This paper presents results of comparison of two welding procedures’ influence on selected properties of the welded joints of high-strength low-alloyed steel (HSLA), specifically the impact toughness and the hardness distribution in the specific zones of “single V” butt multiple-pass welded joints. Based on results obtained from experiments, the two applied welding technologies were evaluated. They differ by the welding grove geometry and by the applied root pass welding procedure. Both procedures use MAG (Metal Active Gas) welding for execution of the filling and covering passes, while the root passes are executed by the MMA (Manual Metal Arc) procedure in the first case and by the MIG (Metal Inert Gas) procedure in the second. Experimentally obtained values of the fracture energy of the welded samples for both procedures were smaller than the values for the parent metal, which confirms the fact that welding causes degradation of the mechanical properties of HSLA steel; thus, any welding technology parameters must be so selected to mitigate this deficiency.

This research aims to show the effects of adding cardinality constraints to limit the number of different cross-sections used in simultaneous sizing and shape optimization of truss structures. The optimal solutions for sizing and shape optimized trusses result in a generally high, and impractical, number of different cross-sections being used. This paper presents the influence of constraining the number of different cross-sections used on the optimal results to bring the scientific results closer to the applicable results. The savings achieved using the cardinality constraint are expected to manifest in more than just the minimization of weight but in all the other aspects of truss construction, such as labor, assembly time, total weld length, surface area to be treated, transport, logistics, and so on. It is expected that the optimal weight of the structures would be greater than when not using this constraint; however, it would still be below conventionally sized structures and have the added benefits derived from the simplicity and elegance of the solution. The results of standard test examples for each different cardinality constraint value are shown and compared to the same examples using only a single cross-section on all bars and the overall optimal solution, which does not have the cardinality constraint. An additional comparison is made with results of just the sizing optimization from previously published research where authors first used the same cardinality constraint.

This research presents the additional benefits gained when using cardinality constraints in just sizing and combined sizing and shape optimization to find solutions with minimal weight while using a set number of different cross-sections allowed in the design. When limiting the number of cross-sections, an optimal solution can result in a structure with a reasonable number of different types of stock needed, unlike an approach which is unconstrained in this regard. This creates a more practical solution, which reduces the complexity of the solution and more resembles an experience-driven design, but with a lower overall weight than analytical solutions due to the optimization methods’ ability to explore practically the entire search space for a minimal weight solution. This limitation has adverse effects on the design. The downside is that the weight of the resulting structure is higher than the global optimum (one which disregards the number of different types or sizes of cross-sections used). However, it means that there are fewer different bar stock dimensions to be ordered, and less waste is created once the necessary pieces are cut from standard bar stock. The example used for these purposes is a typical optimization problem of a 17-bar truss with various numbers of different cross-sections used. The optimal solutions for this example were made using original software developed by the authors for the purposes of previously published research. Standard, available, bar stock dimensions were used in the optimization process in order to best resemble a real-world application. The results illustrate the added benefits of including fewer different bar stock types and the accompanying savings, which are indirectly created using this method.