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Record W4393210089 · doi:10.1061/jhend8.hyeng-13746

Flow in Sewers with Bottom Obstacles

2024· article· en· W4393210089 on OpenAlexaff
Zhi Yang, Biao Huang, David Z. Zhu

Bibliographic record

VenueJournal of Hydraulic Engineering · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicHydrology and Sediment Transport Processes
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsSanitary sewerFlow (mathematics)Hydrology (agriculture)Environmental scienceGeologyGeotechnical engineeringMechanicsEnvironmental engineeringPhysics

Abstract

fetched live from OpenAlex

This study conducted experiments to investigate the impact of bottom obstacles, specifically broad-crest weir-type and cylindrical obstacles, on the flow within a sewer pipe. It was observed that these two types of obstacles, when possessing the same cross-sectional area and length, exhibited nearly equivalent hydraulic responses for both supercritical and subcritical flows. The obstacle height was found to be the primary factor responsible for choking and the transition between different flow regimes. The results of the one-dimensional analysis show that the threshold value of obstacle height depends on the approaching flow conditions, including the Froude number and the filling ratio that is defined as the flow depth to the pipe diameter. In the context of a partially blocked sewer, the relationships established by using the one-dimensional model between the size of the bottom obstacle and the inflow characteristics enable the identification of flow regimes, assessment of reduced hydraulic capacity, and evaluation of local energy loss. The findings of this study elucidate the hydraulic behavior of obstructed sewers, contributing to the development of more effective strategies for the identification of obstructions through monitoring data.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.291
Threshold uncertainty score0.366

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 head0.004
GPT teacher head0.187
Teacher spread0.183 · 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 designSimulation or modeling
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

Citations4
Published2024
Admission routes1
Has abstractyes

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