Contaminants removal from natural gas using dual hollow fiber membrane contactors
Bibliographic record
Abstract
Hollow fiber membrane contactors are advantageous in natural gas processing where the required equipment foot-print is small. This is due to the larger available gas-liquid contactor area, a greater mass transfer coefficient and higher removal efficiencies. Traditionally, the hollow fiber membrane contactors used for gas-liquid contacting were designed to have separate absorption and regeneration system, which may not be practical for offshore application due to limited space. A dual membrane concept is proposed in this work which combines the contactor and stripper into one unit operation. In this design, the gas flows through the porous membranes immersed in a solvent; the solvent strips the gas of the contaminant. Nonporous membranes with a sweep gas flowing or under low pressure in the same shell, partially regenerate the solvent by stripping the contaminant out. In addition, baffles were introduced into the dual membrane module to increase the mass transfer by minimizing shell-side bypass and increasing liquid velocity. The proposed modules and an ordinary single hollow fiber membrane contactor were modeled using partial differential equations based on a single-component absorption scheme. A numerical model based on mass balance was developed to predict the performance of the dual contactor modules and also concentration change in both gas and liquid phase in the modules. -- Simulation results show that the nonporous membranes in the dual hollow fiber membrane contactor can partially regenerate the solvent during the absorption and result in a better gas removal efficiency than the ordinary module. In addition, the baffles were proved to increase the mass transfer by minimizing shell-side bypass and increasing liquid velocity. The predictions of the developed numerical model were found to be in good agreement with the previous experimental results presented by Dindore et al (2005).
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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 | 0.000 |
| 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 | 0.001 |
| 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 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".