Evaluasi Performa Furnace EDC (Ethyl Dichloride) Cracker di VCM (Vinyl Chloride Monomer)-1 Plant
Bibliographic record
Abstract
Furnaces in the production of VCM (Vinyl Chloride Monomer) must be operated with optimal efficiency to maximize production and minimize the formation of impurities (coke). Furnace efficiency is evaluated based on the ratio of heat generated from fuel combustion to heat absorbed by the EDC (Ethyl Dichloride) fluid, and is a key indicator of operational feasibility. In addition, the pressure difference of the inlet convection and outlet radiant sections is used as an additional parameter, where an increase in this value reflects the accumulation of deposits in the tubes. If the efficiency drops below the minimum operating conditions or the pressure difference between the convection inlet and outlet radiant section exceeds 4 kg/cm2G, the furnace is considered unfit for operation and decoking must be performed, which will increase operating costs. During the 12 days of monitoring (measurement every 8 hours), the average efficiency was 85.370%, the highest value was 87.348%, and the lowest value was 83.764%. The efficiency values tended to fluctuate and were below the minimum operating condition (88.898%). This is due to changes in operating conditions and manual control. Therefore, although the pressure difference is still below the threshold of 4 kg/cm2G, the furnace is considered unfit for operation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".