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Record W3200513939 · doi:10.32393/csme.2021.143

Realistic Representative Volume Element Generation For Sintered Solids Part 1: Algorithm For Volume Computation And Geometry Creation

2021· article· en· W3200513939 on OpenAlexaff
Frank D. Thomas, Ahmed Elruby, Sam Nakhla

Bibliographic record

VenueProgress in Canadian Mechanical Engineering. Volume 4 · 2021
Typearticle
Languageen
FieldEngineering
TopicAdditive Manufacturing and 3D Printing Technologies
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsVolume (thermodynamics)ComputationComputational geometryGeometryComputer scienceElement (criminal law)Finite element methodComputational scienceAlgorithmMathematicsEngineeringStructural engineeringPhysicsThermodynamics

Abstract

fetched live from OpenAlex

The following work presents an algorithm for the generation of geometric models which function as realistic and accurate portrayals of powder-based porous sintered solids in both form and function.The code base was developed in Python for use in ABAQUS finite element software.The development of key modules such as the smart compaction, particle settling, and rapid volume computation processes are described in detail.Geometric models were evaluated for accuracy, computational efficiency, and physical characteristics at various porosities.Part 2 of this work investigates the finite element analysis results of these models compared to experimental data.

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)0.001
metaresearch head score (Gemma)0.002
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: none
Teacher disagreement score0.011
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0110.003

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 head0.020
GPT teacher head0.263
Teacher spread0.243 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

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Same venueProgress in Canadian Mechanical Engineering. Volume 4Same topicAdditive Manufacturing and 3D Printing TechnologiesFrench-language works237,207