Silica nanoparticles for fines stabilization in Ottawa sand packed beds; Uso de nanopartículas de sílice para la estabilización de finos en lechos empacados de arena Ottawa
Bibliographic record
Abstract
To determine the problem of fines migration on packed beds and offer a possible solution for this issue, an adsorptive system of packed beds was developed for experimental simulation of fines migration and stabilization by using silica nanoparticles. The adsorbent beds were prepared with Ottawa sand and glass spheres (average radius of 0.53 mm). Three different sand beds were used in the investigation: clean sand (water- wet system), sand submitted to a damage process using an extra-heavy Colombian crude oil (oil-wet system) and sand treated with silica nanoparticles (5-15 nm). Fines suspension was prepared with alumina nanoparticles (50 nm) and distilled water. Results show that beds treated with silica nanoparticles present idealized patterns for the rupture curve, indicating that silica nanoparticles capture and retain fines, decreasing fines migration due to their adsorption capacity.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".