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Record W2153346296 · doi:10.1002/rra.2868

Drag Forces on Large Cylinders

2015· article· en· W2153346296 on OpenAlexaff
Benoit Turcotte, Robert G. Millar, Marwan A. Hassan

Bibliographic record

VenueRiver Research and Applications · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicHydrology and Sediment Transport Processes
Canadian institutionsUniversity of British ColumbiaGolder Associates (Canada)Université Laval
Fundersnot available
KeywordsDragDrag coefficientMechanicsDimensionless quantityCylinderFlow (mathematics)Parasitic dragGeologyGeotechnical engineeringContext (archaeology)Debris flowSurface finishHydraulic roughnessDebrisGeometryPhysicsMathematicsEngineeringMechanical engineering

Abstract

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Abstract Introducing large woody debris into streams is a common practice in restoration projects. Beyond the complexity of flow patterns and sediment movements in streams where woody debris are found or placed, it seems that our understanding of the basic hydraulics of large roughness elements in small channels remains limited. Underestimating the drag force affecting large roughness elements can compromise the success of stream restoration projects. Results from a simple experimental setting confirm that drag force estimates based on approaches developed for small cylinders are not valid when applied to large cylinders. Indeed, the classic drag force equation that uses an empirical drag coefficient is found to significantly underestimate measured drag forces, even when corrected for the ‘blockage ratio’. In contrast, application of specific momentum can yield good estimates of the drag force. A dimensionless depth is defined in a 1D context as a function of the flow depth, critical flow depth and cylinder diameter. A cylinder is considered to be ‘large’ when this dimensionless depth is smaller than 2. In this instance, a relationship is established to estimate the upstream flow depth and the drag force acting on the cylinder. This research bridges the small roughness element theory widely recognized in hydraulic engineering with the theory applicable to large, flow controlling structures such as weirs. From a practical perspective, this research can be used to assist in the design of engineered large woody debris structures. Copyright © 2015 John Wiley & Sons, Ltd.

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 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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.826
Threshold uncertainty score1.000

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)0.0000.001

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 head0.064
GPT teacher head0.347
Teacher spread0.282 · 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 teacher head, not a consensus.

Study designNot applicable
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

Citations10
Published2015
Admission routes1
Has abstractyes

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