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Record W4415569209 · doi:10.3390/w17213059

Assessing the Hydraulic Parameters of an Open Channel Spillway Through Numerical and Experimental Approaches

2025· article· en· W4415569209 on OpenAlexafffundabout
Elaheh Motahari Moghadam, Ali Saeidi, Javier Patarroyo, Alain Rouleau, Meghdad Payan

Bibliographic record

VenueWater · 2025
Typearticle
Languageen
FieldEngineering
TopicHydraulic flow and structures
Canadian institutionsHydro-QuébecUniversité du Québec à Chicoutimi
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSpillwayTurbulenceOpen-channel flowFlow (mathematics)Channel (broadcasting)Computer simulationReduction (mathematics)Sensitivity (control systems)Hydraulic jump

Abstract

fetched live from OpenAlex

The effective design and operation of hydraulic structures, particularly open channel spillways, are crucial for water resource management and flood risk reduction in dams. A clear understanding of flow properties, such as velocity fluctuations and discharge, across various depths is essential for optimizing performance. In this study, experimental analysis and numerical simulation using FLOW-3D were combined to investigate the hydraulic parameters of a scaled model of the Romaine IV spillway located in Quebec, Canada. Measurements focused on flow properties, including velocity fluctuations at various discharge rates in specific flow depths, at selected points along the spillway. The numerical model was assessed by reproducing experimental geometry, initial water levels, and boundary conditions, and through sensitivity analyses to ensure accurate flow representation. Comparisons of flow rates of 180, 240, and 340 L/s showed that while simulations with the renormalized group (RNG) turbulence model reliably predicted average velocities, they underestimated maximum values and overestimated minimum values, especially at higher discharges. The results highlight the difficulty of accurately capturing velocity extremes in turbulent flows and the need for further model refinement. This was evident from the 60% discrepancy in minimum velocities observed at the channel center. Despite these discrepancies, the study advances our understanding of spillway performance and identifies avenues to improve the accuracy of numerical modeling in hydraulic engineering.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.463
Threshold uncertainty score0.233

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 head0.041
GPT teacher head0.289
Teacher spread0.248 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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
Published2025
Admission routes3
Has abstractyes

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