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Record W2033891199 · doi:10.2136/sssaj2005.0001

Modeling Aggregate Internal Pressure Evolution following Immersion to Quantify Mechanisms of Structural Stability

2005· article· en· W2033891199 on OpenAlexaff
Hafida Zaher, Jean‐François Caron, Bennaceur Ouaki

Bibliographic record

VenueSoil Science Society of America Journal · 2005
Typearticle
Languageen
FieldEngineering
TopicSoil and Unsaturated Flow
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsLoamHydraulic conductivityWettingSoil waterDistilled waterWater retentionInternal pressureAggregate (composite)Soil scienceMaterials scienceSoil structureEnvironmental scienceGeotechnical engineeringChemistryComposite materialGeologyChromatography

Abstract

fetched live from OpenAlex

Identification of the key components controlling aggregate stability is important in soil structure research. The deterioration of soil aggregates during rapid wetting has often been attributed to the swelling and internal pressure buildup resulting from the compression of entrapped air by the advancing wetting front. Organic matter is known to reduce the extent of slaking, but the different modes of action have not yet been quantified. The objective of the study was to use theoretical three‐dimensional models to quantify the effect of paper sludge amendment on the key processes controlling internal pressure evolution. A clay loam and a silty‐clay loam were incubated for a 2‐wk period with different amounts and types of paper sludge. Aggregates were then selected, air dried, and then fixed to a hypodermic needle connected to a pressure transducer, and the whole system was immersed in distilled water while images and pressure evolution were recorded. For both soils, the maximum internal pressure was lower in the sludge‐amended aggregates. From the models fitted to the observed data, it appears that the addition of paper sludge resulted in an increase of the potential at the wetting front and a decrease of the near saturated hydraulic conductivity. This result suggests that sludge addition reduces pressure buildup by reducing the rate of water entry, lowering the potential at the wetting front and reducing the hydraulic conductivity of the aggregate.

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)0.001
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 score0.260
Threshold uncertainty score0.511

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.011
GPT teacher head0.242
Teacher spread0.231 · 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

Citations85
Published2005
Admission routes1
Has abstractyes

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