MétaCan
Menu
Back to cohort
Record W2917885823 · doi:10.1139/cgj-2018-0733

Interpretation of bender element test results using sliding Fourier transform method

2019· article· en· W2917885823 on OpenAlexvenueno aff
Jyant Kumar, Ninad Sanjeev Shinde

Bibliographic record

VenueCanadian Geotechnical Journal · 2019
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Underground Structures
Canadian institutionsnot available
Fundersnot available
KeywordsShear (geology)GeologyGeotechnical engineeringFourier transformAcousticsBoundary element methodStructural engineeringEngineeringMathematicsMathematical analysisPhysicsFinite element method

Abstract

fetched live from OpenAlex

Identification of the arrival point of the shear wave in bender element tests is a task that can have ambiguous results. The contamination of the received shear wave signal with a weak P-wave component, which can emerge either directly from the transmitter or reflect from the side boundary, makes the judgement involved in this task dubious. The different available procedures to mark the arrival times of the shear wave are often prone to errors. A method is proposed to identify the time of the arrival of the shear wave. The predominant frequency of the received signal is first evaluated and then, with the help of the sliding Fourier transform approach, the arrival of the shear wave is identified. The method does not require any manual intervention. The proposed approach is applied to bender element tests performed on dry and saturated sand and glass beads by varying (i) input frequency of the signal, (ii) confining pressure, and (iii) void ratio. Results for different cases, including those obtained by using resonant column tests, are found to be very promising.

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)0.001
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: none
Teacher disagreement score0.951
Threshold uncertainty score0.747

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.010
GPT teacher head0.233
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 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

Citations15
Published2019
Admission routes1
Has abstractyes

Explore more

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