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Record W2072630954 · doi:10.1680/eacm.2009.162.2.57

Simulation of wave fronts on dry beds using Lagrangian blocks

2009· article· en· W2072630954 on OpenAlex
Lai Wai Tan, Vincent H. Chu

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.

Bibliographic record

VenueProceedings of the Institution of Civil Engineers - Engineering and Computational Mechanics · 2009
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics Simulations and Interactions
Canadian institutionsMcGill University
Fundersnot available
KeywordsOutflowFront (military)Sump (aquarium)MechanicsOscillation (cell signaling)GeologyEnhanced Data Rates for GSM EvolutionSawtooth waveOblique caseLagrangianPhysicsEngineering

Abstract

fetched live from OpenAlex

Simulations of wave fronts on a dry bed are conducted using blocks as the computational elements. The non-negativity of the blocks allows simulations of the wave fronts to be carried out without the oscillation problem that limits the applicability of many existing computational methods. At the leading edge of the advancing front, the velocity is maximum and friction dominates. Simulations of this dominant friction effect at the wave front are carried out for the release of water from a dam-break outflow, a levee overflow and a sump outflow. Despite geometric differences, the frontal dynamics of all three flows are similarly affected by friction.

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)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.442
Threshold uncertainty score0.584

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0000.000
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 head0.010
GPT teacher head0.208
Teacher spread0.199 · 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