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Record W4390938172 · doi:10.1139/cgj-2023-0150

Degradation mechanisms of soil arching under a localized cyclic surface loading

2024· article· en· W4390938172 on OpenAlexvenueno aff
Fengjuan Tao, Guanbao Ye, Zhen Zhang, Jie Han, Rongjun Zhang, Liu Liu

Bibliographic record

VenueCanadian Geotechnical Journal · 2024
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Stabilization
Canadian institutionsnot available
FundersNational Natural Science Foundation of ChinaShanghai Science and Technology Development Foundation
KeywordsGeotechnical engineeringCyclic stressDegradation (telecommunications)GeologyPileStress (linguistics)Structural engineeringEngineering

Abstract

fetched live from OpenAlex

Soil arching causes stress redistribution in many earth structures, such as pile-supported embankments and buried structures. A localized cyclic surface load (e.g., footing and traffic load) would weaken the arching effect and cause structural safety at potential risk. This paper presents a series of trapdoor tests using transparent soil to investigate the degradation mechanisms of soil arching subjected to a localized cyclic surface load. The particle image velocimetry (PIV) technique was adopted to monitor the inner soil deformations during test. The test results show that soil arching under localized cyclic surface loading first degraded locally on the trapdoor center and then progressed from the center to the entire trapdoor. The soil arching degraded faster within a lower backfill, on a wider trapdoor, and under a higher load frequency of localized surface loading. Owing to the volumetric expansion during trapdoor movement, the average vertical stress with soil arching increased faster under localized surface loading than that without soil arching. After full degradation of soil arching, the stress increment and vertical displacement contours with and without arching effect gradually tended to be similar. Finally, an empirical method was proposed to predict the soil arching ratio under localized cyclic surface loading.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.927
Threshold uncertainty score0.727

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.010
GPT teacher head0.207
Teacher spread0.197 · 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

Citations8
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Geotechnical JournalSame topicGeotechnical Engineering and Soil StabilizationFrench-language works237,207