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Record W4311268741 · doi:10.1139/cgj-2022-0340

Depth-dependent soil fluidization under cyclic loading—an experimental investigation

2022· article· en· W4311268741 on OpenAlexvenueno aff
Warantorn Korkitsuntornsan, Buddhima Indraratna, Cholachat Rujikiatkamjorn, Thanh Trung Nguyen

Bibliographic record

VenueCanadian Geotechnical Journal · 2022
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Mechanics
Canadian institutionsnot available
Fundersnot available
KeywordsFluidizationGeotechnical engineeringSubgradeWater contentVoid ratioSlurryMaterials scienceAtterberg limitsPore water pressureVoid (composites)Soil waterEnvironmental scienceGeologySoil scienceFluidized bedComposite materialEngineering

Abstract

fetched live from OpenAlex

Past studies have shown that shallow subgrade soil can transform to a slurry (i.e., fluidization) under unfavourable cyclic loading. However, the depth-dependent behaviour of soil parameters during this process has not been properly understood. The current study utilised a large-scale cylindrical test rig, where instrumentation was installed to observe the soil behaviour along the depth of the test specimens under cyclic loading, to examine and quantify the onset of soil fluidization. The results show that excess pore water pressure tends to rise more at the upper layers causing zero-effective stress, while void ratio expands rapidly within the deteriorated soil fabric, making the water content approach the liquid limit of soil when internal moisture migration occurs from the bottom to the top of the specimen. The larger the cyclic load, the deeper the fluidized zone and the faster the fluidization. The study also suggests that the zero-effective stress condition alone cannot interpret the inception of soil fluidization; hence, the change in void ratio and the liquidity index during the application of cyclic loading should also be considered in tandem.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.014
GPT teacher head0.206
Teacher spread0.191 · 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 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

Citations3
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Geotechnical Journal→Same topicGeotechnical Engineering and Soil Mechanics→French-language works237,207→