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Record W2793947278 · doi:10.4043/28360-ms

Investigation on Erosion Due to Fine Particles in Multiphase Flow

2018· article· en· W2793947278 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueOffshore Technology Conference Asia · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicErosion and Abrasive Machining
Canadian institutionsIntecsea (Canada)
FundersUniversiti Teknologi Petronas
KeywordsMultiphase flowMechanicsErosionFlow (mathematics)Particle (ecology)Materials scienceComputational fluid dynamicsTwo-phase flowFlow assuranceFlow conditionsParticle sizeFluid dynamicsGeotechnical engineeringGeologyChemistryPhysics

Abstract

fetched live from OpenAlex

Pipeline production system often experiences complex multiphase flow and entrained fine-particles. The erosion due to solid fine particles presents one of the greatest threats to oil and gas flow assurance and consequently impacting material selection and wall thickness design. Limited literature is available on erosional effect caused by submicron particles such as fine sand, abrasive solid materials or gas bubbles. Previous studies on particle erosion are limited to particle size greater than 100 microns in single phase fluid flow. This is based on the assumption that potential for erosion by particle size smaller than 100 microns (specifically lesser than 62.5 microns) is insignificant. Additionally, very few studies have addressed the combined effect of erosion caused by micro-sized particles and multiphase flow. Most predictive erosion models are limited to single phase flow for model simplification purposes. Hence, the effects of multiphase flow and its interaction with sand particles, specifically fine solids, are neglected. Therefore an in-depth understanding of multiphase flow regimes and its interaction with micro-sized particles is an important enabler for more accurate erosion prediction. For more accurate flow modeling and erosion characterization, computer fluid dynamics (CFD) tool is required. In this study, Multiphase CFD (MCFD) is implemented for predicting micro-fine erosion, considering two phase flow pattern features. Concurrently, trajectories of fine particles' bombardment on the pipe inner wall surface are captured using Lagrangian Particle Tracking Model. Analyses are carried out for water and gas flow at isothermal conditions, covering various particle size lesser than 62.5 microns in order to determine material removal rate. The results will be benchmarked against Tulsa multiphase erosion model prediction. Based on the results, it is concluded that the erosional effect caused by micro-sized particles is strongly dependent on the flow patterns in the pipe, determined by superficial velocities of each phase. Additionally, erosional impact or material removal rate is predicted, which though small, is expected to significantly impact material design. The presence of these micro-sized particles acts as an enabler, which produces homogeneous "pits" on the surface of metal, significantly increasing the contact surface area for chemical and mechanical interactions to take place. The results from the proposed modeling using MCFD are expected to benefit erosion impact assessment in multiphase hydrocarbon production and piping systems.

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.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.206
Threshold uncertainty score1.000

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)0.0010.002

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 head0.033
GPT teacher head0.265
Teacher spread0.232 · 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