Overview of Process Modeling Software: Utilizing Alternative Fuels in Cement Plant for Air Pollution Reduction
Why this work is in the frame
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Bibliographic record
Abstract
The use of process systems engineering tools, such as process modeling software enable the alternative generation of more efficient and sustainable processes. This paper presents the simulation of cement process using alternative fuels to replace coal. The process modeling is performed using Aspen HYSYS. Simulation results revealed that the substitution of fuel oil, natural gas and palm kernel shell for coal had a significant contribution for emission reduction in cement industry. The emissions for the base case scenario found to be 40,317 kg/h CO 2 , 806 kg/h NO 2 and 146.8 kg/h SO 2 . Utilizing fuel oil mitigated 22% of CO 2 and 92% of NO 2 but increased 232% of SO 2 emissions. Altering coal to palm kernel shell resulted in 46.16% of CO 2 , 73% of NO 2 and 68% of SO 2 emission reduction. In the best case 45.64 % reduction of CO 2 emissions was achieved by replacing coal to natural gas and neither NO 2 nor SO 2 was generated. Key words : Cement plant; Process simulation; Aspen HYSYS; Alternative fuels; Air pollution reduction
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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 | 0.001 |
| 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