Capillary Curves for Ex‐situ Washing of Oil‐Coated Particles
Bibliographic record
Abstract
Abstract The oil removal efficiency for the ex situ extraction of bitumen from oil sands, or ex situ washing of oil‐contaminated sand and related processes is determined by the balance of forces at the oil/water and solid/fluid interfaces. The objective of this work is to estimate the balance of forces at the interface using dimensionless numbers, and their use in evaluating and engineering ex situ soil washing processes. To this end, bitumen was removed from bitumen‐coated sand particles using a two‐step process. In the first step, the particles were mixed with a suitable solvent (toluene) used, primarily, to reduce the viscosity of bitumen. The particles were then mixed with water or an aqueous surfactant solution capable of producing low interfacial tensions with the solvent‐bitumen mixture. The fraction of oil retained after washing was evaluated as a function of interfacial tension, solvent/bitumen ratio, mixing time, mixing velocity, and particle size. These ex situ washing conditions were normalized using dimensionless film and particle‐based Weber and Capillary numbers. The fraction of oil retained by the particles was plotted against these dimensionless numbers to generate capillary curves similar to those used in enhanced oil recovery. These curves reveal the existence of a critical film‐based Weber number and a particle‐based Capillary number that can be used in the design or evaluation of soil washing processes. The film‐based Weber number also explained literature data that associates interfacial tension with the removal of oil from oil‐based drill cuttings, as well as field observations on the role that particle size plays on the removal of oil in soil washing operations.
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.
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".