Modelling and simulation of carbon dioxide absorption by aqueous MEA solution in hollow fibre membrane contactors
Bibliographic record
Abstract
Abstract In this article, a comprehensive model has been developed for analyzing the transport phenomena in hollow fibre membrane contactors operated under non‐wetted or partially wetted conditions. In this regard, the dynamic behaviour of membrane contactors, considering the entrance regions of momentum, thermal energy, and mass transfers, was investigated carefully. Moreover, effects of temperature distribution on the contactor efficiency were examined by taking into account the influences of heat of solution, heat of reaction, and the viscous dissipation. The chemical system studied was a gas sweetening process, including methane and carbon dioxide as the gaseous mixture, and MEA aqueous solution as the solvent. CFD techniques have been used to solve the nonlinear governing equations simultaneously, and the model predictions were validated against reported experimental data in the literature, and excellent agreement was found. Comparing the model predictions with those of previous models shows relatively better accuracy of the model predictions. Furthermore, distributions of velocity, temperature, and species concentrations in the tube side, shell side, and the membrane were obtained and the effects of various operating and design parameters such as wetting fraction, gas and liquid inlet velocities, inlet temperature of the solvent, MEA concentration, and CO2 volume fraction of the feed on these distributions were carefully studied. Finally, the dynamic response of the system was investigated by analyzing the contactor's response to different step and pulse changes.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 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".