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Record W3134107920 · doi:10.2749/newyork.2019.0799

Investigation and Diagnosis of Fatigue Cracks of Rib-to-Deck Welded Joints in Orthotropic Decks by the Phased Array Ultrasonic Scanner

2019· article· en· W3134107920 on OpenAlexaff
Masafumi Hattori, Koji Osada, S. Nojima, Hideyuki Tatematsu

Bibliographic record

VenueReport · 2019
Typearticle
Languageen
FieldEngineering
TopicInfrastructure Maintenance and Monitoring
Canadian institutionsNexen (Canada)
Fundersnot available
KeywordsOrthotropic materialDeckWeldingStructural engineeringBridge deckPhased arrayUltrasonic sensorScannerMaterials scienceAcousticsEngineeringComposite materialFinite element methodElectrical engineering

Abstract

fetched live from OpenAlex

<p>Over the last decade, fatigue cracks have been observed at the rib-to-deck welded joints in many orthotropic decks in Japan. Considering the fatigue cracks can cause pavement damage and thus compromise transportation safety, it is necessary to detect and repair it at the early stage of its development. But the cracks occur from the weld route, it cannot be detected in early stage by visual check. Therefore, the phased array ultrasonic scanner (PAUS) has been developed as the method which can detect and measure the cracks with small size. And, it can simultaneously investigates the deck propagation type cracks and the weld bead propagation type cracks.</p><p>In this study, we propose a diagnosis method which considered the relation with selected countermeasures based on technological knowledge. And we propose an investigation area selecting method based on investigation speed of the PAUS which is confirmed by trial on the real bridge. In addition, the cost advantage by using the PAUS is estimated.</p>

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.329
Threshold uncertainty score0.313

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.000
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 head0.011
GPT teacher head0.229
Teacher spread0.218 · 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 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

Citations0
Published2019
Admission routes1
Has abstractyes

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