MétaCan
Menu
Back to cohort
Record W2999246558 · doi:10.1139/cgj-2018-0823

Comparison of small-strain shear modulus and Young’s modulus of dry sand measured by resonant column and bender–extender element

2020· article· en· W2999246558 on OpenAlexvenueno aff
Kai Xu, Xiaoqiang Gu, Chao Hu, Lutong Lu

Bibliographic record

VenueCanadian Geotechnical Journal · 2020
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Underground Structures
Canadian institutionsnot available
FundersFundamental Research Funds for the Central UniversitiesNational Natural Science Foundation of China
KeywordsShear modulusCalibrationModulusMaterials scienceCalibration curveTangent modulusAggregate modulusPoisson's ratioYoung's modulusComposite materialStructural engineeringGeotechnical engineeringDynamic modulusGeologyPoisson distributionMathematicsChemistryEngineeringDynamic mechanical analysisChromatography

Abstract

fetched live from OpenAlex

The small-strain shear modulus and Young’s modulus of dry sand are simultaneously measured by resonant column and bender–extender element tests. Two different methods are adopted to calibrate the resonant column and the results indicate that the conventional calibration method may significantly underestimate the Young’s modulus obtained in flexural excitation, while it only slightly underestimates the shear modulus obtained in torsional excitation. A new calibration method that establishes a calibration curve based on the resonant frequency is used to overcome the error. With this new calibration method, the shear modulus and Young’s modulus from the resonant column agree well with those from the bender–extender element. It convincingly explains the reason why a very small Poisson’s ratio was observed in previous resonant column tests and suggests that the effect of resonant frequency on the calibration results must be considered in flexural excitation.

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: Empirical
Teacher disagreement score0.493
Threshold uncertainty score0.950

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.017
GPT teacher head0.216
Teacher spread0.199 · 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

Citations19
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Geotechnical JournalSame topicGeotechnical Engineering and Underground StructuresFrench-language works237,207