories. Biot derived the characteristic frequency on the microscale and questions remain regarding its correct transformation to the macroscale. Specifically, three aspects are neglected due to simplifying assumptions on the microscale: inertia of the solid, elasticity of the solid, and a frequency-dependent momentum interaction. Corrections accounting for these aspects are particularly significant for systems with a weak solid skeleton and a rather incompressible fluid. Neglection of these corrections appears however often justified for typical systems of rocks or soils. Experiments were conducted in which waves propagate through elastic tubes of different materials (steel, silicone) filled with various fluids (air, water, Na-Polywolframat). These experiments are supposed to represent the micro-scale mechanisms in single pores. The mismatch between experimental records and theoretical predictions suggests that some of the assumptions made in current theoretical treatments of the problem require further consideration before a reliable upscaling can be undertaken.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0010.002
Scholarly communication0.0010.002
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.013
GPT teacher head0.215
Teacher spread0.203 · 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 designTheoretical or conceptual
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

Citations9
Published2013
Admission routes1
Has abstractyes

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Same topicSeismic Imaging and Inversion TechniquesFrench-language works237,207