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Hydraulics of Stacked Drop Manholes

2011· article· en· W1966930152 on OpenAlexaff
G. Adriana Camino, David Z. Zhu, N. Rajaratnam

Bibliographic record

VenueJournal of Irrigation and Drainage Engineering · 2011
Typearticle
Languageen
FieldEngineering
TopicWater Systems and Optimization
Canadian institutionsUniversity of Alberta
FundersU.S. Army Corps of Engineers
KeywordsInflowOutflowHydraulicsMechanicsDrop (telecommunication)Flow (mathematics)Momentum (technical analysis)GeologyGeotechnical engineeringPlane (geometry)Environmental scienceGeometryEngineeringPhysicsMechanical engineeringMathematicsThermodynamics

Abstract

fetched live from OpenAlex

This paper presents the results of an experimental investigation on flows inside stacked drop manholes (SDM). An SDM consists of two identical rectangular or square manhole chambers stacked together at an elevation difference. SDMs for different conditions were assessed on their ability to dissipate the energy of the approaching flow and their suitability to perform adequately under different flow conditions. Flow regimes were classified based on the inflow conditions and geometry of the structure in the first chamber and downstream outflows in the second chamber. An analysis based on the integral momentum equation was developed to estimate pool depths and energy losses under critical flow conditions. A fully surcharged stage with inflow and outflow pipes running full was also tested and velocity profiles were measured at a horizontal center plane to the opening connecting both shafts. Additionally, air flow rates were measured to assess the air demand into a large-height SDM.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
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 head0.010
GPT teacher head0.155
Teacher spread0.145 · 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

Citations21
Published2011
Admission routes1
Has abstractyes

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