Chemical Plant Design for the Conversion of Plastic Waste to Liquid Fuel
Bibliographic record
Abstract
This paper presents the plant design for fuel production from plastic waste. The types of plastics to be used for the fuel production include polyethylene, polypropylene and polystyrene. All these materials are to be sourced from Kpone landfill site in Accra, Ghana, where the plant is to be situated. The major fuels produced are gasoline, diesel and kerosene with a plant capacity of approximately 1000 tons of plastic waste per day and its attainment is 95%. The production process involves sorting the municipal solid waste to obtain suitable plastics. The plastics are extruded and cracked thermally in a Pyrolyzer and the gases from it are reformed over Zeolite-ZSM 5 as the catalyst in a reactor. Resulting vapours are fractionated in a column to obtain the various fuel components. The plant operates 24 hours/day and 347 days/year with 3 shifts per day of 8 hours per shift. Total capital required to build and start up the plant amounts to approximately 17 Million US Dollars. The plant life is 25 years with an annual rate of return of 34% and a payback period of 2.9 years for this project, after setting up. Annually, the plant would generate gross and net profits of approximately 9 Million US Dollars and 6.7 Million US Dollars respectively.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.012 | 0.004 |
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".