Version 1
: Received: 5 September 2024 / Approved: 9 September 2024 / Online: 9 September 2024 (11:32:45 CEST)
How to cite:
Benvenga, M. A. C.; Nääs, I. Optimization Refined Palm Oil Biodiesel Production Using Hybrid Metaheuristic Algorithm (SAGAC). Preprints2024, 2024090643. https://doi.org/10.20944/preprints202409.0643.v1
Benvenga, M. A. C.; Nääs, I. Optimization Refined Palm Oil Biodiesel Production Using Hybrid Metaheuristic Algorithm (SAGAC). Preprints 2024, 2024090643. https://doi.org/10.20944/preprints202409.0643.v1
Benvenga, M. A. C.; Nääs, I. Optimization Refined Palm Oil Biodiesel Production Using Hybrid Metaheuristic Algorithm (SAGAC). Preprints2024, 2024090643. https://doi.org/10.20944/preprints202409.0643.v1
APA Style
Benvenga, M. A. C., & Nääs, I. (2024). Optimization Refined Palm Oil Biodiesel Production Using Hybrid Metaheuristic Algorithm (SAGAC). Preprints. https://doi.org/10.20944/preprints202409.0643.v1
Chicago/Turabian Style
Benvenga, M. A. C. and Irenilza Nääs. 2024 "Optimization Refined Palm Oil Biodiesel Production Using Hybrid Metaheuristic Algorithm (SAGAC)" Preprints. https://doi.org/10.20944/preprints202409.0643.v1
Abstract
The main goal of optimization is to find factors values that bring minimum feedstock consumption or maximum final product or services of the production process. In a production process, the factors that make up the model that describes it are usually the properties of the final product. In the case of biodiesel, which is the final product of the process that is the object of study, among the various properties, the glycerol content is among the most important. The present study aims to maximize the model yield that defines glycerol content on the biodiesel composition. This optimization was executed by a hybrid metaheuristic algorithm (SAGAC),and its experimental results are compared with other optimization techniques named by RSM (Response Surface Methodology). After run the experimental assays, SAGAC algorithm has find the follow values of model factors: molar ratio = 3(mol/mol), catalyst content = 0.52 (wt%), reaction temperature = 49(oC), Time = 45 (min) generating model yield of 14.46 that, match with EN 14105 standard value of 0.33 (wt%). Comparing results between SAGAC and RSM methodologies, SAGAC has presented an improvement of 31%.
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
