CFD modeling and simulation of clogging in packed beds with nonaqueous media
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.
Bibliographic record
Abstract
Abstract When liquids containing low concentrations of fine solid impurities are treated in packed‐bed reactors, clogging develops and starts hampering the flow severely. This phenomenon, called deep‐bed filtration, constitutes serious concern over hydrotreating or hydrocracking of bituminous sands in packed‐bed reactors, in which such nonfilterable fines as native clay or incipient coke cause reactor dysfunction by clogging. A detailed k‐fluid Eulerian 2‐D transient computational‐fluid dynamic (CFD) model was formulated to describe the space‐time evolution of clogging patterns developing in deep‐bed filtration of the liquids. A local formulation of the macroscopic logarithmic filtration law is proposed, as well as a geometrical model for the effective specific surface area of momentum exchange. Both mono‐ and multiple‐layer deposition mechanisms were accounted for by including appropriate filter coefficient formulations. Transient, 2‐D axisymmetrical simulations were benchmarked using experimental results and observations of Narayan et al. (1997) of the carbon‐black contaminated kerosene flow through packed beds. Comparing the simulations and experiments showed that CFD is useful for the quantitative description of packed‐bed clogging.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| 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 it