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Record W2018185662 · doi:10.1002/nag.774

Finite element formulation for poroelastic problem with zero effective stress boundary condition

2009· article· en· W2018185662 on OpenAlexaff
Bin Xu, R.C.K. Wong

Bibliographic record

VenueInternational Journal for Numerical and Analytical Methods in Geomechanics · 2009
Typearticle
Languageen
FieldEngineering
TopicNumerical methods in engineering
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsPoromechanicsConvergence (economics)BoreholeNonlinear systemFinite element methodBoundary value problemStress (linguistics)Boundary (topology)Stability (learning theory)Hydraulic fracturingNumerical analysisComputer simulationApplied mathematicsGeologyComputer scienceMechanicsMathematicsGeotechnical engineeringEngineeringMathematical analysisStructural engineeringPorous mediumPorosityPhysics

Abstract

fetched live from OpenAlex

Abstract Zero effective stress boundary condition along with constant fluid flux is commonly encountered in geotechnical applications such as uncased borehole stability, fluid injection and production at an uncased borehole, hydraulic fracturing and sand production. This complex boundary condition introduces high nonlinearity in the numerical simulation. Conventional iterative methods such as Newton–Raphson method are required to solve this nonlinear problem iteratively, which involve huge computing time and also pose numerical difficulties on the convergence. To overcome this numerical difficulty and hence reduce the computing time, a novel numerical technique is proposed in this paper. Its performance is evaluated using a numerical example simulating fluid injection around an uncased borehole. Copyright © 2009 John Wiley & Sons, Ltd.

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 score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0030.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.014
GPT teacher head0.349
Teacher spread0.334 · 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

Citations3
Published2009
Admission routes1
Has abstractyes

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