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Record W4402501790 · doi:10.11159/icceia24.110

Effect of Distance on Hydraulic Efficiencies of Successively Located Grate Inlets

2024· article· en· W4402501790 on OpenAlexvenueno aff
Cumhur Ozbey

Bibliographic record

VenueProceedings of the World Congress on New Technologies · 2024
Typearticle
Languageen
FieldEngineering
TopicHydraulic and Pneumatic Systems
Canadian institutionsnot available
Fundersnot available
KeywordsInletEnvironmental scienceMarine engineeringPetroleum engineeringMechanicsGeologyEngineeringPhysicsGeomorphology

Abstract

fetched live from OpenAlex

Laboratory experiments were conducted at a recirculating rectangular channel of 12 m long and 0.9 m wide with a longitudinal slope of 1/300.Accordingly, two-grated inlet systems were tested under varying approach flow rates, and the corresponding capturing efficiencies were determined.To do so, two cases were considered where the side grates were successively positioned on the main channel with a distance of 0.2 m and 0.4 m, respectively.The ranges of total flow rate and Froude number were 0.33 < 𝐹𝐹𝐹𝐹 < 0.52 and 1 𝐿𝐿/𝑠𝑠 < 𝑄𝑄 𝑡𝑡 < 5.2 𝐿𝐿/𝑠𝑠, respectively.The results revealed that the hydraulic performance of a two-grated inlet system is strongly linked to the longitudinal distance between the grates and it was observed that positioning the grate inlets at a lesser distance was hydraulically more efficient in capturing the total approach flow rate.Moreover, the experimental results have also shown that the total hydraulic efficiency of successively located grate inlets displayed an increased tendency for higher values of upcoming flow rates.

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)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.007
GPT teacher head0.228
Teacher spread0.221 · 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 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
Published2024
Admission routes1
Has abstractno

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