Application of response surface methodology for optimization of hybrid friction diffusion bonding of tube-to-tube-sheet connections in coil-wound heat exchangers

• Main Authors: Diego Rafael Alba, Arne Roos, Georg Wimmer, Arnaldo Ruben Gonzalez, Stefanie Hanke, Jorge Fernandez dos Santos
• Format: Article
• Language: English
• Published: Elsevier 2019-04-01
• Series: Journal of Materials Research and Technology
• Online Access: http://www.sciencedirect.com/science/article/pii/S2238785418301522

This study evaluates the application of a new solid state joining process referred to as hybrid friction diffusion bonding. Based on heat processing and pressure, accelerated diffusion joins the materials. In the present study, two aluminum alloys were welded and characterized using leak tightness tests, tensile pull out tests, and metallographic analysis. Response surface methodology was used to optimize the tensile strength of single-hole tube-sheet samples. A Box–Behnken design was selected to evaluate the relations between the important process parameters and the ultimate tensile strength response to obtain optimal welding parameters. The data were analyzed with analysis of variance and were fitted to a second-order polynomial equation. The three-dimensional response surfaces derived from the mathematical models were applied to determine several optimum input parameters conditions. Under these conditions, the experimental ultimate tensile strength value was 202 MPa, which represents 95% of the base material strength. The experimental results obtained under optimum operating conditions were in agreement with the predicted values. Axial force was found to be the most significant factor affecting the joint strength followed by rotational speed. This can be attributed to their influence on the amount of mechanical energy introduced during the process, which is the parameter that primarily determines the joint strength. Keywords: Solid state welding, Hybrid friction diffusion bonding, 5XXX series aluminum, Box–Behnken design, Response surface methodology