Process Optimization of Biodiesel from Used Cooking Oil in a Microwave Reactor: A Case of Machine Learning and Box–Behnken Design
Abstract
:1. Introduction
2. Methodology for Research
2.1. Materials
2.2. Biodiesel Synthesis from UCO in a Microwave Reactor
2.3. Design of Experiments (DoE) by BBD Modeling
2.4. Improvement of Biodiesel Process by ANN Modeling
3. Results and Discussion
3.1. Modeling and Optimization of Biodiesel Process Using RSM
3.2. Modeling and Regression of Biodiesel Process Using ANN
4. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
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Process Variables | Symbol | Units | Levels | ||
---|---|---|---|---|---|
Low −1 | Mid 0 | High +1 | |||
Catalyst content | A | wt.% | 3.0 | 5.0 | 7.0 |
Methanol/UCO mole ratio | B | mol/mol | 12:1 | 15:1 | 18:1 |
Irradiation time | C | Min | 5.0 | 7.0 | 9.0 |
Property | Value/Comment |
---|---|
Training algorithm | Levenberg-Marquardt (LM) or trainlm |
Back-propagation (BP) | |
Learning | Supervised |
Input layer | No transfer function is used |
Hidden layer | TANSIG transfer function |
Output layer | PURELIN transfer function |
Number of best iterations/epoch | 5 |
Number of input neurons | 3 |
Number of hidden neurons | 10 |
Number of output neurons | 1 |
Run | A Catalyst Content (wt.%) | B Methanol/UCO Mole Ratio (mol/mol) | C Irradiation Time (min) | Experimental Biodiesel Yield (%) | Predicted Biodiesel Yield (%) |
---|---|---|---|---|---|
1 | 5 | 15 | 7 | 90 | 89.68 |
2 | 5 | 12 | 5 | 43 | 42.25 |
3 | 5 | 15 | 7 | 90 | 89.68 |
4 | 5 | 15 | 7 | 90 | 89.68 |
5 | 5 | 15 | 7 | 90 | 89.68 |
6 | 3 | 12 | 7 | 51 | 50.82 |
7 | 7 | 12 | 7 | 44 | 45.34 |
8 | 5 | 12 | 9 | 56 | 55.56 |
9 | 5 | 15 | 7 | 90 | 89.68 |
10 | 5 | 15 | 7 | 90 | 89.68 |
11 | 3 | 18 | 7 | 90 | 89.01 |
12 | 5 | 15 | 7 | 90 | 89.68 |
13 | 3 | 15 | 9 | 84 | 84.11 |
14 | 7 | 15 | 5 | 77 | 77.31 |
15 | 7 | 15 | 9 | 85 | 83.78 |
16 | 5 | 18 | 9 | 96 | 96.62 |
17 | 7 | 18 | 7 | 99 | 98.39 |
18 | 5 | 15 | 7 | 90 | 89.68 |
19 | 5 | 18 | 5 | 92 | 92.44 |
20 | 3 | 15 | 5 | 72 | 73.08 |
Source | Sum of Squares | Df | Mean Square | F-Value | p-Value |
---|---|---|---|---|---|
Model | 5758.98 | 9 | 639.89 | 909.89 | <0.0001 |
A—Catalyst content | 7.61 | 1 | 7.61 | 10.81 | 0.0082 |
B—Methanol/UCO mole ratio | 4162.83 | 1 | 4162.83 | 5919.32 | <0.0001 |
C—Irradiation time | 153.04 | 1 | 153.04 | 217.61 | <0.0001 |
AB | 55.20 | 1 | 55.20 | 78.50 | <0.0001 |
AC | 5.20 | 1 | 5.20 | 7.39 | 0.0216 |
BC | 20.84 | 1 | 20.84 | 29.63 | 0.0003 |
A2 | 136.63 | 1 | 136.63 | 194.27 | <0.0001 |
B2 | 811.00 | 1 | 811.00 | 1153.20 | <0.0001 |
C2 | 98.39 | 1 | 98.39 | 139.91 | <0.0001 |
Residual | 7.03 | 10 | 0.7033 | ||
Lack of fit | 7.01 | 3 | 2.34 | 681.75 | <0.0001 |
Pure error | 0.0240 | 7 | 0.0034 | ||
Cor. total | 5766.02 | 19 |
Model | A Catalyst Content (wt.%) | B Methanol/UCO Mole Ratio (mol/mol) | C Irradiation Time (min) | Predicted Biodiesel Yield (%) | Validation Biodiesel Yield (%) |
---|---|---|---|---|---|
BBD | 4.94 | 16.76 | 8.13 | 98.62 | 98 |
ANN | 7 | 18 | 7 | 98.53 | 98 |
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Buasri, A.; Sirikoom, P.; Pattane, S.; Buachum, O.; Loryuenyong, V. Process Optimization of Biodiesel from Used Cooking Oil in a Microwave Reactor: A Case of Machine Learning and Box–Behnken Design. ChemEngineering 2023, 7, 65. https://doi.org/10.3390/chemengineering7040065
Buasri A, Sirikoom P, Pattane S, Buachum O, Loryuenyong V. Process Optimization of Biodiesel from Used Cooking Oil in a Microwave Reactor: A Case of Machine Learning and Box–Behnken Design. ChemEngineering. 2023; 7(4):65. https://doi.org/10.3390/chemengineering7040065
Chicago/Turabian StyleBuasri, Achanai, Phensuda Sirikoom, Sirinan Pattane, Orapharn Buachum, and Vorrada Loryuenyong. 2023. "Process Optimization of Biodiesel from Used Cooking Oil in a Microwave Reactor: A Case of Machine Learning and Box–Behnken Design" ChemEngineering 7, no. 4: 65. https://doi.org/10.3390/chemengineering7040065