Numerical Modelling of Transport in Complex Porous Media: Metal Foams to the Human Lung
Bibliographic record
Abstract
Transport in porous media has many practical applications in science and engineering. This work focuses on the development of numerical methods for analyzing porous media flows and uses two major applications, metal foams and the human lung, to demonstrate the capabilities of the methods. Both of these systems involve complex pore geometries and typically involve porous domains of complex shape. Such geometric complexities make the characterization of the relevant effective properties of the porous medium as well as the solution of the governing equations in conjugate fluid-porous domains challenging. In porous domains, there are typically too many individual pores to consider transport processes directly; instead the governing equations are volume-averaged to obtain a new sets of governing equations describing the conservation laws in a bulk sense. There are, however, unknown pore-level terms remaining in the volume-averaged equations that must be characterized using effective properties that account for the effects of processes at the pore level. Once closed, the volume-averaged equations can be solved numerically, however currently available numerical methods for conjugate domains do not perform well at fluid-porous interfaces when using unstructured grids.\nIn light of the preceding discussion, the goals of this work are: (i) to develop a finite-volume-based numerical method for solving fluid flow and non-equilibrium heat transfer problems in conjugate fluid-porous domains that is compatible with general unstructured grids, (ii) to characterize the relevant flow and thermal properties of an idealized graphite foam, (iii) to determine the permeability of an alveolated duct, which is considered as a representative element of the respiratory region of the human lung, and (iv) to conduct simulations of airflow in the human lung using a novel fluid-porous description of the domain. Results show that the numerical method that has been developed for conjugate fluid-porous systems is able to maintain accuracy on all grid types, flow directions, and flow speeds considered. This work also introduces a comprehensive set of correlations for the effective properties of graphite foam, which will be useful for studying the performance of devices incorporating this new material. In order to model air flow in the lung as a porous medium, the permeability of an alveolated duct is obtained using direct pore-level simulations. Finally, simulations of air flow in the lung are presented which use a novel fluid-porous approach wherein the upper airways are considered as a pure fluid region and the smaller airways and alveoli are considered as a porous domain.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".