INSTABILITY OF FLUID AND THERMAL FRONTS IN NON-ISOTHERMAL FLOWS IN HOMOGENEOUS POROUS MEDIA
Bibliographic record
Abstract
The viscous fingering of miscible flow displacements in a homogeneous porous media is examined in the case involving heat transfer between the fluids. The problem is formulated using continuity equation, Darcy's law, and volume-averaged forms of convection-diffusion equation for mass and energy balance. Full nonlinear simulations, using a pseudo-spectral method, allowed to analyze the mechanisms of fingering instability that result from the dependence of the fluids viscosities on both temperature and concentration. This dependence is represented by two dimensionless parameters; the solutal viscosity ratio; βC and the thermal viscosity ratio; βT. In particular, the study examined the effects of varying important parameters such as the Lewis number, the thermal lag coefficient and the thermal mobility ratio on the dynamics of the flow. The development of the new finger structures is analyzed by examining contours of the concentration and characterizing them qualitatively through a spectral analysis of the average concentration and an analysis of the variations of the mixing length and the relative contact area. It is found that diffusion of heat and its redistribution between the fluid and solid phases have a strong effect on the growth of the fingers. Furthermore, close and intricate interactions between the fluid and thermal fronts affect the subsequent development of the instability even in case where the two fronts are separated, with the thermal front lagging behind the fluid one.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".