Abstract

As manufacturers strive to improve product performance and reduce weight, particularly in the transportation industries, designers are optimizing material usage with combinations of many different materials and alloys. The goal is to optimize mechanical behavior by selecting material specifically tailored for locations within a product or component. Such mixed material solutions require innovative joining technologies to combine, for example, aluminum and steel or magnesium and carbon fiber composite, etc. Critical to expanding the use of such joined materials in structural applications is the relevant technical understanding of how they form and deform across varying strain rates ranging from superplastic forming to stamping to crash events. With an increasingly rapid development of advanced materials, knowledge gained by assessing the post-weld formability of joined similar and multimaterial structures is crucial to providing the data needed to enable more widespread utilization. On the other end of the spectrum, increased insight characterizing the deformation of these joined structures is also critical to paving the way toward successful implementation. Characterizations via experimentation as well as predictive capabilities are essential to this effort as explored by the articles included in this issue. First, Judy Schneider and Ron Radzilowski provide a history of various processes for joining aluminum and iron-based materials in ‘‘Welding of Very Dissimilar Materials (Fe-Al).’’ They discuss how welding technologies were developed for specific families of materials followed by the joining of dissimilar materials and how such technologies are implemented in the automotive industry. Next, Mike Miles et al. describe efforts in modeling material deformation of advanced highstrength steels joined by friction stir spot welding. This work combines heat input from deformation as well as frictional heating from the welding process and relates processing parameters to microstructure and deformation behavior. The model was validated with experimental data and accurately predicted nugget geometry and thermal profiles.

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