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Record W2312329521 · doi:10.1139/cgj-2012-0379

Effect of load shape on relationship between dissipated energy and residual excess pore pressure generation in cyclic triaxial tests

2013· article· en· W2312329521 on OpenAlexvenueno aff
Carmine P. Polito, Russell A. Green, Erin Dillon, Changbum Sohn

Bibliographic record

VenueCanadian Geotechnical Journal · 2013
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Mechanics
Canadian institutionsnot available
FundersDivision of Civil, Mechanical and Manufacturing InnovationPolitecnico di TorinoValparaiso UniversityNational Science Foundation
KeywordsPore water pressureLiquefactionGeotechnical engineeringDissipationSoil liquefactionResidualEffective stressOverburden pressureCyclic stressRange (aeronautics)Soil waterMaterials scienceStructural engineeringGeologyEngineeringComposite materialMathematicsSoil science

Abstract

fetched live from OpenAlex

The energy dissipated in soil during cyclic loading can be used to predict the change in the pore-water pressure developed in the soil. To examine whether the energy required to cause liquefaction is dependent on or independent of the load shape applied, a series of 28 cyclic triaxial tests were performed using five different load shapes having a range of cyclic stress ratios. The five load shapes were applied to identically prepared specimens of clean sand and the dissipated energy – pore pressure generation characteristics examined. It was found that that the dissipated energy to cause initial liquefaction was normally distributed and independent of the load shape, although it is seemingly somewhat dependent on duration of loading. A corollary to this finding is that laboratory data from specimens tested using sinusoidal loadings can be used to calibrate the Green, Mitchell, and Polito (GMP) energy-based pore pressure generation model for use in predicting in situ pore pressures in soils subjected to nonsinusoidal loadings (e.g., earthquake loadings). Given the relative simplicity of the GMP model, these findings make the model an attractive alternative to implement in effective stress dynamic response codes.

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)0.001
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 score0.115
Threshold uncertainty score0.767

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.015
GPT teacher head0.222
Teacher spread0.208 · 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

Citations91
Published2013
Admission routes1
Has abstractyes

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