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Record W4309751383 · doi:10.1061/jhend8.hyeng-13197

Calculating Column Separation in Conduit Systems Using an Innovative Open Channel Based Model

2022· article· en· W4309751383 on OpenAlexaff
David Khani, Yeo Howe Lim, Ahmad Malekpour

Bibliographic record

VenueJournal of Hydraulic Engineering · 2022
Typearticle
Languageen
FieldEngineering
TopicWater Systems and Optimization
Canadian institutionsThornhill Medical (Canada)
Fundersnot available
KeywordsOpen-channel flowFinite volume methodMechanicsFlow (mathematics)Riemann solverCavitationShock (circulatory)SolverChannel (broadcasting)Riemann problemEuler equationsMathematicsApplied mathematicsComputer sciencePhysicsMathematical optimizationMathematical analysisRiemann hypothesis

Abstract

fetched live from OpenAlex

An innovative numerical model called the Modified Two-Component Pressure Approach (MTPA) is proposed to better capture the physics of column separation in conduit systems. Based on the Two-Component Pressure Approach (TPA), the MTPA calculates both cavitating and pressurized flow using a single set of equations that governs unsteady flow in open channel flow. As opposed to shock-fitting-based models, in which a complex algorithm is needed to keep track of the interfaces separating the cavitating and liquid zones, the proposed model can capture both flow phases automatically. The first-order Godunov type finite volume method is utilized to numerically solve the equations. A customized Harten, Lax and Van Leer (HLL) Riemann solver is employed to calculate the fluxes at the computational cell boundaries and to dissipate potential post-shock oscillations generated when the cavity is collapsed and the open channel flow beneath the cavity is switched back to pressurized flow. The numerical results are shown to be in good agreement with both experimental data and the results obtained from the Discrete Gas Cavity Model (DGCM). A hypothetical test case is also presented to demonstrate the unique feature of the proposed model, which is the ability to simultaneously account for waterhammer, cavitation, and open channel flow regimes, a feature making the model even superior to the DGCM.

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)0.001
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: none
Teacher disagreement score0.548
Threshold uncertainty score0.652

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.041
GPT teacher head0.272
Teacher spread0.231 · 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

Citations3
Published2022
Admission routes1
Has abstractyes

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