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Record W2099068810 · doi:10.3934/nhm.2011.6.401

An adaptive finite-volume method for a model of two-phase pedestrian flow

2011· article· en· W2099068810 on OpenAlexaff
Stefan Berres, Ricardo Ruíz-Baier, Hartmut Schwandt, Elmer M. Tory

Bibliographic record

VenueNetworks and Heterogeneous Media · 2011
Typearticle
Languageen
FieldEngineering
TopicEvacuation and Crowd Dynamics
Canadian institutionsMount Allison University
FundersDeutsche Forschungsgemeinschaft
KeywordsFinite volume methodDegenerate energy levelsFlow (mathematics)Mathematical analysisPhase spaceSpace (punctuation)DiffusionStability (learning theory)MathematicsCountercurrent exchangeDimension (graph theory)Applied mathematicsMechanicsPhysicsGeometryComputer science

Abstract

fetched live from OpenAlex

A flow composed of two populations of pedestrians moving in different directions is modeled by a two-dimen\-sional system ofconvection-diffusion equations. An efficient simulation of the two-dimensional model is obtained by a finite-volume scheme combinedwith a fully adaptive multiresolution strategy. Numerical tests showthe flow behavior in various settings of initial and boundaryconditions, where different species move in countercurrent orperpendicular directions.The equations are characterized ashyperbolic-elliptic degenerate, with an elliptic region in the phase space, which in one space dimension is known to produce oscillation waves.When the initial data are chosen inside the elliptic region,a spatial segregation of the populations leads to pattern formation.The entries of the diffusion-matrix determine the stability of the model and the shape of the patterns.

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 score0.013
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.001
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 head0.045
GPT teacher head0.286
Teacher spread0.240 · 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

Citations25
Published2011
Admission routes1
Has abstractyes

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