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Flow Observations in Tall Plunging Flow Dropshafts

2014· article· en· W2038846101 on OpenAlexaff
G. Adriana Camino, David Z. Zhu, N. Rajaratnam

Bibliographic record

VenueJournal of Hydraulic Engineering · 2014
Typearticle
Languageen
FieldEngineering
TopicHydraulic flow and structures
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMechanicsFlow (mathematics)Flow conditionsEnvironmental scienceAirflowDissipationOpen-channel flowDrop (telecommunication)MeteorologyFlow measurementGeologyEngineeringPhysicsThermodynamicsMechanical engineering

Abstract

fetched live from OpenAlex

Plunging flow dropshafts are commonly used in municipal drainage systems. In this Note, an exploratory study is reported on the physics of the flow and air demand in two dropshafts of 7.7 and 6.3 m drop height. The flow inside these dropshafts was controlled by the upstream conditions with no outlet control. The water flow distribution and flow velocities in the vertically falling section are presented, and the energy dissipation in plunge flow drop structures is analyzed. The air demand was measured, and an empirical relation is proposed to predict the air demand in these tall dropshafts.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.006
GPT teacher head0.181
Teacher spread0.176 · 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 designObservational
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

Citations51
Published2014
Admission routes1
Has abstractyes

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