LAPSE:2019.1320
Published Article
LAPSE:2019.1320
Model Prediction and Optimization of Waste Lube Oil Treated with Natural Clay
December 10, 2019
In this work, used lube oil was treated using natural acid-free clay. Clay was added at different amounts (5, 10, and 20 g) to 100 mL of waste engine oil at various temperatures (250, 350, 400, and 450 °C) and mixed at a speed of 800 rpm for 30 min. After settling and separation, the treated oil was diluted with kerosene before being examined using a Ultraviolet−visible (UV) spectrophotometer. In order to achieve cost-effective recycling, this process is modeled using the response surface method (RSM). Five regression models (linear, quadratic, Two Factor Interactions (2FI), cubic, and reduced-order quadratic model) were developed, then tested, and examined by calculating the statistical performance indicators (R2, R2adj, Akaike’s Information Criterion corrected (AICc), Bayesian Information Criterion (BIC), and Root Mean Square Error (RMSE)). The results obtained reveal that the modified quadratic model outperforms the rest of the models in terms of the low value of RMSE, the lowest AICc, lowest BIC, and the highest R2 and R2adj. The developed modified quadratic model is optimized successfully to predict optimum operation conditions. Results show that optimum operation conditions are at the minimum area under the curve for UV absorption at 223.358; this can be achieved with a process temperature of 266.246 °C and clay quantity of 5.331 g. This model agreed with experimental data regardless of the effectiveness of red clay in the therapy of lube oil.
Keywords
ANOVA statistical test, lube oil treatment, process optimization, response surface method, UV-VIS spectrophotometer
Suggested Citation
Osman H. Model Prediction and Optimization of Waste Lube Oil Treated with Natural Clay. (2019). LAPSE:2019.1320
Author Affiliations
Osman H: Department of Chemical Engineering, College of Engineering, King Khalid University, Abha 61421, Saudi Arabia [ORCID]
Journal Name
Processes
Volume
7
Issue
10
Article Number
E729
Year
2019
Publication Date
2019-10-11
Published Version
ISSN
2227-9717
Version Comments
Original Submission
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PII: pr7100729, Publication Type: Journal Article
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LAPSE:2019.1320
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doi:10.3390/pr7100729
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Dec 10, 2019
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CC BY 4.0
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Dec 10, 2019
 
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Original Submitter
Calvin Tsay
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