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Undrained Pore Pressure Prediction in Clayey Soil under Cyclic Loading

2014· article· en· W1985882023 on OpenAlexaff
Monideepa Paul, Ramendu Bikas Sahu, Goutam Banerjee

Bibliographic record

VenueInternational Journal of Geomechanics · 2014
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Mechanics
Canadian institutionsHeritage College
Fundersnot available
KeywordsPore water pressureGeotechnical engineeringSoil waterEffective stressPlasticityOverburden pressureGeologySoil scienceMaterials scienceComposite material

Abstract

fetched live from OpenAlex

Prediction of pore-water pressure is important for understanding the behavior of soils under both static and cyclic loading and also for estimation of their effective stresses. Undrained cyclic pore pressure models available in the literature are for some typical soils and are hardly applicable for other soils. In this paper, a generalized hyperbolic model for prediction of undrained pore-water pressure has been proposed as a function of cyclic stress ratio, frequency, and plasticity of soils using data reported by a number of researchers. The proposed model has been validated by a chi-square goodness-of-fit test. The correlation between the predicted and measured pore pressure ratio at various confining pressure regimes has also been statistically examined to discern the model. The model output has been found to be correlated to an extent of up to 85% with the literature data.

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: none
Teacher disagreement score0.784
Threshold uncertainty score0.641

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.005
GPT teacher head0.200
Teacher spread0.195 · 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

Citations31
Published2014
Admission routes1
Has abstractyes

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