Gas Sorption and Transport in Poroelastic Coals
Bibliographic record
Abstract
Abstract In this paper, natural gas sorption and transient diffusion processes are described within coals exhibiting bimodal (macro- and micro-) pore structure on space-time continuum. Single-component gas is distributed in the microporous solid at adsorbed and dissolved states and in the macropores as free gas. The coal matrix is poroelastic, namely, its solid material manifests swelling and shrinkage effects due to the sorption phenomena under effective overburden stress. Gas transport is Fickian in nature and described by molecular and surface diffusion processes simultaneously taking place in the macro- and micropores, respectively. A free gas concentration-dependent apparent diffusion coefficient is explicitly derived. Initial/boundary value problems are constructed considering the cases of gas uptake by and release from the coal. Consequently, influences of sorption phenomena on solid/macropore volumes and on the overall gas transport are numerically investigated using a finite difference approach. It is found that transport is primarily hindered by equilibrium sorption and takes place at a rate significantly less (typically 1-10 per cent) than that in the macropores only. Macroporosity variations are non-uniform in space and time. These mainly relate to availability of the sorbed gas in microporous solid; thus, the swelling and shrinkage effects are closely associated with the affinity of solid material to the gas component. Only in gas-coal systems with large sorption capacity the solid material is observed to shrink during the gas release and swell as the gas is sorbed by the coal. The estimated macropore volume changes could be as high as ±10 percent, although their effect on the overall gas transport is negligible.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".