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Record W4312736712 · doi:10.1115/ipc2022-86297

Performance of Twelve Different Equations of State for Natural Gas and Hydrogen Blends

2022· article· en· W4312736712 on OpenAlexaff
K. K. Botros, Larry Jensen

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicPhase Equilibria and Thermodynamics
Canadian institutionsAlberta EnergyNova Chemicals (Canada)
Fundersnot available
KeywordsIsochoric processIsobaric processThermodynamicsHeat capacitySpeed of soundHelmholtz free energyCompressibility factorEnthalpyGibbs free energyEquation of stateChemistryAtmospheric temperature rangeCompressibilityMaterials sciencePhysics

Abstract

fetched live from OpenAlex

Abstract The aspiration for blending hydrogen (H2) into natural gas (NG) in gas transmission systems is high and is happening globally. However, the principal properties of the blended mixtures and their thermodynamic derivatives can significantly vary depending on the Equation of State (EOS) employed. There is a need to arrive at the best performing EOS for the prediction of the blended mixtures from low to high concentration of H2 in the blend with NG. Twelve different EOS were evaluated against measured data found in the open literature of pure H2, binary mixtures with alkanes and mixtures with NG. Three measured properties were found, namely density, speed of sound and isobaric heat capacity (Cp) in the range of pressures up to 50 MPa and temperatures in the range of −20°C to +80°C and H2 concentration up to 88%(mole). The total number of measured data points are 629 for pure H2 and 1788 for Binaries and NG mixtures with H2. Performance of each EOS is based on the average of the absolute error (deviation%) between predicted vs. measured parameters. These were: density, which represents the principal performance of the EOS with respect the basic formulation of P, ρ and T, the speed of sound, which represents a thermodynamic derivative with respect to entropy, and isobaric heat capacity which represents a thermodynamic derivative with respect to enthalpy. All other thermodynamic derivatives can be related to these three parameters (e.g., J.T coefficient, isochoric heat capacity, enthalpy, internal energy,, compressibility factor and Helmholtz and Gibbs free energies, etc.). Transport properties predictions are based on other empirical and semi-empirical correlations that are independent of the EOS and hence were not considered. It was found that, for the most part and for pure H2, GERG2008 EOS performed best in predicting the above three principal parameters followed by AGA8. For Binary and NG mixtures with H2, again GERG2008 was found to be the best performing EOS for all ranges of P and T, while the second-best performer is BWRS in the range of 0.1–3 MPa and AGA8 in the range of 3–25 MPa, respectively.

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)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.005
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.008
GPT teacher head0.204
Teacher spread0.196 · 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 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
Published2022
Admission routes1
Has abstractyes

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