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Record W4385303672 · doi:10.18280/acsm.470304

Effect of Porosity Shape, Size and Distribution on Stress Intensity Factors in Spot Welded Joints: A Finite Element Study

2023· article· en· W4385303672 on OpenAlexvenueno aff
Imen Benala, Leila Zouambi, Farida Bouafia, B. Sérier, Sardar Sikandar Hayat

Bibliographic record

VenueAnnales de Chimie Science des Matériaux · 2023
Typearticle
Languageen
FieldEngineering
TopicAdvanced Welding Techniques Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsFinite element methodMaterials scienceSpot weldingPorosityWeldingStress intensity factorIntensity (physics)Structural engineeringComposite materialEngineeringPhysicsOptics

Abstract

fetched live from OpenAlex

In this study, the influence of porosity on crack initiation behavior in welded structures subjected to spot welding was investigated.Three-dimensional (3D) finite element analyses were conducted using the ABAQUS finite element software under mechanical stress.The stress intensity factors (SIF) in opening and moving modes were computed employing the finite element technique.A comprehensive analysis of various parameters, including mechanical load, crack size, porosity form, porosity size, porosity-crack interaction, and crack orientation, was carried out.This investigation was approached as a mixed-mode, plane stress, and linear elastic fracture mechanics problem with a focus on the passive voice.The results demonstrated that the stress intensity factor is not only dependent on the magnitude of the applied mechanical loading but also on factors such as crack size, porosity form, defect-defect interaction, and crack orientation.Additionally, it was observed that both the size and form of porosity play a significant role in influencing the stress intensity factors.This research contributes to the understanding of fracture mechanics in welded structures and provides valuable insights for enhancing the structural integrity and reliability of such systems.

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)0.002
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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.021
GPT teacher head0.287
Teacher spread0.265 · 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".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractno

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