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Record W4403872064 · doi:10.1061/jhend8.hyeng-14117

Prediction of Geyser Occurrences in Covered Manholes of Urban Stormwater Systems

2024· article· en· W4403872064 on OpenAlexaff
Yaohui Chen, Shangtuo Qian, Qian Yu, David Z. Zhu, Jiangang Feng, Hui Xu

Bibliographic record

VenueJournal of Hydraulic Engineering · 2024
Typearticle
Languageen
FieldEngineering
TopicSoil and Unsaturated Flow
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsStormwaterStormwater managementGeologyGeotechnical engineeringEnvironmental scienceHydrology (agriculture)Civil engineeringEngineeringSurface runoff

Abstract

fetched live from OpenAlex

Storm geysers are air–water eruptions from stormwater manholes during intense rainfalls, which raise public safety concerns. They arise from entrapped air release in stormwater tunnels as flow transitions from open to pressurized. This paper experimentally investigated air–water flow characteristics during air pocket release in covered manholes. Four geyser regimes were identified: no geyser, single air-release geyser, single rapid-filling geyser, and multigeysers. The air-release geyser and rapid-filling geyser refer to ejections of water column and air–water mixture induced by distinct mechanisms. Impacts of manhole diameter, cover ventilation area, system pressure head, and initial air pocket volume on geyser regimes were analyzed. As manhole diameter increases or cover ventilation area decreases, maximum geyser heights decrease, subsequently decreasing the likelihood of geyser occurrence. Higher system pressure head and larger initial air pocket volume increase the maximum geyser heights. Equations were derived to predict the maximum geyser heights, and prediction accuracies exceeded 87%, providing safe predictions of geyser occurrences relative to the manhole height. The findings can help provide advance warning of geysers when combined with information of stormwater system structures and real-time monitoring of operating conditions.

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 score0.018
Threshold uncertainty score0.400

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 head0.011
GPT teacher head0.191
Teacher spread0.180 · 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

Citations5
Published2024
Admission routes1
Has abstractyes

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