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Record W4366179034 · doi:10.3390/geotechnics3020013

Effect of Sample Preparation on Saturated and Unsaturated Shear Strength of Cohesionless Soils

2023· article· en· W4366179034 on OpenAlexaff
Ilyas Akram, Shahid Azam

Bibliographic record

VenueGeotechnics · 2023
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Mechanics
Canadian institutionsUniversity of Regina
Fundersnot available
KeywordsCohesion (chemistry)Soil waterGeotechnical engineeringShear (geology)SuctionSaturation (graph theory)Soil testOverburden pressureOverburdenMaterials scienceGeologyComposite materialChemistrySoil scienceMathematicsThermodynamics

Abstract

fetched live from OpenAlex

The geotechnical behavior of cohesionless soils is governed by field conditions. Such soils exist in two distinct forms, namely: disintegrated, such as fresh sediments under no overburden and/or no suction, and intact, such as old deposits with overburden and/or suction. The main contribution of this research was the successful capture of field conditions in laboratory samples, and the determination of shear strength under saturated and dried states. Results indicated that disintegrated samples possess identical soil behavior under both saturation states. Shear stiffness and peak shear increased with increasing normal stress, and no clear failure peaks were observed, similar to loose soils. Both samples showed an initial contraction followed by dilation at low normal stresses and mostly contraction at high normal stresses. Apparent cohesion was non-existent, and the friction angle measured 44.5° in the saturated state and 48° in the dried state. The intact sample exhibited behavior similar to the disintegrated sample when saturated. Under the dried state, clear failure peaks followed by residual shear were observed, similar to dense soils. Soil response was primarily dilative at low normal stresses and largely contractive under high normal stresses. Apparent cohesion was zero, and friction angle was 42° in the saturated state and changed to 91 kPa and 36°, respectively, in the dried state. Finally, structural cohesion increased with normal stress, and the friction angle due to suction was between 0.05° and 0.02°.

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)0.001
metaresearch head score (Gemma)0.003
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 score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.229
Teacher spread0.223 · 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

Citations8
Published2023
Admission routes1
Has abstractyes

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