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Record W4365459980 · doi:10.1139/cgj-2022-0442

Characteristics of solid–liquid phase transformation of saturated coral sand subjected to various patterns of cyclic loading

2023· article· en· W4365459980 on OpenAlexvenueno aff
You Qin, Xinyu Du, Zhengtao Yang, Weijia Ma, Qi Wu, Guoxing Chen

Bibliographic record

VenueCanadian Geotechnical Journal · 2023
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Mechanics
Canadian institutionsnot available
Fundersnot available
KeywordsMaterials scienceGeotechnical engineeringShear stressPhase (matter)Stress pathGeologyShear (geology)Composite materialChemistry

Abstract

fetched live from OpenAlex

This study conducts a series of undrained cyclic shear tests on saturated coral sand with different initial relative densities ( D r ) subjected to a 90° jump rotation of the principal stress with various initial orientations. Considering liquefiable coral sand as a fluid, an important finding is that the variation in the apparent viscosity with the number of cycles is significantly affected by D r , the effective mean principal stress ( [Formula: see text] ), cyclic stress ratio, cyclic loading path, and cyclic loading frequency. The average flow coefficient (κ) is introduced to describe the fluidity of saturated coral sand under cyclic loading by considering the variation in the shape of the stress–strain rate curve. A positive exponential correlation is observed between κ and the excess pore water pressure (EPWP) ratio ( r u ) under the given cyclic loading modes. Another significant finding is that the solid–liquid phase change time is the turning point of the apparent viscosity and the average flow coefficient gradients with r u . The inversion point’s EPWP ratio is approximately 0.9, defined as the EPWP ratio during the solid–liquid phase transformation ( r uth ). The r uth value is not affected by cyclic loading mode, [Formula: see text] , and D r .

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)0.000
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.300
Threshold uncertainty score0.748

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.011
GPT teacher head0.229
Teacher spread0.218 · 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 designBench or experimental
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

Citations25
Published2023
Admission routes1
Has abstractyes

Explore more

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