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Record W3165312810 · doi:10.3233/978-1-61499-601-9-358

Relationship Between Undrained Shear Strength And Shear Wave Velocity For Clays

2015· book-chapter· en· W3165312810 on OpenAlexaboutno aff
Shehab S. Agaiby, Mayne Paul W.

Bibliographic record

VenueIOS Press eBooks · 2015
Typebook-chapter
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Mechanics
Canadian institutionsnot available
Fundersnot available
KeywordsGeotechnical engineeringGeologyShear (geology)Shear strength (soil)Wave velocitySoil waterSoil sciencePetrology

Abstract

fetched live from OpenAlex

The interrelationship between undrained shear strength (su) and downhole shear wave velocity (VsVH) of normally consolidated (NC) and lightly overconsolidated (LOC: OCR < 2) to overconsolidated (OC) to highly overconsolidated (HOC: OCR > 10) clays is investigated in the presented study. The main objective of this research program is to develop a worldwide database of high quality in-situ geophysical and laboratory strength data from thirty seven well-documented geotechnical sites from locations in Australia, Brazil, Canada, China, Italy, Japan, South Korea, North Sea, Norway, Singapore, Sweden, Thailand, United Kingdom, USA, and Vietnam. The study includes undrained shear strength measurements on undisturbed samples of normally to lightly overconsolidated intact to overconsolidated and fissured clays using anisotropically-consolidated triaxial compression tests (CAUC). Shear wave velocities were measured in the field by downhole tests (DHT), in many cases via seismic piezocones (SCPTu). Analyses of the compiled database found approximate trends between undrained shear strength and shear wave velocity. Tentative correlations are explored by including other various parameters such as Atterberg limits, void ratio, overconsolidation ratio (OCR), and effective vertical stresses. The correlative trends may aid geotechnical engineers in helping to assess suprofiles in clay deposits in preliminary investigations and as an independent method in collaboration with sampling, lab testing, and other field data.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.093
GPT teacher head0.248
Teacher spread0.155 · 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 designObservational
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

Citations11
Published2015
Admission routes1
Has abstractyes

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