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Fatigue Life of Girders with Trapezoidal Corrugated Webs

2006· article· en· W2099190600 on OpenAlexaff
Richard Sause, Mohamed Abbas, Robert G. Driver, Kengo Anami, John W. Fisher

Bibliographic record

VenueJournal of Structural Engineering · 2006
Typearticle
Languageen
FieldEngineering
TopicStructural Load-Bearing Analysis
Canadian institutionsUniversity of Alberta
FundersLehigh UniversityPennsylvania Department of Community and Economic DevelopmentPennsylvania Department of Transportation
KeywordsGirderFlangeStructural engineeringWeldingFillet weldFillet (mechanics)EngineeringFatigue limitMechanical engineering

Abstract

fetched live from OpenAlex

Fatigue design criteria are necessary to design steel corrugated web girders for highway bridges. The paper presents research on the fatigue life of steel bridge I-girders with trapezoidal web corrugations. Eight large-scale test girders were fabricated from HPS 485W steel and fatigue-tested in four-point bending. The web-to-flange fillet welds were made using semiautomatic gas metal arc welding (GMAW) or robotic GMAW. Fatigue cracks initiated in the tension flange at the web-to-flange fillet weld toe along the inclined web folds and adjacent bend regions, and propagated in the flange. The results demonstrate that steel corrugated web I-girders exhibit a fatigue life that is longer than that of conventional steel I-girders with transverse stiffeners. For design of corrugated web I-girders, the Category B′ design curve of the AASHTO LRFD specifications is recommended for finite life fatigue design calculations, and a value of 96.5MPa(14.0ksi) is recommended for the constant amplitude fatigue limit.

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 score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0010.000

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 head0.004
GPT teacher head0.172
Teacher spread0.167 · 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

Citations57
Published2006
Admission routes1
Has abstractyes

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