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Record W168843121 · doi:10.1007/0-306-47015-2_53

Parallel Finite Element Simulation of 3D Mold-Filling Problems

2005· book-chapter· en· W168843121 on OpenAlexaff
Martin Audet, Jean‐François Hétu, Florin Ilincahetu, Randall Bramley

Bibliographic record

VenueKluwer Academic Publishers eBooks · 2005
Typebook-chapter
Languageen
FieldEngineering
TopicAdvanced Numerical Methods in Computational Mathematics
Canadian institutionsNational Research Council Canada
FundersNational Science Foundation
KeywordsPreconditionerSolverParallel computingBiconjugate gradient stabilized methodComputer scienceComputational scienceFinite element methodHexahedronLinear systemCompilerSimple (philosophy)AlgorithmMathematicsIterative methodEngineeringProgramming languageStructural engineering

Abstract

fetched live from OpenAlex

This paper presents a distributed memory parallel implementation of a three dimensional stabilized finite element solver for industrial mold-filling problems using the MPI standard library. These problems present unusual challenges for both the physical modeling and parallelization. Numerical methods and algorithms are proposed for parallel system generation, assembly and linear system solve. Results show that the stabilized formulation is accurate, efficient and leads to linear systems that can be solved very efficiently using simple BiCGStab solver with local ILU(0) preconditioner. Results also show that the proposed approach and data structure are reasonably efficient up to 16 CPUs.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.365
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.002
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 head0.048
GPT teacher head0.295
Teacher spread0.247 · 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.

Study designSimulation or modeling
Domainnot available
GenreMethods

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
Published2005
Admission routes1
Has abstractyes

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