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Fatigue Testing and Analysis of Aluminum Welds under In-Service Highway Bridge Loading Conditions

2011· article· en· W2143931130 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.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal of Bridge Engineering · 2011
Typearticle
Languageen
FieldEngineering
TopicFatigue and fracture mechanics
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsStructural engineeringBridge (graph theory)EngineeringEurocodeWeldingEquivalence (formal languages)AluminiumMaterials scienceMechanical engineeringMathematicsMetallurgy

Abstract

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For the fatigue design of aluminum structures, most applicable international codes specify fatigue-resistance (S-N) curves with slopes that vary, depending on the detail category. This complicates the selection of appropriate damage equivalence factors for use in highway bridge applications. The existing codes also differ in their treatment of high cycle fatigue, with single-slope S-N curves specified in some cases and multislope curves specified in others. In this paper, a recent investigation conducted to examine the fatigue behavior of aluminum welds under in-service highway bridge loading conditions is summarized. Specifically, calculations performed to establish damage equivalence factors for aluminum for use with the AASHTO and Canadian Standards Association (CSA) CAN/CSA-S6 codes are first reviewed. Following this, small-scale fatigue tests of aluminum welds under simulated highway bridge loading conditions are described. A fracture mechanics model is then validated by comparison with the test results and used to perform simulations encompassing a wider range of loading conditions. On the basis of this work, the adequacy of the current design provisions is discussed and possibilities for further extending the employed methodology are identified.

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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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.442
Threshold uncertainty score0.707

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.051
GPT teacher head0.240
Teacher spread0.189 · 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