Hybrid Modelling Approach for Investigating the Thermal Contact during Solid State Joining

Abstract:

In FSW modelling, two major approaches have been used to describe the heat loss from the workpiece to the backing bar. The first method simplifies the heat loss using a convective transfer and has been used by some researchers such as Khandkar et al.[1]. The second method uses a contact gap conductance to represent the imperfect contact at the interface between the workpiece and the backing bar [1-3]. The contact gap conductance, k is defined as: k = Q/(T₀-T_A), where Q is the heat flux from the workpiece to the backing bar, T_O is the temperature of the workpiece and T_A is the temperature of the backing bar. Khandkar et al.[1] found that using the contact gap conductance method was more accurate than the convective heat transfer coefficient. Both Simar et al.[2], Colegrove and Shercliff [3] and Shi et al.[4] have used a variable contact gap conductance in their models. Shi et al.[4] applied a temperature dependent contact gap conductance method where the value increased with temperature to simulate the better contact under the tool. This paper combined the FSW process model with Artificial Neural Network (ANN) models to find the temperature dependent contact gap conductance k which is named as a hybrid models.

• Periodical: Materials Science Forum (Volumes 783-786)
• Pages: 2225-2230
• DOI: https://doi.org/10.4028/www.scientific.net/MSF.783-786.2225
• Online since: May 2014
• Authors: Hua Wang*, Paul A. Colegrove, Jorge Fernandez Dos Santos
• Keywords: Artificial Neural Network (ANN), Computational Fluid Dynamics (CFD), Contact Gap Conductance, Modelling of Friction Stir Welding, Plunge Depth

References

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