Optimization of Welding Process Parameters for Reduced Activation Ferritic-Martensitic (RAFM) Steel

作     者：Fuzeau, J. Vasudevan, M. Maduraimuthu, V. 

作者机构：Higher Inst Aeronaut & Space Higher Natl Sch Mech & Aeronaut ENSMA ISAE Toulouse France Indira Gandhi Ctr Atom Res Monitoring & Modeling Sect Mat Technol Div Adv Welding Proc Kalpakkam 603102 Tamil Nadu India 

出 版 物：《TRANSACTIONS OF THE INDIAN INSTITUTE OF METALS》 (印度金属学会汇刊)

年 卷 期：2016年第69卷第8期

页      面：1493-1499页

核心收录：

学科分类：0806[工学-冶金工程] 08[工学] 

主　　题：Genetic algorithm Artificial neural network A-TIG welding RAFM steel Process parameters optimization 

摘      要：Reduced-activation ferritic and martensitic (RAFM) steels are considered as struc tural materials for fusion reactor applications as they can loose their induced radioactivity quite early. In RAFM steel weld joints produced by A-TIG welding process, weld bead width (BW), depth of penetration and heat affected zone (HAZ) width play an important role in determining the mechanical properties and also the performance of the weld joints during service. To obtain the desired depth of penetration, and HAZ width, it becomes necessary to set up the welding process parameters. In the present work, intelligent modeling using genetic algorithm (GA) was used for optimization of the welding process parameters. Then GA suggested welding process parameters were validated for achieving the desired depth of penetration and HAZ width during A-TIG welding of RAFM steels. There was good agreement between the predicted and the measured values of depth of penetration and the HAZ width obtained.