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Record W2005933970 · doi:10.1139/t09-125

Analytical solution for heat and moisture diffusion in layered materials

2010· article· en· W2005933970 on OpenAlexvenueno aff
Jeongwoo Lee, Ji-Tae Kim, Il-Moon Chung, Nam Won Kim

Bibliographic record

VenueCanadian Geotechnical Journal · 2010
Typearticle
Languageen
FieldEngineering
TopicSoil and Unsaturated Flow
Canadian institutionsnot available
Fundersnot available
KeywordsMoisturePorous mediumDiffusionMechanicsPorosityMaterials scienceGeotechnical engineeringThermodynamicsGeologyPhysicsComposite material

Abstract

fetched live from OpenAlex

The study of heat and moisture flows in multiple layers of different materials that make up the unsaturated zone is of great importance when characterizing the behaviour of these materials. In the present paper, analytical solutions of the one-dimensional heat and moisture coupled diffusion problem for layered materials under two different sets of boundary conditions are proposed. The coupled flow of heat and moisture are assumed to follow the theory of Philip and De Vries, and the solutions are derived analytically using integral transform methods. A comparison between the analytical and numerical solutions for one example problem shows satisfactory results. Furthermore, a procedure is presented for estimating heat and moisture distribution profiles in any layered materials using the derived analytical solutions. It is expected that the proposed analytical solutions will be used effectively for preliminary analyses of coupled heat and moisture movements in unsaturated porous media.

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)0.002
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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.008
GPT teacher head0.208
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 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
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
Published2010
Admission routes1
Has abstractyes

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