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Record W2183498584

Pressure Predictions and Run-Up on a Vertical Wall and Slop-

2014· article· en· W2183498584 on OpenAlexaboutno aff
Caroline S ́ Evigny

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCoastal and Marine Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsFlumeWave flumeClimbGeologyGeotechnical engineeringFull scaleScale modelScale (ratio)Span (engineering)MechanicsMarine engineeringEngineeringFlow (mathematics)Structural engineeringBreaking wavePhysicsWave propagation
DOInot available

Abstract

fetched live from OpenAlex

E, INRS-ETE, University of Quebec, Canada — This paper presents large scale experiments of water wave impact on wall. This study is concerned with advancing knowledge on rapidly varying pressure magnitude and distributions on different types of sea/river/harbor walls. The experiments are conducted in the new Quebec Coastal Physics Laboratory (QCPL), Canada. The flume has a depth and a width of 5 m and is 120 m long. It is designed for modeling the interactions of waves, currents and sediment transport. The wall has a test area of 1.2 2.4 m. The outer regions of the wall are made of steel to span the entire width of the tank. The wall is designed to behave as a rigid plate. The geometric model to full scale is about 1:4. Sensors are mounted along the flume, beach slope and wall to monitor hydrodynamics parameters. The incoming waves evolve over a flat bed to climb the final 25 m on a beach with a constant slope of 1:10. Broad- and narrow-banded spectra representing operational and storm events were investigated. The initial results are promising. Details of the underlying mechanism of various types of breaking and impact on the wall will be presented.

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)0.000
metaresearch head score (Gemma)0.001
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: Empirical
Teacher disagreement score0.284
Threshold uncertainty score0.565

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.006
GPT teacher head0.176
Teacher spread0.171 · 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

Citations0
Published2014
Admission routes1
Has abstractyes

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Same topicCoastal and Marine DynamicsFrench-language works237,207