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Record W3202507360 · doi:10.1002/cjce.24319

Experimental and simulation studies on the phase behaviour for gas hydrates in a <scp> CO <sub>2</sub> </scp> rich gas dominant multiphase pipeline system

2021· article· en· W3202507360 on OpenAlexvenueno aff
Jai Krishna Sahith Sayani, Kuah Jian Ho, Bhajan Lal, Srinivasa Rao Pedapati

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicMethane Hydrates and Related Phenomena
Canadian institutionsnot available
FundersYayasan UTP
KeywordsPropaneClathrate hydrateNatural gasMethaneButaneWork (physics)Pipeline (software)Gas compositionThermodynamicsPetroleum engineeringHydrateMaterials scienceProcess engineeringChemistryMechanical engineeringEngineeringOrganic chemistryPhysics

Abstract

fetched live from OpenAlex

Abstract In this work, an experimental and modelling study is performed to identify the phase behaviour of gas hydrates formation for a high CO 2 content natural gas system and multiphase gas dominant system. Further, CSMGem, PVTSim, and Aspen HYSYS software packages are used to verify the prediction capabilities for gas hydrates formation conditions. Initially, thermodynamic equilibrium conditions are obtained using CSMGem, PVTSim, and Aspen HYSYS. Then, these results are validated and compared to the experimental work to verify the accuracy in predicting hydrate formation conditions. An experimental study is performed in the pressure range of 2–7 MPa for a pure system and multiphase system with the gas composition of carbon dioxide (70%) + methane (26%) + ethane (2%) + propane (1%) + butane (1%). The results show that the PVTSim software package shows the best accuracy with 99.9% for the pure system and 99.88% for the multiphase 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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.016
GPT teacher head0.248
Teacher spread0.233 · 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 source (direct Gemma or distilled Codex), 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

Citations4
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueThe Canadian Journal of Chemical Engineering→Same topicMethane Hydrates and Related Phenomena→French-language works237,207→