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Record W1972436043 · doi:10.1139/t00-125

Modified Cam-Clay modelling of temperature effects in clays

2001· article· en· W1972436043 on OpenAlexvenueno aff
J. Graham, Naoto Tanaka, Thomas Crilly, Marolo Alfaro

Bibliographic record

VenueCanadian Geotechnical Journal · 2001
Typearticle
Languageen
FieldEngineering
TopicSoil and Unsaturated Flow
Canadian institutionsnot available
Fundersnot available
KeywordsGeotechnical engineeringCritical state soil mechanicsIsothermal processPore water pressureStress (linguistics)GeologyMaterials scienceThermodynamicsEngineeringConstitutive equationFinite element methodStructural engineering

Abstract

fetched live from OpenAlex

The Cam-Clay model for isothermal mechanical behaviour of clays has been extended to take account of the effects of temperature on stress–strain behaviour. The assumptions used in constructing the new model are based on published results and on new data presented in the paper. The model allows prediction of how heating and cooling affect volume changes, pore-water pressures, and strengths for both normally consolidated and overconsolidated saturated clays. It permits modelling of observed reductions in the overconsolidation ratio with increasing temperature. The model provides accessible qualitative explanations for temperature effects that were previously difficult to understand. It will also allow easy implementation for quantitative modelling in triaxial stress fields. Results predicted by the model are compared with data collected by the authors at temperatures up to 100°C. The model does not account for changes that occur in clay minerals at higher temperatures, for example, in bentonites at temperatures higher than about 150°C.Key words: clay, triaxial, temperature, modelling, elastic–plastic, Cam-Clay.

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)0.001
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 score0.018
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
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 head0.012
GPT teacher head0.192
Teacher spread0.180 · 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

Citations250
Published2001
Admission routes1
Has abstractyes

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