Robust Particle Swarm Optimization Algorithm for Modeling the Effectof Oxides Thermal Properties on AMIG 304L Stainless Steel Welds  

作　　者：Rachid Djoudjou Abdeljlil Chihaoui Hedhibi Kamel Touileb Abousoufiane Ouis Sahbi Boubaker Hani Said Abdo 

机构地区：[1]Department of Mechanical Engineering,College of Engineering in Al-Kharj,Prince Sattam bin Abdulaziz University,P.O.Box 655,Al-Kharj,16273,Saudi Arabia [2]Department of Computer and Network Engineering,College of Computer Science and Engineering,University of Jeddah,Jeddah,21959,Saudi Arabia [3]Laboratory of Mechanics of Sousse(LMS),National Engineering School of Sousse,University of Sousse,Sousse,4054,Tunisia [4]Center of Excellence for Research in Engineering Materials(CEREM),King Saud University,P.O.Box 800,Al-Riyadh,11421,Saudi Arabia [5]Department of Metallurgical and Materials Engineering,Faculty of Petroleum and Mining Engineering,Suez University,Suez,43512,Egypt

出　　处：《Computer Modeling in Engineering & Sciences》2024年第11期1809-1825,共17页工程与科学中的计算机建模（英文）

摘　　要：There are several advantages to the MIG(Metal Inert Gas)process,which explains its increased use in variouswelding sectors,such as automotive,marine,and construction.A variant of the MIG process,where the sameequipment is employed except for the deposition of a thin layer of flux before the welding operation,is the AMIG(Activated Metal Inert Gas)technique.This study focuses on investigating the impact of physical properties ofindividual metallic oxide fluxes for 304L stainless steel welding joint morphology and to what extent it can helpdetermine a relationship among weld depth penetration,the aspect ratio,and the input physical properties ofthe oxides.Five types of oxides,TiO_(2),SiO_(2),Fe_(2)O_(3),Cr_(2)O_(3),and Mn_(2)O_(3),are tested on butt joint design withoutpreparation of the edges.A robust algorithm based on the particle swarm optimization(PSO)technique is appliedto optimally tune the models’parameters,such as the quadratic error between the actual outputs(depth and aspectratio),and the error estimated by the models’outputs is minimized.The results showed that the proposed PSOmodel is first and foremost robust against uncertainties in measurement devices and modeling errors,and second,that it is capable of accurately representing and quantifying the weld depth penetration and the weld aspect ratioto the oxides’thermal properties.

关 键 词：Activated metal inert gas welding stainless steel activating flux oxides’thermal properties particle swarm optimization 

分 类 号：TG142[一般工业技术—材料科学与工程] TP18[金属学及工艺—金属材料]