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Record W3210535235 · doi:10.1002/nag.3290

Analytical solution for distributed torsional low strain integrity test for pipe pile

2021· article· en· W3210535235 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInternational Journal for Numerical and Analytical Methods in Geomechanics · 2021
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Underground Structures
Canadian institutionsWestern University
FundersSystematic Project of Guangxi Key Laboratory of Disaster Prevention and Structural SafetyNational Natural Science Foundation of China
KeywordsPileStructural engineeringNeckingFinite element methodEngineeringDynamic load testingGeotechnical engineeringMaterials scienceComposite material

Abstract

fetched live from OpenAlex

Abstract Low strain integrity tests (LSITs) are the most popular non‐destructive methods for pile testing. However, traditional LSITs have encountered unprecedented challenges as the need for long pile and existing pile testing keeps multiplying. Compared to traditional longitudinal excitations, the torsional wave is less influenced by the velocity attenuation effect and can be subjected at the pile shaft for existing piles. Distributed torsional LSIT is proposed in this article with the presentation of the corresponding analytical solutions that exhibiting the velocity responses along the pile shaft. The solution is verified with previous simplified theoretical and rigorous finite element method (FEM) answers. At the end, the application of this method is exhibited through the identification of necking and concrete segregation defects on pipe piles, which shows the advantage of this method on long pile testing.

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.

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)0.004
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: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.713
Threshold uncertainty score0.837

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.004
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 head0.027
GPT teacher head0.349
Teacher spread0.322 · 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