MétaCan
Menu
Back to cohort
Record W3169851190 · doi:10.1061/9780784483466.045

CFD Simulation of Air–Water Interactions in Rapidly Filling Horizontal Pipe with Entrapped Air

2021· article· en· W3169851190 on OpenAlexaff
Biao Huang, Mengge Fan, Jiachun Liu, David Z. Zhu

Bibliographic record

VenueWorld Environmental and Water Resources Congress 2021 · 2021
Typearticle
Languageen
FieldEngineering
TopicWater Systems and Optimization
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMechanicsWater hammerComputational fluid dynamicsMixing (physics)Flow (mathematics)Volume of fluid methodPipe flowMaterials scienceSolverComputer simulationBreakupAirflowTransient (computer programming)Air waterGeotechnical engineeringGeologyTurbulenceMechanical engineeringEngineeringPhysicsComputer science

Abstract

fetched live from OpenAlex

One-dimensional mathematical models have been developed in order to predict pressure transients for pipes containing entrapped air undergoing rapid filling. A common hypothesis was adopted in these models, as there exists a distinct vertical air-water interface throughout the filling process. The limitation on the assumption becomes significant for pipes with large diameter, where the filling front undergoes notable deformation due to density difference and gravity effects. This study modeled air-water interactions in a horizontal pipe over rapid filling processes, by using the compressibleInterFoam solver of OpenFOAM. Both empty and partially filled pipe filling cases were simulated and compared with rigid-column models. Comprehensive analyses are presented, including detailed velocity profile, pressure distribution, temperature variation of entrapped air, and interface evolution. The results indicate that the transient water flow is analogous to water hammer flow and that the contribution of air-water mixing on the pressure oscillation damping is considerable. The findings are helpful to better understand the physics of the flow and to improve numerical models.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.742
Threshold uncertainty score0.633

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)0.0010.000

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 head0.005
GPT teacher head0.174
Teacher spread0.169 · 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

Citations8
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueWorld Environmental and Water Resources Congress 2021Same topicWater Systems and OptimizationFrench-language works237,207