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Record W2605385726 · doi:10.1139/cgj-2016-0531

Effect of specimen preparation techniques on dynamic properties of unsaturated fine-grained soil at high suctions

2017· article· en· W2605385726 on OpenAlexvenueno aff
C.W.W. Ng, Sina Baghbanrezvan, Hamed Sadeghi, Chao Zhou, Fardin Jafarzadeh

Bibliographic record

VenueCanadian Geotechnical Journal · 2017
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Mechanics
Canadian institutionsnot available
Fundersnot available
KeywordsShear modulusSuctionSiltMaterials scienceDamping ratioGeotechnical engineeringSoil waterComposite materialShear (geology)Dynamic modulusDynamic mechanical analysisGeologySoil scienceThermodynamics

Abstract

fetched live from OpenAlex

The seismic response of soil depends on proper evaluation and use of soil dynamic properties, including shear modulus and damping ratio at various strain levels. Despite extensive studies on the shear modulus and damping ratio of saturated soils, research on the dynamic properties of unsaturated fine-grained soils — especially at high suction — is limited. This study aims to investigate the dynamic properties of loess at a variety of initial states resulting from different specimen preparation techniques (reconstituted, recompacted, and intact) and their evolutions due to suction-induced desiccation. Results of resonant column tests show that at initial states, the specimen preparation technique has a negligible effect on the normalized modulus (G/G max ) and damping degradation pattern, while the influence becomes significant at a high suction (40 MPa). This is attributed to the microstructural evolution of specimens with different initial states that were subjected to suction-induced desiccation. More specifically, the elastic shear strain threshold decreases (reduction of elastic range) while shear modulus increases as suction reaches 40 MPa. Furthermore, the rate of increase in the damping ratio as well as degradation of the shear modulus for specimens at high suction is faster than their initial states. Based on the scanning electron microscopy observations, these findings may be attributed to the aggregation of larger silt–clay assemblies induced by suction increase. Consequently, soil with larger aggregates behaves more like granular sandy soil than saturated silt or clay.

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 score0.389
Threshold uncertainty score0.773

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.006
GPT teacher head0.209
Teacher spread0.203 · 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

Citations44
Published2017
Admission routes1
Has abstractyes

Explore more

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