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Record W4254517576 · doi:10.4171/176-1/34

Two-scale space-time methods for computational solid mechanics

2018· book-chapter· en· W4254517576 on OpenAlex
Patrice Hauret, Eric Lignon, Benoît Pouliot, Nicole Spillane

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEMS Press eBooks · 2018
Typebook-chapter
Languageen
FieldEngineering
TopicAdvanced Numerical Methods in Computational Mathematics
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsDiscretizationIntegratorDomain decomposition methodsComputer scienceScale (ratio)Reliability (semiconductor)Mathematical optimizationSpace (punctuation)AlgorithmMathematicsApplied mathematicsFinite element methodEngineeringMathematical analysisStructural engineering

Abstract

fetched live from OpenAlex

The efficient, robust and accurate assessment of structures in large deformation simultaneously requires: i) the resolution of micro-scale states to avoid the use of empirical material laws and assess reliability, ii) the availability of sufficiently light models to enable optimal structure design and uncertainty quantification. The present work contributes to the first objective by the use of variational integrators, a non-conforming space discretization in the sense of mortar methods and the design of optimal coarse grids to enhance traditional domain decomposition methods. The second issue is handled by an homogenized problem iteratively improved by accurate subgrid models in space and time. Several aspects of the method are analyzed and some examples are displayed as an illustration.

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.

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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.212
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 science0.0000.000
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 head0.051
GPT teacher head0.368
Teacher spread0.317 · 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