Multi-objective optimization of gas metal arc welding parameters and sequences for low-carbon steel (Q345D) T-joints

IF 3.1 2区 材料科学 Q1 METALLURGY & METALLURGICAL ENGINEERING
Qing Shao, Tao Xu, Tatsuo Yoshino, Nan Song
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引用次数: 27

Abstract

Q345D high-quality low-carbon steel has been extensively employed in structures with stringent welding quality requirements. A multi-objective optimization of welding stress and deformation was presented to design reasonable values of gas metal arc welding parameters and sequences of Q345D T-joints. The optimized factors included continuous variables (welding current (I), welding voltage (U) and welding speed (v)) and discrete variables (welding sequence (S) and welding direction (D)). The concepts of the pointer and stack in Visual Basic (VB) and the interpolation method were introduced to optimize the variables. The optimization objectives included the different combinations of the angular distortion and transverse welding stress along the transverse and longitudinal distributions. Based on the design of experiments (DOE) and the polynomial regression (PR) model, the finite element (FE) results of the T-joint were used to establish the mathematical models. The Pareto front and the compromise solutions were obtained by using a multi-objective particle swarm optimization (MOPSO) algorithm. The optimal results were validated by the corresponding results of the FE method, and the error between the FE results and the two-objective results as well as that between the FE results and the three-objective optimization results were less than 17.2% and 21.5%, respectively. The influence and setting regularity of different factors were discussed according to the compromise solutions.

低碳钢(Q345D) t形接头气体保护焊参数及顺序多目标优化
Q345D优质低碳钢广泛应用于焊接质量要求严格的结构中。为设计合理的Q345D型t形接头气体保护焊参数和焊接顺序,提出了焊接应力和变形的多目标优化方法。优化后的因素包括连续变量(焊接电流(I)、焊接电压(U)和焊接速度(v))和离散变量(焊接顺序(S)和焊接方向(D))。介绍了Visual Basic (VB)中指针和堆栈的概念,以及对变量进行优化的插值方法。优化目标包括沿横向和纵向分布的角变形和横向焊接应力的不同组合。在试验设计(DOE)和多项式回归(PR)模型的基础上,利用t型接头的有限元结果建立数学模型。采用多目标粒子群优化(MOPSO)算法得到了Pareto前沿解和折中解。采用有限元方法对优化结果进行了验证,结果表明,优化结果与两目标优化结果、与三目标优化结果的误差分别小于17.2%和21.5%。根据折衷方案,讨论了不同因素的影响及设定规律。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
4.30
自引率
0.00%
发文量
2879
审稿时长
3.0 months
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