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Record W4206370735 · doi:10.51865/jpgt.2021.02.02

THE INFLUENCE OF PRESSURE AND TEMPERATURE ON THE COMPRESSIBILITY FACTOR

2021· article· en· W4206370735 on OpenAlexaboutno aff
George Iulian Oprea, Artemis Aidoni, Ioana Cornelia Mitrea, Florinel Dinu

Bibliographic record

VenueRomanian Journal of Petroleum & Gas Technology · 2021
Typearticle
Languageen
FieldEngineering
TopicPhase Equilibria and Thermodynamics
Canadian institutionsnot available
Fundersnot available
KeywordsCompressibility factorCompressibilityNatural gasIdeal gasEquation of stateBar (unit)Real gasThermodynamicsSimplicityReduced propertiesNatural gas fieldRange (aeronautics)MathematicsMaterials scienceGeologyPhysicsChemistry

Abstract

fetched live from OpenAlex

The natural gas compressibility factor indicates the compression and expansion characteristics of natural gas under different conditions. It is a thermodynamic property used to take into account the deviation of the behaviour of real natural gases from that of an ideal gas. Compressibility factor, Z, values of natural gases are necessary for most petroleum gas engineering calculations. In this study, a comparison between five different calculation methods is presented to determine this critical parameter for the same natural gas at different conditions (pressure and temperature), using Canadian Association of Petroleum Producers, Azizi, Behbahani and Isazadeh, Dranchuk- Purvis- Robinson, Dranchuk-Abu-Kassem and Standing- Katz methods. The correlations are based on the equation of state are often implicit because they require iteration. Many correlations have been derived to enhance simplicity; however, no correlation has been developed for the entire range of pseudo-reduced pressures and temperatures. Azizi, Behbahani and Isazadeh’s method was found to have the biggest error as a result obtained for T=20° C, and p=20 bar is no longer in the field of applicability.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.570
Threshold uncertainty score0.289

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 integrity0.0000.001
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 head0.004
GPT teacher head0.198
Teacher spread0.194 · 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 designBench or experimental
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

Citations1
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueRomanian Journal of Petroleum & Gas TechnologySame topicPhase Equilibria and ThermodynamicsFrench-language works237,207