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Direct Solutions for Uniform Flow Parameters of Wide Rectangular and Triangular Sections

2021· article· en· W3160483102 on OpenAlex

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

VenueJournal of Irrigation and Drainage Engineering · 2021
Typearticle
Languageen
FieldEngineering
TopicHydraulic flow and structures
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsComputationHead (geology)Hydraulic headOpen-channel flowFlow (mathematics)GeometryChannel (broadcasting)Series (stratigraphy)Section (typography)Power seriesPotential flowMathematicsMechanicsSurface (topology)Mathematical analysisComputer scienceAlgorithmGeologyTelecommunicationsPhysicsGeotechnical engineering

Abstract

fetched live from OpenAlex

One of the general problems encountered in the design of open channels is the computation of normal depth, head loss, and discharge. A wide rectangular section is commonly used in natural streams and surface/sheet flow in watersheds and the triangular section is commonly used for irrigation and roadside channels. The normal depth or head loss is traditionally solved using a trial (iterative) procedure. This paper develops two direct solutions for the head loss and normal depth for the wide rectangular and triangular open channel sections. The explicit equations for the normal depths are developed in terms of fast converging power series. The maximum errors of the proposed explicit formulas are 0.65% and 2% for triangular and wide rectangular channels, respectively, compared with 5% and 8% for the existing methods.

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: none
Teacher disagreement score0.549
Threshold uncertainty score0.354

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 head0.009
GPT teacher head0.197
Teacher spread0.189 · 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