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Record W1833701724 · doi:10.1139/p2012-057

Hot isostatic pressing process simulation: application to metal powders

2012· article· en· W1833701724 on OpenAlexvenueno aff
Locif Redouani, Samir Boudrahem

Bibliographic record

VenueCanadian Journal of Physics · 2012
Typearticle
Languageen
FieldEngineering
TopicPowder Metallurgy Techniques and Materials
Canadian institutionsnot available
Fundersnot available
KeywordsHot isostatic pressingWork (physics)PhysicsPressingTungstenDeformation (meteorology)MechanicsProcess (computing)MetallurgyMechanical engineeringThermodynamicsComposite materialAlloyMaterials scienceComputer science

Abstract

fetched live from OpenAlex

Deformation and transport mechanisms of matter, which intervene in the powder densification process by hot isostatic pressing (HIP), are very complicated to put into equation form. Their contribution to densification depends on powder characteristics, their configuration in aggregates, and the used HIP cycle parameters (temperature, pressure, and time). In this work, we have envisaged modifications that seemed to us necessary to bring to the previous simulations, so that their predictions will be related to experiment. New equations were established to evaluate the efficient pressure and the contributions of different mechanisms. The obtained results are used for the construction of densification diagrams by the HIP of copper, nickel, and tungsten powders and to the comparison with the experimental data. The comparative tables, between theoretical results and experimental data, were established for tin and lead. The simulation predictions are in good agreement with experimental results.

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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.017
GPT teacher head0.261
Teacher spread0.244 · 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
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

Citations11
Published2012
Admission routes1
Has abstractyes

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