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Record W7073998686

Development of a three-dimensional multi-scale model to study the formation of solidification defects in fusion welding,

2016· other· en· W7073998686 on OpenAlexaff

Bibliographic record

VenuecIRcle (University of British Columbia) · 2016
Typeother
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCell Image Analysis Techniques
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsEquiaxed crystalsMicrostructureWeldingDeformation (meteorology)ShrinkageFlow (mathematics)Fusion weldingDevelopment (topology)Fluid dynamicsCracking
DOInot available

Abstract

fetched live from OpenAlex

One of the long-standing challenges in joining of aluminum alloys is the occurrence of solidification defects, i.e. hot cracking and porosity, since these defects significantly increase manufacturing costs. This research project investigates the formation of solidification defects through development of a novel and comprehensive 3-D multi-scale and multi-physics numerical study and then application to the GTA welding of the aluminum alloy AA6061. The developed multi-scale model is composed of four different modules: 1) Solidification, 2) Deformation, 3) Fluid flow, and 4) Defect formation. The solidification module numerically reconstructs the 3-D microstructure of semisolid welds using a granular model of solidification. Specifically, a modified Voronoi tessellation algorithm is used to generate an unstructured grid representing the weld microstructure. The reconstructed microstructure contains both columnar and equiaxed grains and varies as a function of welding process parameters. Then, the Scheil equation is used in combination with the temperature field obtained through the Rosenthal equation and the reconstructed 3D microstructure to simulate solidification. This module outputs the evolving 3D structure of the semisolid weld composed of solid grains and a network of micro liquid channels for use by the deformation and fluid flow modules as the simulation geometry. The deformation module analyzes via finite elements the deformation of the semisolid weld due to externally applied strains and self-induced strains such as thermo-mechanical strains and solidification shrinkage in order to obtain local strain rates within the micro liquid channels. The local strain rates outputted by the deformation module feed a fluid flow analysis module in which the pressure field within the semisolid weld is calculated. Finally, the defect formation module uses various defect formation models to link the pressure field and the local strain rates to the formation of solidification defects including micro cracks and hydrogen porosity.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.010
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.014
GPT teacher head0.224
Teacher spread0.210 · 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
GenreMethods

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
Published2016
Admission routes1
Has abstractyes

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