Mechanistic models for the forces in FSW of aluminum alloy 5052-H34

Friction stir welding (FSW) technique produces welded joints with better quality than most widely used welding methods. The absence of material melting and the small energy requirement are the main features of this process. Friction stir welding forces influence the process and its main phenomena. H...

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Bibliographic Details
Published in:International journal of advanced manufacturing technology 2018-06, Vol.96 (9-12), p.3993-4008
Main Authors: Quintana, Karen J., Silveira, Jose Luis
Format: Article
Language:English
Subjects:
Aluminum
Aluminum base alloys
Axial forces
CAE) and Design
Computer-Aided Engineering (CAD
Engineering
Friction stir welding
Industrial and Production Engineering
Inverse problems
Mathematical models
Mechanical Engineering
Media Management
Original Article
Parameter estimation
Process parameters
Welded joints
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Summary:Friction stir welding (FSW) technique produces welded joints with better quality than most widely used welding methods. The absence of material melting and the small energy requirement are the main features of this process. Friction stir welding forces influence the process and its main phenomena. However, models and experimental studies for the forces involved in FSW have received little attention. In this paper, the influence of the pin and shoulder on the axial force is separately considered and three models are developed to describe the axial force as a function of the tool geometry and the rotational, plunging, and welding speeds. The axial force is individually modeled for the plunging and welding phases. Additionally, a model is developed to describe the welding force as a function of rotational and welding speeds for the complete tool. The axial, welding, and transverse forces are measured during FSW experiments for different combinations of the main process parameters, and the results are used as input data for the estimation of the model parameters via inverse problem. The results showed a good agreement between the experimental data and the models.
ISSN:0268-3768
1433-3015
DOI:10.1007/s00170-018-1859-3