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Record W2094458393 · doi:10.1080/02626667.2014.959447

Practical finite analytic methods for simulation of advection-dominated solute transport

2014· article· en· W2094458393 on OpenAlexaff
Mohammad Salman Sabahi, Hanif Montazeri, Mojtaba Ardestani, Brent E. Sleep

Bibliographic record

VenueHydrological Sciences Journal · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicGroundwater flow and contamination studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsAdvectionCourant–Friedrichs–Lewy conditionPéclet numberConvection–diffusion equationMechanicsUpwind schemeStability (learning theory)MathematicsCauchy distributionQuadratic equationBoundary value problemApplied mathematicsMathematical analysisPhysicsComputer scienceGeometryThermodynamics

Abstract

fetched live from OpenAlex

The practical finite-analytic (PFA) method was applied to the solution of the one-dimensional advection–dispersion equation (ADE) for solute transport in porous media under advection-dominated (high Peclet number, Pe) conditions. Several PFA spatial-temporal computational molecules were developed for Cauchy and pulse loading boundary conditions. The PFA solutions were compared with solutions from the upwind method and quadratic upwind differencing (QUICK) scheme. For all boundary conditions the trapezoidal explicit PFA (EPFA) computational molecule gave the most accurate results at very high Pe number as long as the Courant number (Cr) was close to one. Stability analysis shows that the PFA molecules are always stable for high Pe number.

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: Methods · Consensus signal: Methods
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.057
GPT teacher head0.374
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

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
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

Citations2
Published2014
Admission routes1
Has abstractyes

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