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Record W2899686404 · doi:10.1016/j.crme.2018.10.001

A model for the aerodynamic coefficients of rock-like debris

2018· article· fr· W2899686404 on OpenAlexfundno aff
Vincent Chai, Dushyant Parkhi, Sethu Raman Boopathy, Junting Xiang, Jörg Schlüter

Bibliographic record

VenueComptes Rendus Mécanique · 2018
Typearticle
Languagefr
FieldEnvironmental Science
TopicLandslides and related hazards
Canadian institutionsnot available
FundersDefence Science and Technology Agency - SingaporePetroleum Technology Research Centre
KeywordsAerodynamicsDebrisWind tunnelAerodynamic forceGeotechnical engineeringObject (grammar)GeologyMagnitude (astronomy)Aerospace engineeringMarine engineeringStructural engineeringEngineeringComputer scienceEnvironmental scienceArtificial intelligencePhysics

Abstract

fetched live from OpenAlex

This study presents a model to determine the aerodynamic forces on an irregularly shaped object for prediction of trajectories of debris. We classify the debris according to shape and use wind tunnel tests to create a database of aerodynamic forces of similarly sized objects. We have then validated the database results against wind tunnel measurements of aerodynamic coefficients of rock-like debris objects. Although the individual errors may be significant, the results show a generally good agreement with our model prediction and a small average error.

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: Methods · Consensus signal: Methods
Teacher disagreement score0.011
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.020
GPT teacher head0.252
Teacher spread0.232 · 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

Citations7
Published2018
Admission routes1
Has abstractyes

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