Froth flotation as primary treatment of flowback water: Removal of total organic carbon and prediction of kinetics
Bibliographic record
Abstract
Abstract Petroleum and exploration industries employ a hydrofracking process where a large volume of water (fracturing fluid) is injected and a fraction (known as flowback water) is returned to the surface. Froth flotation is a typical process employed for the primary treatment of water. In the present work, froth flotation has been used as a pretreatment method for real flowback water sourced from the petroleum and shale gas exploration industry. In the present work, a first‐principle based convective mass transfer model has been developed to describe the froth flotation performance. The resultant equation was solved analytically and compared with the numerical solution, and a parametric sensitivity analysis of the process performance was also undertaken. In addition, a correlation to estimate the flotation rate constant was proposed, thereby circumventing the need to obtain a large number of cumbersome parameters experimentally. Overall, this study proposes froth flotation as an efficient primary treatment method towards the separation of dispersed oil droplets from the flowback water and the corresponding prediction of kinetics using a first‐principle based transport model.
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".