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Record W2322120881 · doi:10.1115/ipc2012-90556

Optimization of Valve Placement in Liquids Pipeline Systems

2012· article· en· W2322120881 on OpenAlexaff
Cameron Rout

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicWater Systems and Optimization
Canadian institutionsDynamic Systems Analysis (Canada)
Fundersnot available
KeywordsPipeline (software)Pipeline transportComputer scienceMinificationContainment (computer programming)Globe valveTimelineVolume (thermodynamics)Environmental scienceEngineeringMechanical engineering

Abstract

fetched live from OpenAlex

Many considerations go into the design of liquid pipelines relative to the placement of valves. Proper consideration of this issue must address not only minimization of capital costs, but the minimization of potential environmental and safety consequences. Critical to minimizing operating risks is the impact of valve placement on the potential outflow during a loss of containment event. In order to optimize the placement of valves in a pipeline, the effectiveness of each of many potential valve placement combinations must be measured by properties of the potential spill behaviour (i.e., average spill volume, peak spill volume, and HCA impacts). Factors affecting spill volume are topography, product properties, detection periods, valve closure timelines, and pump shut-down behaviour. This paper presents a solution to the challenge of optimizing valve placement in both interconnected and isolated systems through iterative generation of valve placement scenarios and hydraulic modeling. Various considerations that designers and operators should address are presented, along with results that are calibrated against real-world incidents.

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 score0.980
Threshold uncertainty score0.223

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 head0.010
GPT teacher head0.200
Teacher spread0.190 · 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

Citations2
Published2012
Admission routes1
Has abstractyes

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