MétaCan
Menu
Back to cohort
Record W4283659165 · doi:10.1680/jgele.21.00155

Novel evaluation of mass polar moment of inertia of the drive plate in resonant column

2022· article· en· W4283659165 on OpenAlexaff
Zahid Khan, Giovanni Cascante, Rana E. Ahmed

Bibliographic record

VenueGéotechnique Letters · 2022
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Mechanics
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsMoment of inertiaStiffnessCalibrationInertiaStructural engineeringRotary inertiaAdded massMaterials scienceMoment (physics)MechanicsAcousticsPhysicsEngineeringClassical mechanicsVibration

Abstract

fetched live from OpenAlex

Resonant column (RC) is a standard laboratory test for the dynamic characterization of soils. Mass polar moment of inertia (MPMI) of the drive plate of RC is required for the solution of equation of motion for a specimen-mass system in RC. In standard procedure, the MPMI is evaluated by testing of calibration probes. Studies have shown that torsional stiffness of the probes have significant effect on the evaluation of MPMI of drive plate due to contribution from base of RC. The extent of contribution increases with increase in torsional stiffness of probes and consequently error in MPMI increases. This study presents a new calibration method that does not use probes. The MPMI of the drive plate is evaluated by suspension of drive plate with polyamide wire of negligible torsional stiffness and damping. The modified equation of motion is used to evaluate the MPMI of drive plate. Results show that the variation of MPMI with frequency is very small compared to its variation from conventional procedure. The apparent values of MPMI from conventional procedure are found to be higher than its inferred true-value, which results in overestimation of shear wave velocity of soil specimen.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

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 communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.011
GPT teacher head0.197
Teacher spread0.186 · 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

Citations2
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueGéotechnique LettersSame topicGeotechnical Engineering and Soil MechanicsFrench-language works237,207