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Record W1994815249 · doi:10.1115/1.2137751

Tensile-Shear Forces and Fracture Modes in Single and Multiple Weld Specimens in Dual-Phase Steels

2005· article· en· W1994815249 on OpenAlexfundno aff
Manuel Marya, Kathy Wang, Louis G. Hector, Xiaohong Gayden

Bibliographic record

VenueJournal of Manufacturing Science and Engineering · 2005
Typearticle
Languageen
FieldEngineering
TopicMetal Forming Simulation Techniques
Canadian institutionsnot available
FundersMcMaster University
KeywordsMaterials scienceDual-phase steelUltimate tensile strengthSpot weldingShear (geology)Composite materialWeldingFracture (geology)Deformation (meteorology)MetallurgyMicrostructureMartensite

Abstract

fetched live from OpenAlex

In this article, weld fracture criteria based upon low strain rate (i.e., ε̇∼10−3-10−2s−1) tensile-shear tests of spot welds in dual-phase (DP) steels DP600, DP780, and DP980 are developed. Three empirical equations are inferred from least-squares root-fitting analyses of tensile-shear testing data. Building upon existing results in the literature, the first equation relates the tensile-shear force to the weld diameter. The second and third equations relate, respectively, a critical weld diameter and a critical tensile-shear force for interfacial fracture to the sheet thickness and hardness extrema in the heat-affected zone. These idealized equations can serve as the basis for further development of fracture criteria resembling material flow laws that account for higher strain rates and more complicated deformation paths. The effect of spot-weld placement in specific patterns or arrays on deformation and fracture behavior was also investigated to explore underlying effects from deformation field interactions between adjacent spot welds.

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 score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
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 head0.012
GPT teacher head0.237
Teacher spread0.225 · 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

Citations107
Published2005
Admission routes1
Has abstractyes

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