Modeling Solid Oxide Fuel cell SOFC numerically and by Al-based technique is the main objective of this paper. Testing the reliability of a two dimensional numerical model of SOFC using COMSOL (FEMLAB 3.1) software against neural network model is another important issue that will be considered in this paper. In the proposed study, two layers feed forward neural network was examined for the purpose of modeling the Solid Oxide Fuel Cell (SOFC) system. The examined neural network model with one hidden layer of ten nodes was trained with the Levenberg-Marquardt back propagation algorithm. The presented feed forward neural network model is fitted very well with the experimental data and proved to outperform a numerical model. The various outcomes of this application indicate that numerical simulation of SOFC by using FEMLAB 3.1 needs minor modifications. A more general investigation into potential role of neural network in modeling SOFC is conducted in this research.
El-Hosseini, M., & Haikal, A. (2021). Solid Oxide Fuel Cell Modeling Using Numerical Method and Neural Network.. MEJ- Mansoura Engineering Journal, 39(4), 1-8. doi: 10.21608/bfemu.2021.201597
MLA
Mostafa El-Hosseini; Amira Y. Haikal. "Solid Oxide Fuel Cell Modeling Using Numerical Method and Neural Network.". MEJ- Mansoura Engineering Journal, 39, 4, 2021, 1-8. doi: 10.21608/bfemu.2021.201597
HARVARD
El-Hosseini, M., Haikal, A. (2021). 'Solid Oxide Fuel Cell Modeling Using Numerical Method and Neural Network.', MEJ- Mansoura Engineering Journal, 39(4), pp. 1-8. doi: 10.21608/bfemu.2021.201597
VANCOUVER
El-Hosseini, M., Haikal, A. Solid Oxide Fuel Cell Modeling Using Numerical Method and Neural Network.. MEJ- Mansoura Engineering Journal, 2021; 39(4): 1-8. doi: 10.21608/bfemu.2021.201597
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