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Record W2077109823 · doi:10.1002/cjce.5450790105

Transient analysis of gas flow in a straight pipe

2001· article· en· W2077109823 on OpenAlexvenueno aff
Anindya Hati, Nishith Verma, R.P. Chhabra

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2001
Typearticle
Languageen
FieldEngineering
TopicWater Systems and Optimization
Canadian institutionsnot available
Fundersnot available
KeywordsMechanicsPressure dropVolumetric flow ratePipe flowFlow coefficientFlow (mathematics)Transient (computer programming)Mass flow rateWork (physics)Steady state (chemistry)Transient flowPipeline transportMaterials scienceThermodynamicsSurgeChemistryPhysicsEngineeringMechanical engineeringMeteorologyTurbulenceComputer science

Abstract

fetched live from OpenAlex

Abstract In the present work, numerical simulation has been done to analyze transients in gas flow and pressure in a horizontal straight pipe. For a single gas pipeline, eight representative cases corresponding to different causes of transient behaviour are simulated to predict unsteady state flow and the evolution of pressure profiles. The numerical results show that depending upon the pipe dimensions and operating variables such as pressure and gas flow rate, transient effects in the pipeline may last for a long time and/or over significant length of pipe. The simulations predict an initial surge in gas flow rate greater than the final steady‐state value if the pressure drop across the pipe is increased. Similarly, initial flow rate may decrease below the final steady‐state value if the pressure drop is decreased. In case of complete closure of a valve, oscillations in both pressure and mass flow rate are observed, which gradually decay and the steady state conditions of no flow are ultimately achieved. The present results are compared with a published work from the literature. A reasonably good agreement is found between these two predictions. The present study is of practical significance in safe design and operation of a gas delivery system.

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 score0.373

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.005
GPT teacher head0.155
Teacher spread0.150 · 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
Published2001
Admission routes1
Has abstractyes

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