scholarly journals 3-D modelling of the coaxial one-side resistance spot welding of AL5052/CFRP dissimilar material

2021 ◽  
Vol 68 ◽  
pp. 940-950
Author(s):  
Sendong Ren ◽  
Yunwu Ma ◽  
Ninshu Ma ◽  
Shuhei Saeki ◽  
Yoshiaki Iwamoto
Author(s):  
Sendong Ren ◽  
Yunwu Ma ◽  
Ninshu Ma ◽  
Qian Chen ◽  
Haiyuan Wu

Abstract In the present research, a digital twin of coaxial one-side resistance spot welding (COS-RSW) was established for the real-time prediction of transient temperature field. A 3D model of COS-RSW joint was developed based on the in-house finite element (FE) code JWRIAN-SPOT. The experimental verified FE model was employed to generate the big data of temperature of COS-RSW process. Multiple dimension interpolation was applied to process database and output prediction. The FE model can predict the thermal cycle on COS-RSW joints under different parameter couples. The interpolation effect of individual welding parameters was discussed and a power weight judgement for welding time was essential to ensure accuracy. With the support of big data, the digital twin can provide visualization prediction of COS-RSW within 10 seconds, whereas numerical modelling needs at least 1 hour. The proposed application of digital twin has potential to improve the efficiency of process optimization in engineering.


2020 ◽  
Vol 188 ◽  
pp. 108442
Author(s):  
Sendong Ren ◽  
Yunwu Ma ◽  
Shuhei Saeki ◽  
Yoshiaki Iwamoto ◽  
Ninshu Ma

2013 ◽  
Vol 7 (1) ◽  
pp. 114-119 ◽  
Author(s):  
Hitomi Nishibata ◽  
◽  
Shota Kikuchi ◽  
Manabu Fukumoto ◽  
Masato Uchihara

This paper describes a Single-Side resistance Spot Welding (SSSW) process which is expected to be a productive welding technology for the joining of stamped sheet panels to hollow parts for auto bodies. To obtain guidelines for making a sound weld with the SSSW process, the effects of welding parameters and the alignment of specimens on nugget growth are investigated experimentally. In addition, a numerical study is carried out to discuss the mechanism of nugget growth in the SSSW process.


2018 ◽  
Vol 32 (6) ◽  
pp. 390-398
Author(s):  
Nishibata Hitomi ◽  
Kikuchi Shota ◽  
Uchihara Masato ◽  
Yutaka S Sato ◽  
Kokawa Hiroyuki

2021 ◽  
Vol 1105 (1) ◽  
pp. 012055
Author(s):  
Imad M. Husain ◽  
Mursal Luaibi Saad ◽  
Osamah Sabah Barrak ◽  
Sabah Khammass Hussain ◽  
Mahmood Mohammed Hamzah

2016 ◽  
Vol 34 (1) ◽  
pp. 42-49
Author(s):  
Hitomi NISHIBATA ◽  
Shota KIKUCHI ◽  
Masato UCHIHARA ◽  
Yutaka S SATO ◽  
Hiroyuki KOKAWA

Author(s):  
Sendong Ren ◽  
Yunwu MA ◽  
Ninshu Ma

Abstract Coaxial one-side resistance spot welding (COS-RSW) is a newly developed process for joining metals and composites. In the present study, AL5052 and carbon-fiber-reinforced plastic (CFRP) lap joints were fabricated via COS-RSW. The welding process was modeled numerically using an in-house finite element code called JWRIAN. Single lap shear tests were performed to evaluate the joining strength. The molten zone diameter was defined and measured experimentally to verify the numerical model. An artificial neural network (ANN) was established based on multitask learning, and its training dataset was prepared via finite element analysis (FEA). The well-trained ANN was employed to generate a process window for the COS-RSW. Results demonstrated that the FEA could accurately reproduce the COS-RSW process, which served as an efficient tool for generating a process dataset without performing experiments. The ANN performed multitask learning well and predicted the welding output effectively. Furthermore, an index representing the average value of the maximum temperature in the molten interface of CFRP, was adopted to evaluate the contribution of the integral interface temperature field to the bonding strength qualitatively. An optimal value, which was close to the CFRP decomposition temperature of 340 °C, was obtained, and it exhibited an excellent correlation with higher bonding strengths. The process window provided welding parameters directly to yield the desired results.


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