Establishment of Intrinsic Permeability of Coarse Open-Graded Materials: Review and Analysis of Existing Data from Natural Air Convection Tests
Bibliographic record
Abstract
This paper presents a review and analysis of large-scale air convection tests and the establishment of intrinsic permeability in coarse open-graded materials. Natural air convection can make a significant contribution to heat transfer during cooling periods. In seasonally freezing environments this can result in excessive frost penetration and subsequent frost-related problems. Intrinsic permeability largely defines the onset of convective heat transfer in granular materials. Conventional methods for measuring intrinsic permeability cannot be applied to very coarse materials. Large-scale laboratory experiments on natural air convection can serve as an alternative method for determining this crucial parameter. This paper gives an overview of four different experimental test setups for measuring natural air convection, all differing in physical shape, boundary conditions and heat flux/temperature measurement devices. Comparison between these is difficult because the air convection pattern can differ and in some cases the shape and number of convection cells cannot be validated. Most of the studies available in the literature use theoretical equations to approximate intrinsic permeability. A method based on the analytical Nu-Ra number relationship is employed to establish the values of intrinsic permeability. Tests that provide enough data to enable the use of the Nu-Ra relationship are very limited. The overall results show a reasonable correlation between experiment-based intrinsic permeability and theoretical approximation. However, several issues must be addressed: first, differences may exist between the intrinsic permeability of natural and of crushed materials due to the shape effect. Second, the method used is in theory valid only for two-dimensional air convection within a square enclosure heated from below. Yet the results show that this method could be extended to other conditions with a certain degree of confidence. Third, a good estimate of intrinsic permeability is possible only with accurate experimental measurement.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.009 | 0.006 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".