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Record W2326832044 · doi:10.1061/41016(314)2

Fatigue Analysis of Needle Peened Welds under Variable Amplitude Loading Conditions

2008· article· en· W2326832044 on OpenAlexafffund
Scott Walbridge

Bibliographic record

VenueStructures Congress 2008 · 2008
Typearticle
Languageen
FieldEngineering
TopicFatigue and fracture mechanics
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Waterloo
KeywordsMaterials scienceAmplitudeStress (linguistics)WeldingStructural engineeringStress intensity factorStress concentrationRange (aeronautics)Fatigue limitComposite materialFracture mechanicsEngineeringPhysicsOptics

Abstract

fetched live from OpenAlex

Regarding the analyses presented herein, the following comments can be made: 1 Both models show a decrease in the treatment benefit (fatigue life improvement) with an increase in the stress range under constant amplitude loading for all stress ratios. 2 Under constant amplitude loading, the strain-based model predicts higher fatigue lives for the untreated weld and a lower treatment benefit, regardless of the stress range/ratio. 3 Despite the lower benefit predicted by the strain-based model, significant fatigue life improvements are still seen. For example, at stress ranges less than ∼450 MPa at R = –1 or ∼250 MPa at R = 0, a fatigue life improvement of 100% or greater is still predicted. 4 Both models predict that the effect of the periodic compressive overloads on the fatigue life of the untreated weld will generally be less significant than for the treated weld. 5 For the treated weld, the fatigue life can be seen to decrease as the magnitude of the overload stress increases. This is also reflected in the calculated treatment benefit at the various stress ranges. Interestingly, the drop in the treatment benefit (in terms of the fatigue life improvement) is most pronounced in the results obtained using the LEFM model. When comparing the results obtained using the two models, it may be noted that the largest differences can be seen at the lower stress ranges, even though the influence of the non-linear material behaviour is the lowest at these stress ranges. The reason for this trend is that the stress intensity factor (SIF) calculated using (10) considers the effect of the non-uniform stress distribution along the crack edges, whereas the SIF calculated using (3) does not. As the crack grows out of a weld toe notch, this effect becomes more significant and the influence of the non-linear material behaviour diminishes. The reason that (3) has been used successfully in [11–13] to model the behaviour of small cracks emanating from notches may be that the non-uniform stress distribution plays a much less significant role in this case, in particular when the level of yielding is significant. One possible way to account for this observation would be to use a hybrid model that uses (3) for the smaller crack depths and then switches to (10) when the influence of the nonlinear material behaviour is seen to become negligible. Despite the apparent limitations of the models employed herein, the following conclusions can be drawn from this work: 1 Under constant amplitude loading conditions, although considering the nonlinear material behaviour appears to reduce the predicted treatment effectiveness, substantial benefits are still seen — even at relatively high applied stress range levels. 2 Both the LEFM and strain-based fracture mechanics models predict a significant decrease in the treatment effectiveness for load histories that include periodic compressive overloads. The reduction in fatigue life due to the compressive overloads is generally greater for the treated welds than for the corresponding untreated welds. 3 On this basis, it is concluded that, although residual stress-based post-weld treatments have shown strong potential as a means for improving or rehabilitating the welds in existing steel structures such as bridges, it is important that the influence of the true load history be considered when exploiting the benefits of these treatments.

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 score0.004
Threshold uncertainty score0.009

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 communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.024
GPT teacher head0.252
Teacher spread0.228 · 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".

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Citations2
Published2008
Admission routes2
Has abstractyes

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