Bibliographic record
Abstract
Sulphur dioxide (SO2) emission has become one of the major challenging issues for clean \nmarine transportation globally and especially in zero discharge zones Canada-wide with the \nimplementation of the International Maritime Organization (IMO) regulations. Currently, as \nper the IMO guidelines, zero-discharge scrubber technology is in use for the ships that operate \non low cost high sulfur (3.5% w/w) heavy fuels. One of the main concerns with these scrubber \ntechnologies is the non-recyclability of the absorbent and high demand for onsite waste storage \nwhich takes a toll on process operating cost and cargo space. \nOwing to its high capacity, specific selectivity, recyclability, good thermodynamic properties \nand thermal stability, Ionic Liquids (ILs) can be used as an alternative solvent and need to be \ntested to get measurable laboratory data. IMO regulations state that SO2 content release should \nbe within 52 ppm as compared to about 1800 ppm of sulfur oxides in typical exhaust flue gas \nstreams. For this, lab scale experiments were performed with a selected group of ILs to \nunderstand the absorption-desorption capacity of one such ionic liquids. One IL, named IL-A, \nwas selected for it better performance and was further studied to better understand the reaction \nmechanism between the IL and SO2. Results were quite promising with good amount of SO2 \nabsorption and partial regenerative desorption of the solvent mixture. \nBased on the results, it was evident that the viscosity of the IL-A increased tremendously due \nto SO2 dissolution, which necessitated the use of an additive (additive B) as a diluent. The \ndilution effect on vapor-liquid-equilibrium (VLE) and other physical properties were \nexperimentally analyzed. TGA and FTIR gave some insights to quantify the amount of solvent \nloss during the recycling process and to learn about thermal properties and the temperature \noperating range for the absorption-desorption in order to maximize the efficiency. \nA mathematical scale-up design model of the absorber to support an actual 20 MW marine \nvessel combustion engine emitting 61.6 x106 L/hour of flue gas was developed in MATLAB. \nTheoretical modelling of the process helped in selecting the ideal packing material and to \ncompare the designed tower with traditional scrubber. For the same scrubber diameter, the \ndesigned tower height is about 3 meters higher; however, to reduce the footprint to half, an \nincrease of 4.6 meters in height is required. Other advantages include lower operating costs, \nlower solvent requirement and low storage for solvent and waste generation.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".