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Record W6947535791 · doi:10.48336/77a2-3f91

Investigation of pressure and temperature gradient in four-phase flow in a complex horizontal pipeline

2022· article· en· W6947535791 on OpenAlexaff

Bibliographic record

VenueMemorial University Research Repository (Memorial University) · 2022
Typearticle
Languageen
FieldComputer Science
TopicResearch Data Management Practices
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsPipeline (software)Flow (mathematics)Submarine pipelinePipeline transportPressure gradientWork (physics)Flow assuranceFlow conditionsTemperature gradient

Abstract

fetched live from OpenAlex

The oil and gas (O&G) industry uses multi-phase and multi-component pipeline flows to move product from one site to another or to different areas within the same site. In extreme environments, such as offshore or the Arctic, the development of four-phase flows in a complex pipeline can bring even more challenges to the project. Jumpers and bends need to be able to is to withstand pressure drops and hydrodynamic loads from internal multi-phase flows and the current, respectively. The study outlines the development of an experiment to investigate of pressure and temperature gradients in four-phase flows in a complex pipeline. Due to the excessive temperatures and pressures of the oil transport pipeline system, the main pipes include shorter pipes (bends and jumpers) that are attached to the manifold at the pipeline. These shorter pipes are used to enable expandability and prevent system failure. The present work examines the practicality of applying a system of four-phase, four-fluid flows for transporting a multi-phase flow (sand, water, gas, and oil) along a flow loop horizontal pipeline with many multiple bends and jumpers. This experimental set-up can be used for investigating a wide variety of multi-phase flow problems considered in the this research. As a means to precisely measure and predict the characteristics of thermo- and hydro-dynamic multi-component mixtures, models representing the multi-phase behavior and equilibrium phase are created and tested. Additionally, the study looks at heat transfer, mass, and momentum in both the flow and the pipeline walls, and offers equations to describe their interrelationships. Another focus of this research is to obtain a Computational Fluid Dynamics (CFD) investigation of multi-phase flow phenomena in order to characterize the impact of pressure gradients and flow regimes due to various types of phase flow techniques used in the petroleum industry and in horizontal pipelines. The results of this thesis offer fundamental and practical guidance for the analysis and design of flow loop pipeline multi-phase flow systems and devices incorporating four-phase flows (sand, water, gas, and oil) through a flow loop pipeline. The novel results were obtained with carefully controlled flow loop pipeline and volume fractions, which show a significant impact on temperature and pressure drops. Dimensionless numbers in fluid mechanics and pressure drop results show good agreement with the experimental data. Further, the experimental and modeling approach of this thesis makes a unique contribution to the O&G field and to the design of transport pipelines for processing four-phase flows that include bends and jumpers.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.696
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.004
Science and technology studies0.0010.000
Scholarly communication0.0000.008
Open science0.0030.005
Research integrity0.0000.001
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 head0.073
GPT teacher head0.295
Teacher spread0.222 · 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.

Study designNot applicable
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

Citations0
Published2022
Admission routes1
Has abstractyes

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