OPTIMIZATION AND SENSITIVITY ANALYSIS OF AN EXTENDED DISTRIBUTED DYNAMIC MODEL OF SUPERCRITICAL CARBON DIOXIDE EXTRACTION OF NIMBIN FROM NEEM SEEDS
Why this work is in the frame
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Bibliographic record
Abstract
ABSTRACT In this article, supercritical extraction of nimbin from neem seeds has been studied. In order to investigate the effect of parameters on nimbin extraction yield, a partial differential equation model based on mass conservation principles. The model was solved using MATLAB software. The results were successfully validated with available laboratory experimental data. The optimum values of the operating parameters were obtained using gradient search strategy. Optimization routine was employed to maximize process profit. The optimum value of temperature, pressure, CO 2 flow rate and particle diameter were found to be 305K, 177.339 bar, 0.9660 cm 3 /min and 0.0575 cm, respectively. Finally, a sensitivity analysis was carried out on the different model parameters, and found that process profit is mostly sensitive to neem price. PRACTICAL APPLICATIONS This work uses mathematical optimization as a computational engine to arrive at the best solution for neem extraction in a systematic and efficient way. In the context of neem supercritical fluid extraction (SFE) systems, coupling optimization with suitable simulation modules opens a new avenue of possibilities. It saves money and provides economical benefits. In neem SFE process, measuring parameters and understanding the process are difficult. In this case, modeling can provide virtual environmental for operator practice.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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