Capture and catalytic conversion of CO <sub>2</sub> from marine and offshore applications – A review
Bibliographic record
Abstract
Abstract This contribution examines recent advances in modeling fluid dynamics and capture/conversion of CO 2 from marine and offshore applications in packed-bed columns/trickle-bed reactors subjected to static inclination, externally-induced rolling and heaving motions. Breaking the axial symmetry of the two-phase flow once the packed bed system is tilted results in a significant decrease in process performance, the extent of which is determined by the magnitude of the tilt and the column/reactor diameter. Only the conversion of CO 2 from marine engine emissions on-board large cargo ships via catalytic cycloaddition of CO 2 to styrene oxide in multiphase large-diameter trickle-bed reactors increases slightly with increasing reactor inclination. Under the externally induced column/reactor oscillations, CO 2 capture/conversion performance shifts toward the steady-state solution of the vertical column/reactor as the asymmetry between the two inclined positions decreases. Oscillating (between two inclined symmetrical positions) and heaving packed-bed columns/trickle-bed reactors generate an oscillating performance around the steady-state solution of the vertical static position, which is driven by the amplitude and period of the angular and heaving motions via the continuous evolution of the intensity of the reverse secondary flow and by the magnitude of the reactor/column diameter. The catalytic conversion of CO 2 captured from marine emissions via an integrated process coupling reverse water-gas shift reaction and methanol synthesis in a fixed-bed reactors network system shows a remarkable enhancement with the addition of H 2 O adsorbent to the reaction systems in the sorption-enhanced process periods.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".