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Shock-Fitting Approach for Calculating Air Pocket Entrapment Caused by Full Obstruction in Closed Conduit Transient Flow

2020· article· en· W3085576007 on OpenAlexaff
Arman Rokhzadi, Musandji Fuamba

Bibliographic record

VenueJournal of Hydraulic Engineering · 2020
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics Simulations and Interactions
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsMechanicsDiscontinuity (linguistics)Flow (mathematics)Transient (computer programming)Shock (circulatory)Euler equationsFree surfaceGeologyMathematicsPhysicsMathematical analysisComputer science

Abstract

fetched live from OpenAlex

ABSTRACT: This paper studies the ability of a Shock-Fitting approach in computing air pocket entrapments in a closed conduit transient flow, caused by suddenly blocking the downstream end. The flow is pressurized at the upstream, which detaches from the wall somewhere at the downstream after which a free surface flow develops. In this Shock-Fitting approach a pressurized flow is simulated by the rigid column model and the free surface flow is simulated by the Saint-Venant equations set. A transient region, which is characterized by the speed of the discontinuity, links these two flow regimes. The relevant governing equations of the rigid column model and the transient region are solved using the backward Euler temporal scheme and the Saint-Venant equations set is solved using the method of characteristics. It was found that this Shock-Fitting approach is able to predict the attenuation behavior as well as to calculate the flow variables more efficiently than the rigid column model and the modified Saint-Venant equations. By means of a linear stability analysis, it was shown that these improvements are provided by the speed of discontinuity in the transient region and the pressurized water column length.

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: none
Teacher disagreement score0.612
Threshold uncertainty score0.849

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 head0.212
Teacher spread0.201 · 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

Citations6
Published2020
Admission routes1
Has abstractyes

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