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Corrosion rate prediction for metals in biodiesel using artificial neural networks

Author

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  • Rocabruno-Valdés, C.I.
  • González-Rodriguez, J.G.
  • Díaz-Blanco, Y.
  • Juantorena, A.U.
  • Muñoz-Ledo, J.A.
  • El-Hamzaoui, Y.
  • Hernández, J.A.

Abstract

The objective of this research was to develop a direct artificial neural network with the ability to predict a corrosion rate of metals in different biodiesel. Experimental values were obtained by the electrochemical noise technique, EN, as well as, information reported in the literature. A backpropagation model was proposed with three layers; metal and biodiesel composition, blend biodiesel/diesel, total acid number (TAN), temperature and exposure time were considered as input variables in the model. The best fitting training data were acquired with 24:4:1, considering a Levenberg –Marquardt learning algorithm, a hyperbolic tangent and linear transfer functions in the hidden and output layer respectively. Experimental and simulated data were compared satisfactorily through the linear regression model with a correlation coefficient of 0.9885 and a mean square error, MSE, of 2.15 × 10−4 in the validation stage. Furthermore, the model agreed the requirements of the slope and the intercept statistical test with a 99% confidence. The obtained results indicated that the ANN model could be attractive as corrosion rate estimator.

Suggested Citation

  • Rocabruno-Valdés, C.I. & González-Rodriguez, J.G. & Díaz-Blanco, Y. & Juantorena, A.U. & Muñoz-Ledo, J.A. & El-Hamzaoui, Y. & Hernández, J.A., 2019. "Corrosion rate prediction for metals in biodiesel using artificial neural networks," Renewable Energy, Elsevier, vol. 140(C), pages 592-601.
    • Handle: RePEc:eee:renene:v:140:y:2019:i:c:p:592-601
    DOI: 10.1016/j.renene.2019.03.065
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    References listed on IDEAS

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    2. Jin, Dingfeng & Zhou, Xuehua & Wu, Panpan & Jiang, Li & Ge, Hongliang, 2015. "Corrosion behavior of ASTM 1045 mild steel in palm biodiesel," Renewable Energy, Elsevier, vol. 81(C), pages 457-463.
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    2. Dmytro Zhuravel & Kyrylo Samoichuk & Serhii Petrychenko & Andrii Bondar & Taras Hutsol & Maciej Kuboń & Marcin Niemiec & Lyudmyla Mykhailova & Zofia Gródek-Szostak & Dmytro Sorokin, 2022. "Modeling of Diesel Engine Fuel Systems Reliability When Operating on Biofuels," Energies, MDPI, vol. 15(5), pages 1-16, February.
    3. Kugelmeier, Cristie Luis & Monteiro, Marcos Roberto & da Silva, Rodrigo & Kuri, Sebastião Elias & Sordi, Vitor Luiz & Della Rovere, Carlos Alberto, 2021. "Corrosion behavior of carbon steel, stainless steel, aluminum and copper upon exposure to biodiesel blended with petrodiesel," Energy, Elsevier, vol. 226(C).
    4. Li, Kaiyang & Zeng, Yimin, 2022. "Corrosion of heat exchanger materials in co-combustion thermal power plants," Renewable and Sustainable Energy Reviews, Elsevier, vol. 161(C).

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