MétaCan
Menu
Back to cohort
Record W2971004102 · doi:10.1007/s11661-019-05437-0

The Effect of Die Bearing Geometry on Surface Recrystallization During Extrusion of an Al-Mg-Si-Mn Alloy

2019· article· en· W2971004102 on OpenAlex

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueMetallurgical and Materials Transactions A · 2019
Typearticle
Languageen
FieldEngineering
TopicMetallurgy and Material Forming
Canadian institutionsRio Tinto (Canada)University of British ColumbiaUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsExtrusionMicrostructureMaterials scienceElectron backscatter diffractionDie (integrated circuit)MetallurgyDynamic recrystallizationAlloyDeformation (meteorology)Composite materialHot working

Abstract

fetched live from OpenAlex

Abstract The formation of large surface grains known as peripheral coarse grains (PCG) is an undesirable feature commonly observed in extruded medium-strength Al-Mg-Si alloys produced for many applications including automotive. The objective of this study was to evaluate factors contributing to the formation of PCG layers, particularly the die bearing geometry, with the goal of developing strategies to eliminate or reduce this phenomenon. This was accomplished using a combination of extrusion trials and finite element method simulations to characterize the role of die bearing geometry on the formation of surface microstructure during the extrusion of an Al-Mg-Si-Mn alloy. The extrusion trials were conducted using two die bearing geometries, (i) a zero bearing die and (ii) a choke die using an extrusion temperature of 480 °C and ram velocities of 20 to 30 mm/s. Axisymmetric extrusion was conducted with an extrusion ratio of 16.5. During the extrusion trials, partially extruded billets were extracted from the extrusion press and water quenched in order to follow the evolution of the surface microstructure for the different bearing geometries. In addition, ram motion was arrested in the middle of the extruded length, held for 5 seconds and then resumed to investigate the role of changing the deformation conditions of the surface on the extruded microstructure. Optical microscopy and electron back-scattered scanning diffraction (EBSD) were used to quantify the microstructure and crystallographic texture of the extrudates and partially extruded billets at different spatial locations. A finite element (FE) mathematical model using the commercial software package DEFORM 2D was also developed to simulate the extrusion process so that loads, temperatures, and material flow patterns could be predicted. The FE model was used to track material flow streamlines close to the surface. Specific locations along these streamlines were then selected for EBSD analysis on the partially extruded billets. The results indicate that the major factor affecting the formation of the PCG layer is the local stored energy of the near surface material which in turn is a function of the details of the die bearing geometry.

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)0.001
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.664

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.005
GPT teacher head0.202
Teacher spread0.197 · 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