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Record W3101618130 · doi:10.1177/0954405420970087

Flow, process forces and strains during Friction Stir Welding: A comprehensive First principle approach

2020· article· en· W3101618130 on OpenAlex
Dhruv Bajaj, Arshad Noor Siddiquee, Noor Zaman Khan, A. K. Mukhopadhyay, Sohail M.A.K. Mohammed, D.L. Chen, Namrata Gangil

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.

Bibliographic record

VenueProceedings of the Institution of Mechanical Engineers Part B Journal of Engineering Manufacture · 2020
Typearticle
Languageen
FieldEngineering
TopicAdvanced Welding Techniques Analysis
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsMaterial flowFriction stir weldingProcess (computing)Shear (geology)MechanicsFlow (mathematics)WeldingMechanical engineeringScale (ratio)Rotation (mathematics)Computer scienceMaterials scienceEngineeringPhysicsComposite materialArtificial intelligence

Abstract

fetched live from OpenAlex

Friction stir welding is recent yet spectacular process, which assumes accrescent expanse to evolve as a multi-purpose process. Its potential is greatly being tapped through large-scale experimental and computer simulation-based investigations. Several simulation and empirical models have been proposed but exact fundamental analyses on forces, material flow and strain are still absent. Complexities associated with the process are perhaps the main reason that a fundamental analysis is difficult. A comprehensive analysis of this kind is critical for understanding the evolution of microstructure, mechanical properties of joint and defect formation. This study presents an analysis of material flow, process forces and strains using first principle approach. Results have been presented as exact mathematical expressions in terms of material properties and process parameters. It was demonstrated that the material during stirring experiences direct and shear strains both when it moves from advancing side to retreating side in front of the tool and after rotation deposits behind the tool. It was also demonstrated that the strain significantly reduced from advancing to retreating side; for a typical case the shear strain greater than 10,000% prevails in advancing side and the maximum shear strain on retreating side is of the order of 6000%.

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.

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 score0.349
Threshold uncertainty score0.969

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.012
GPT teacher head0.214
Teacher spread0.202 · 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