TY - JOUR ID - 118857 TI - Modified Particle Swarm Optimization-Artificial Neural Network and Gene Expression Programing for Predicting High Temperature Oxidation Behavior of Ni–Cr–W-Mo Alloys JO - International Journal of Engineering JA - IJE LA - en SN - 1025-2495 AU - Hasibi, H. AU - Mahmoudian, A. AU - Khayati, G. R. AD - Department of Materials Science and Engineering, Shahid Bahonar University of Kerman, Kerman, Iran AD - Department of Metal, Institute of Science and High Technology and Environmental Sciences, Graduate University of Advanced Technology, Kerman, Iran Y1 - 2020 PY - 2020 VL - 33 IS - 11 SP - 2327 EP - 2338 KW - Artificial Neural Network KW - Gene expression programming KW - High-temperature alloys KW - Modified Particle Swarm Optimization KW - Oxidation behavior DO - 10.5829/ije.2020.33.11b.23 N2 - This paper is an attempt to model the oxidation behavior of Ni-base alloys by considering the alloying elements, i.e., Cr, W, Mo, as variables. Modified particle swarm optimization-artificial neural network (MPSO-ANN) and gene expression programming (GEP) techniques were employed for modeling. Data set for construction of (MPSO-ANN) and GEP models selected from 66 cyclic oxidation performed in the temperature range of 400-1150 ᵒC for 27 different Ni-based alloy samples at various amounts of Cr, W, and Mo. The weight percent of alloying elements selected as input variables and the changes of weight during the oxidation cycle considered as output. To analyze the performance of proposed models, various statistical indices, viz. root mean squared error (RMSE) and the correlation coefficient between two data sets (R2) were utilized. The collected data of GEP randomly divided into 21 training sets and 6 testing sets. The results confirmed that the possibility of oxidation behavior modeling using GEP by R2 = 0.981, RMSE =0.0822. By consideration of oxidation resistance as criteria, Cr, Mo, and W enhanced the oxidation resistance of Ni-based alloys. The results showed that in the presence of Cr as alloying element, especially at Cr contents higher than 22 wt.%, the effect of W and Mo were negligible. However, the same trend was reversed at the sample with Cr content lower than 20 wt.%. In these cases, the effect of W and Mo on oxidation resistance were significantly enhanced. UR - https://www.ije.ir/article_118857.html L1 - https://www.ije.ir/article_118857_9d420621ea2ebe6c0cef7bc2e56fc339.pdf ER -