Mass transfer of CO2 gas pocket in horizontal pipe flow
Bibliographic record
Abstract
ABSTRACT The mass transfer from a stagnant CO2 gas pocket to the flowing water in a horizontal pipe was investigated experimentally, considering the application of pH adjustment by injecting gaseous CO2 for raw water in water treatment industries. In the experiments, the variation of the CO2 gas pocket volume and the corresponding pH values of the pipe flow with time under different conditions were recorded. The mass transfer coefficient of the CO2 gas pocket in the pipe flow was then calculated. The results showed that the injection of gaseous CO2 into the pipe flow could effectively adjust the pH. The volume of the CO2 gas pocket decreased exponentially. Different from most studies on bubble mass transfer, it was found that the ambient CO2 concentration could not be neglected in this study due to the large volume of the gas pocket and the restricted space in the pipe. The mass transfer coefficient increased with the increasing ratio of the CO2 injection rate to the water flow rate and exhibited a sharp reduction as the volume of the CO2 gas pocket decreased by about 80%. The outcomes of this paper can contribute to a better understanding of gas bubble mass transfer in pipe flows.
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".