A new graph-based parameterization concept aimed at the global optimization of laminated structures by the means of evolutionary algorithms and finite element analysis is introduced. The motivation to develop this novel parameterization concept is twofold. First, the entire design space is accessible to optimization down to the smallest entity, which is a single finite element, and secondly, this concept guarantees greatest flexibility in terms of laminate layer shape and placement. The finite element mesh of a structure is represented as a mathematical graph. Substructures of this graph form fiber reinforced and possibly overlapping patches and are affiliated to virtual graph vertices representing their properties. Adapted genetic variation operators are directly applied on this graph. The method allows for concurrent optimization of number, size, shape, and position of the patches and an arbitrary number of material related properties for each of them. The novel concept overcomes the limits of traditional geometry-based approaches, as it is able to represent almost arbitrary patch shapes even on curved surfaces. Two numerical examples demonstrate the efficiency of the method.

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Nickel-based super alloys are popular for applications in the energy and aerospace industries due to their excellent corrosion and high-temperature resistance. Direct metal deposition (DMD) of nickel alloys has reached technology readiness for several applications, especially for the repair of turbomachinery components. However, issues related to part quality and defect formation during the DMD process still persist. Laser remelting can effectively prevent and repair defects during metal additive manufacturing (AM); however, very few studies have focused on numerical modeling and experimental process parameter optimization in this context. Therefore, the aim of this study is to investigate the effect of determining the remelting process parameters via numerical simulation and experimental analyses in order to optimize an industrial process chain for part repair by DMD. A heat conduction model analyzed 360 different process conditions, and the predicted melt geometry was compared with observations from a fluid flow model and experimental single tracks for selected reference conditions. Subsequently, the remelting process was applied to a demonstrator repair case. The results show that the models can well predict the melt pool shape and that the optimized remelting process increases the bonding quality between base and DMD materials. Therefore, DMD part fabrication and repair processes can benefit from the remelting step developed here.