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Record W1780557940 · doi:10.1115/1.4031857

Viscoplastic Modeling of the Green Anode Paste Compaction Process

2015· article· en· W1780557940 on OpenAlexafffund
Hicham Chaouki, Donald Picard, Donald Ziegler, Kamran Azari, Houshang Alamdari, Mario Fafard

Bibliographic record

VenueJournal of Applied Mechanics · 2015
Typearticle
Languageen
FieldEngineering
TopicComposite Material Mechanics
Canadian institutionsUniversité LavalNatural Sciences and Engineering Research Council of Canada
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsConstitutive equationViscoplasticityMaterials scienceMechanicsCompressibilityCauchy elastic materialAnodeDeformation (meteorology)Nonlinear systemFinite element methodCompactionHelmholtz free energyPhysicsThermodynamicsComposite material

Abstract

fetched live from OpenAlex

The aim of this work is to simulate the forming process of green anodes. For this purpose, a nonlinear compressible viscoplastic constitutive law is presented. The concept of natural reference configuration is considered. Within an isothermal thermodynamic framework, a Helmholtz free energy is proposed to take into account the nonlinear compressible deformation process occurring between natural reference configuration and current configuration. A dissipation potential is introduced in order to characterize the irreversible aspect of compaction process. The constitutive law is thus formulated through two equations: (1) an expression of Cauchy stress tensor and (2) a differential equation characterizing the evolution of the natural reference configuration. Material parameters are assumed to be a function of the apparent green density. An experimental study is carried out in order to characterize the compaction behavior of the anode paste. A user's material VUMAT subroutine for finite-element dynamic explicit analysis has been developed and implemented in the abaqus commercial software. To evaluate the model predictive capability, numerical simulations of the compaction forming process of anode paste were performed. Simulation results show that the constitutive law predicts the experimental trends and gives insight of physical responses. This constitutes a first step toward characterizing the anode paste behavior and making a benchmark with experimental results on the forming process of anode paste.

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 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 score0.436
Threshold uncertainty score0.400

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.000

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 head0.018
GPT teacher head0.212
Teacher spread0.194 · 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 teacher head, 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

Citations9
Published2015
Admission routes2
Has abstractyes

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