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Record W3210650145 · doi:10.32920/ryerson.14644233.v1

Fatigue damage and life assessment of welded joints based on energy methods

2021· preprint· en· W3210650145 on OpenAlexaff
Faertom Pakandam

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicFatigue and fracture mechanics
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsWeldingStructural engineeringJoint (building)Materials scienceStress (linguistics)Finite element methodFatigue limitHysteresisComposite materialEngineeringPhysics

Abstract

fetched live from OpenAlex

The present study intends to evaluate fatigue damage of different welded joints under loading conditions and their response on fatigue lifetime. The main variables influencing the fatigue life of a welded joint are: applied stress amplitude, material properties, geometrical stress concentration effects, and size and location of welding defects. In order to carry out the study, calculations have been performed using the parameters in three energy-based models. Calculations have been carried out separately for each model from the original experimental data obtained from available literature related to each welded joint. The data variables used as a basis for the calculations of the energy-based models for different welded joints include: cyclic stress-strain properties related to the base metal material type of the welded joints, dimensional and geometrical information on the welded joints, and stress versus endurance cycle tables obtained from the tests performed on the welded joints. All the mentioned variables are parameters influencing the fatigue life of a welded joint. Fatigue damage assessments were performed and discussed based on earlier developed energy damage approaches consisting of: (i) the hysteresis loop based parameter of Masing type material, (ii) the notch stress-intensity based parameter and (iii) the critical plane/energy based parameter. In evaluating fatigue damage of welded joints, these approaches were discussed based on the comparison of energy-lifetime diagrams obtained from each energy model and how readily coefficients/constants are determined and employed in the parameters. In addition, a finite element analysis was performed on selected welded joints to obtain local peak stress values and their location. Numerically obtained stress concentration factor and fatigue notch factor values were also compared with their analytical values. To assess fatigue damage of welded joints based on various energy models, different sets of experimentally obtained fatigue data performed by different laboratories under uniaxial loading conditions available in literature were chosen. The welded joints used in this study were butt joint, cruciform joint, butt-ground joint, and butt-strap fillet joint. The welded joint base metals included low carbon structural steel, aluminium alloys, and carbon steel. The energy models were compared for their energy-fatigue life curve slopes and their ability to converge the related nominal stress-life scatter. The energy values calculated based on their models included the effect of variables of cyclic stresses. Important results were concluded for welded joints from the study including: the relation between fatigue notch factor and fatigue strength, the stress-life diagram slope and fatigue resistance, the ability of the energy models to reflect the fatigue notch factor, and merits and disadvantages of each energy model.

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)0.001
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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0030.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.000
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 head0.038
GPT teacher head0.324
Teacher spread0.287 · 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 designSimulation or modeling
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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Citations0
Published2021
Admission routes1
Has abstractyes

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