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Record W2885506274 · doi:10.1016/j.dib.2018.07.066

Extensional rheological data from ex-situ measurements for predicting porous media behaviour of the viscoelastic EOR polymers

2018· article· en· W2885506274 on OpenAlex
Madhar Sahib Azad, Japan Trivedi

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueData in Brief · 2018
Typearticle
Languageen
FieldChemical Engineering
TopicRheology and Fluid Dynamics Studies
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaCanada Foundation for InnovationCanada First Research Excellence FundUniversity of Alberta
KeywordsViscoelasticityRheologyRheometerExtensional viscosityMaterials scienceBreakupExtensional definitionPolymerStrain hardening exponentExtrusionPorous mediumViscosityConstitutive equationComposite materialPorosityMechanicsThermodynamicsPhysicsGeologyFinite element methodShear viscosity

Abstract

fetched live from OpenAlex

In this article, extensional rheological data of various polymer solutions, to be used in Azad Trivedi viscoelastic model (AT-VEM) for predicting the viscoelastic behavior of synthetic polymer in porous media are provided. Extensional rheology measurements are performed for different polymer solutions using Capillary breakup extensional Rheometer (CaBER) to obtain the filament diameter with respect to time. Extensional rheological parameters, such as the extensional relaxation time, maximum elongational viscosity at the critical Deborah number and strain hardening index are determined from observed filament diameter with time-based on the Upper Convected Maxwell model, the finite extensible non-linear elastic model, and the power law model.

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)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.447
Threshold uncertainty score0.441

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.003
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 science0.0020.002
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 head0.081
GPT teacher head0.294
Teacher spread0.213 · 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