MétaCan
Menu
Back to cohort
Record W3127674974 · doi:10.3390/ma14040704

Compaction of Cohesive Granular Material: Application to Carbon Paste

2021· article· en· W3127674974 on OpenAlexafffund
Zahraa Kansoun, Hicham Chaouki, Donald Picard, Julien Lauzon‐Gauthier, Houshang Alamdari, Mario Fafard

Bibliographic record

VenueMaterials · 2021
Typearticle
Languageen
FieldEngineering
TopicGranular flow and fluidized beds
Canadian institutionsAlcoa (Canada)Université LavalNatural Sciences and Engineering Research Council of Canada
FundersNatural Sciences and Engineering Research Council of CanadaFonds de recherche du Québec – Nature et technologiesUniversité LavalAlcoa
KeywordsMaterials scienceCompactionRheologyComposite materialCompressibilitySofteningStrain hardening exponentCarbon fibersForming processesMechanicsComposite number

Abstract

fetched live from OpenAlex

Carbon-like materials such as the anode and the ramming paste play a crucial role in the efficiency of the Hall-Héroult process. The mechanical behavior of these materials during forming processes is complex and still ill-understood. This work aimed to investigate experimentally the mechanical behavior of a carbon paste used in the aluminum industry under different loading conditions. For this purpose, experiments consisting of (1) relaxation tests at different compaction levels, (2) quasi-static cyclic tests at several amplitudes, (3) monotonic compaction tests at varied strain rates, and (4) vibrocompaction tests at different frequencies were carried out. The obtained results highlight some fundamental aspects of the carbon paste behavior such as the strain rate's effect on the paste compressibility, the hardening-softening behavior under cyclic loadings, the effect of cycling amplitude on the stress state and the paste densification, and the frequency effect on the vibrocompaction process. These results pave the way for the development of reliable rheological models for the modeling and the numerical simulation of carbon pastes forming processes.

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 score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.006
GPT teacher head0.201
Teacher spread0.195 · 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

Citations4
Published2021
Admission routes2
Has abstractyes

Explore more

Same venueMaterialsSame topicGranular flow and fluidized bedsFrench-language works237,207