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A continuum model of unstable infiltration in porous media endowed with an entropy function

2020· article· en· W3042125696 on OpenAlexfundno aff
Abdelaziz Beljadid, Luis Cueto‐Felgueroso, Rubén Juanes

Bibliographic record

VenueAdvances in Water Resources · 2020
Typearticle
Languageen
FieldEngineering
TopicSoil and Unsaturated Flow
Canadian institutionsnot available
FundersFonds de recherche du Québec – Nature et technologiesMinisterio de Economía y Competitividad
KeywordsPorous mediumInfiltration (HVAC)Capillary actionEntropy (arrow of time)Nonlinear systemMechanicsPorosityMathematicsStatistical physicsPhysicsThermodynamicsGeotechnical engineeringGeology

Abstract

fetched live from OpenAlex

We propose a thermodynamic approach to modeling unsaturated flow in porous media, where the liquid saturation is understood as the state variable. The free energy functional is designed as a symmetric expansion of the traditional capillary energy density in Richards equation , therefore removing ambiguities on the interpretation of the higher-order term in the model equation. The proposed definition renders a formulation that leads naturally to an entropy function of the system, and we show that the model describes an entropy-increasing process for an isolated system. The new formulation reproduces gravity fingering during infiltration in soil. We show that the nonlinear and singular structure of the capillary pinning function in the fourth-order term plays a fundamental role in the behavior and stability of infiltration fronts, promoting front pinning and the persistence of fingered infiltration at relatively large flux ratios.

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)0.000
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
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.185
Teacher spread0.177 · 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

Citations45
Published2020
Admission routes1
Has abstractyes

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