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Record W2183958150

Hydraulic Characteristics of Fully Developed Flow in Circular Culverts

2009· dissertation· en· W2183958150 on OpenAlexfundaboutno aff
Nicholas Jon Kehler

Bibliographic record

VenueMspace (University of Manitoba) · 2009
Typedissertation
Languageen
FieldEngineering
TopicHydraulic flow and structures
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsCulvertFlow (mathematics)EngineeringMechanicsGeotechnical engineeringPhysics
DOInot available

Abstract

fetched live from OpenAlex

Throughout the world, particularly in countries such as Canada, water crossings are a significant part of the infrastructure system. Since corrugated metal pipe culverts are an inexpensive choice, as well as hydraulically efficient, they are a very appealing option to designers. To ensure that the natural ecosystem is not adversely affected, culverts must be designed so that throughout the year fish can migrate upstream. Current design regulations are based on the average velocity within the culvert and the prolonged swimming speed of the fish species present. In order to examine the validity of this approach, a physical modeling study was undertaken using a circular CMP culvert. It was found that there is significant cross sectional area below average velocity, and that gravel embedment further increases this area. In addition, a technique was developed that produced very agreeable streamwise velocity predictions over a two dimensional cross section in the developed region.

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 score0.011
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

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

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 head0.007
GPT teacher head0.180
Teacher spread0.173 · 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

Citations5
Published2009
Admission routes2
Has abstractyes

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