2011Applied Mechanics and MaterialsRequires access

Prediction of Welding Distortion in 304 Stainless Steel

Dong Feng Li, Rui Wang, Xin Han, Peng Yang, Jun Han, Lei Zhang

Open publisher page 1 citations

Abstract

Prediction of welding distortion of stainless steel welding joint in reasonable time is meaningful in welding industry. In this paper, a three dimensional thermo-elastic-plastic finite element method (FEM) is developed to precisely predict welding distortion on bead on plate welding with 304 stainless steel. Meanwhile, the corresponding experiments are carried out to validate the predicted results. Research results show the predicted results by FEM match the experimental results very well. In the condition of different welding heat input, the welding heat input play an important role on welding distortion. While, material properties of stainless steel play a larger role on welding distortion when welding heat input is same. Further, for bead on plate welding of thin plate, both large distortion theory and small distortion theory are computed. The results show that using large distortion theory is more accurate in prediction welding distortion on thin plate welding.

About this research paper

What this paper is about

Prediction of welding distortion of stainless steel welding joint in reasonable time is meaningful in welding industry. In this paper, a three dimensional thermo-elastic-plastic finite element method (FEM) is developed to precisely predict welding distortion on bead on plate welding with 304 stainless steel. Meanwhile, the corresponding experiments are carried out to validate the predicted results. Research results show the predicted results by FEM match the experimental results very well. In the condition of different welding heat input, the welding heat input play an important role on welding distortion. While, material properties of stainless steel play a larger role on welding distortion when welding heat input is same. Further, for bead on plate welding of thin plate, both large distortion theory and small distortion theory are computed. The results show that using large distortion theory is more accurate in prediction welding distortion on thin plate welding.

Why it matters

OpenAlex reports 1 citations for this work. Citation counts describe recorded attention and do not establish research quality.

Key contribution

A contribution statement is not available in the OpenAlex record.

Method / approach

Method details are not available in the OpenAlex metadata.

Main findings

Findings are not separately available in the OpenAlex metadata.

Limitations

Limitations are not available in the OpenAlex metadata.

Applications

Application details are not available in the OpenAlex metadata.

Available abstract

Prediction of welding distortion of stainless steel welding joint in reasonable time is meaningful in welding industry. In this paper, a three dimensional thermo-elastic-plastic finite element method (FEM) is developed to precisely predict welding distortion on bead on plate welding with 304 stainless steel. Meanwhile, the corresponding experiments are carried out to validate the predicted results. Research results show the predicted results by FEM match the experimental results very well. In the condition of different welding heat input, the welding heat input play an important role on welding distortion. While, material properties of stainless steel play a larger role on welding distortion when welding heat input is same. Further, for bead on plate welding of thin plate, both large distortion theory and small distortion theory are computed. The results show that using large distortion theory is more accurate in prediction welding distortion on thin plate welding.

Key concepts: Welding, Distortion (music), Materials science, Finite element method, Electric resistance welding, Heat-affected zone, Metallurgy, Structural engineering

Related papers

Back to paper searchBrowse research topicsOriginal source
Prediction of Welding Distortion in 304 Stainless Steel — Research Paper | ScholarLens