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Record W2059061644 · doi:10.1021/ef050057c

Development of Graphical Methods for Estimating the Diffusivity Coefficient of Gases in Bitumen from Pressure-Decay Data

2005· article· en· W2059061644 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueEnergy & Fuels · 2005
Typearticle
Languageen
FieldEngineering
TopicPhase Equilibria and Thermodynamics
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsThermal diffusivityThermodynamicsLaplace transformDiffusionChemistryMechanicsMathematicsMathematical analysisPhysics

Abstract

fetched live from OpenAlex

New graphical techniques are presented for estimating the diffusivity coefficient (or mass diffusivity) of CO 2, CH 4, and N 2 in highly viscous bitumens from pressure-decay data. These methods are based on modeling the rate of change in system pressure as gas diffuses into the bitumen using the diffusion equation, coupled with a mass balance for the gas phase. Analytical solutions of the resulting set of equations, with appropriate initial and boundary conditions, are obtained by Laplace transformation. An inverse solution technique is used for developing two graphical methods to estimate the diffusivity coefficient from pressure-decay data reported in the literature. The estimated diffusivity coefficients for gas−bitumen pairs at 75−90 °C vary from 2.5 × 10 - 10 m 2 /s to 7.8 × 10 - 10 m 2 /s, and these are in good agreement with literature values. The novelty of the proposed methodology is in its simplicity and its ability to isolate portions of the pressure-decay data that are affected by experimental fluctuations. This enables the consideration of only that portion of the data that is consistent with the analytical solution.

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 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 score0.603
Threshold uncertainty score0.365

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 integrity0.0000.000
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 head0.028
GPT teacher head0.306
Teacher spread0.277 · 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