Mathematical Modelling of Deposition and Erosion of Particles in Pipes
Bibliographic record
Abstract
Paebbl are interested in the effective transport of a particle-laden fluid through a system of pipes. This transport has the potential to be disrupted if the particles sediment on the walls of the pipe, leading to pipe clogging and blockage. Motivated by this, we investigate the gravity- driven deposition and shear-driven erosion of solid particles carried in a turbulent flow in a pipe. We develop and solve a mathematical model for particle transport in the bulk of the fluid, and particle behaviour near the pipe walls, including deposition and erosion. We also model the chemistry related to the effective capture of CO2, which is important for the quality of the product. Our analysis is a good entry point for future work with Paebbl. More broadly, our work has relevance in wider industrial applications in relation to safety and efficiency, as well as the economic viability of industrial-scale production.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".