@Article{cmc.2022.019257,
AUTHOR = {A. F. Mohamed, J. Abu Alsoud, Mujahed Al-Dhaifallah, Hegazy Rezk, Mohamed K. Hassan},
TITLE = {Modeling and Optimization of Surface Roughness of Epoxy/Nanoparticles Composite Coating},
JOURNAL = {Computers, Materials \& Continua},
VOLUME = {71},
YEAR = {2022},
NUMBER = {1},
PAGES = {71--83},
URL = {http://www.techscience.com/cmc/v71n1/45367},
ISSN = {1546-2226},
ABSTRACT = {In power plants, flue gases can cause severe corrosion damage in metallic parts such as flue ducts, heat exchangers, and boilers. Coating is an effective technique to prevent this damage. A robust fuzzy model of the surface roughness (<i>R</i><sub>a</sub> and <i>R</i><sub>z</sub>) of flue gas ducts coated by protective composite coating from epoxy and nanoparticles was constructed based on the experimental dataset. The proposed model consists of four nanoparticles (ZnO, ZrO<sub>2</sub>, SiO<sub>2</sub>, and NiO) with 2%, 4%, 6%, and 8%, respectively. Response surface methodology (RSM) was used to optimize the process parameters and identify the optimal conditions for minimum surface roughness of this coated duct. To prove the superiority of the proposed fuzzy model, the model results were compared with those obtained by ANOVA, with the coefficient of determination and the root-mean-square error (RMSE) used as metrics. For <i>R</i><sub>a</sub>, for the first output response, using ANOVA, the coefficient-of-determination values were 0.9137 and 0.4037, respectively, for training and prediction. Similarly, for <i>R</i><sub>z</sub>, the second output response, the coefficient-of-determination results were 0.9695 and 0.4037, respectively, for training and prediction. In the fuzzy modeling of <i>R</i><sub>a</sub>, for the first output response, the RMSE values were 0.0 and 0.1455, respectively, for training and testing. The values for the coefficient of determination were 1.00 and 0.9807, respectively, for training and testing. The results prove the superiority of fuzzy modeling. For modeling the second output response <i>R</i><sub>z</sub>, the RMSE values were 0.0 and 0.0421, respectively, for training and testing, and the coefficient-of-determination values were 1.00 and 0.9959, respectively, for training and testing.},
DOI = {10.32604/cmc.2022.019257}
}