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Record W2726783680 · doi:10.1061/9780784480779.124

Numerical Simulation of 12 Years Long Biaxial Creep Tests: Efficiency of Assuming a Constant Poisson’s Ratio

2017· article· en· W2726783680 on OpenAlexaff
Laurent Charpin, T. O. Sow, X. D’Estève de Pradel, François P. Hamon, J.-P. Mathieu

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicConcrete Properties and Behavior
Canadian institutionsBombardier (Canada)
Fundersnot available
KeywordsCreepMaterials scienceShrinkageMechanicsStructural engineeringConstant (computer programming)Poisson distributionPhenomenological modelConsolidation (business)Composite materialComputer sciencePhysicsEngineeringMathematics

Abstract

fetched live from OpenAlex

For a part of the concrete containment buildings of French nuclear power plants, the leak-tightness depends vastly on the pre-stress of the building which can decrease due to concrete delayed strains. Therefore, EDF has developed a large experimental program in the early 2000 in order to study the biaxial creep of concrete. In this paper phenomenological drying, shrinkage and creep model is used to model these biaxial tests. The identification of the parameters of the drying model is first presented. Then, the parameters relative to a parasite mass-loss which occurred in the sealed tests and to the creep model are identified. The model is shown unable to reproduce correctly the biaxial strains observed in the tests. A change of the part of the model accounting for the desiccation creep is therefore proposed. Assuming that the desiccation creep Poisson’s ratio is identical to the basic creep and the elasticity ones allows for a better reproduction of long-term multiaxial concrete creep.

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)0.002
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: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.026
GPT teacher head0.265
Teacher spread0.239 · 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

Citations4
Published2017
Admission routes1
Has abstractyes

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Same topicConcrete Properties and BehaviorFrench-language works237,207