Performance of Appended Wire Mesh Packing in Sieve Tray Distillation Column of Ethanol-Water System
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Bibliographic record
Abstract
For the separation process in liquid-liquid mixture such as ethanol-water mixture, a sieve tray distillation columnis an alternatif for affordable process and maintenance. However to date, this sieve tray system is still currentlyhaving a lower Murphee efficiency and smaller interfacial area, as compared to other tray system, that is, either abubble cap or valve tray. Therefore it is of important to optimize the performance of sieve tray distillation bymeans of adding the wire mesh packing on that tray, as being the aim of the present study. This study isconducted by using a batch sieve tray distillation system, where the wire mesh packing is added on the third traythat is calculated from the top of the column, to avoid flooding inside the column. Here the resulting fermentedmolasses of containing a 10% volume of ethanol is used as a mixture distillation feed. The height of the wiremesh packing being studied is varied as 5 cm, 3 cm, and 2 cm. Our results showed that the Murphee efficiencyobtained by the variation of the packing height of 5 cm, 3 cm, 2 cm and without packing were 73.5%, 66.27%,56.86%, and 46.7% respectively, and were increased by subsequent level of the packing height. Thecorresponding hydrodynamic properties of this appended packing sieve tray distillation by means of theinterfacial area were 11.88 cm2/cm3, 0.48 cm2/cm3, and 0.32 cm2/cm3, while its pressure drop measured from thewater manometer height were 38.33 cm H2O/m, 30 cm H2O/m, 10 cm H2O/m for the packing height of 5 cm, 3cm, 2 cm height, respectively. The increasing of the performance of appended packing sieve tray distillation bymeans of the Murphee efficiency is explained by the increasing of the interfacial area for vapour-liquid than thetray itself. This preliminary study is expected to be a pioneer study of strategy to increase the performance ofconventional sieve tray distillation that is known as a kind of affordable distillation process.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| 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 it