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Record W4214596093 · doi:10.1139/cgj-2021-0259

Common characteristics between cyclic behaviours at different frequencies and monotonic behaviours of clay

2022· article· en· W4214596093 on OpenAlexvenueno aff
Tingyu Wu, Junhao Tong, Honglei Sun, Zonghao Yuan, Lin Guo

Bibliographic record

VenueCanadian Geotechnical Journal · 2022
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Mechanics
Canadian institutionsnot available
FundersNational Key Research and Development Program of ChinaNatural Science Foundation of Zhejiang ProvinceNational Natural Science Foundation of China
KeywordsMonotonic functionGeotechnical engineeringCyclic stressStress (linguistics)Clay soilMathematicsMaterials scienceGeologySoil waterComposite materialSoil scienceMathematical analysis

Abstract

fetched live from OpenAlex

The loading frequencies in cyclic tests and the rate of strain or stress in monotonic tests have a significant effect on the soil behaviour, particularly of clayey soil. This study aimed to determine the common characteristics of the behaviour of clay under cyclic loading at different frequencies and the relationship between cyclic and monotonic behaviours. Monotonic triaxial tests and cyclic triaxial tests at frequencies of 0.1 and 0.001 Hz were conducted on undrained saturated reconstituted soft clay. The results showed that the frequency of 0.001 Hz is sufficiently low to make the soil response comparable to that in monotonic tests. Second, there exists a unique “feature line” for cyclic tests in the plot of allowable stress versus strain, independent of the frequency. Third, the feature lines for the cyclic and monotonic tests are close and parallel to each other. Therefore, although the cyclic and monotonic loadings are quite different from each other, there are connections between these different loadings in terms of the relationship between the allowable stress and strain.

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)0.002
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 score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.012
GPT teacher head0.202
Teacher spread0.190 · 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

Citations2
Published2022
Admission routes1
Has abstractyes

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