Optimized Supporting Structures for Small Artefacts: Generative Designed Prototypes

Retrievals of small and medium scale are one of the fundamental and most numerous parts of the entire museal heritage set. Their exposition represents an issue, looking for supporting structures that could be non-invasive, aesthetically pleasant, customized, and, last but not least, safe and stiff enough to avoid any damage to the artifacts. Through the usage of several engineering methods, starting from the retrieval and the exhibition requirements, optimized supporting structure can be developed. The procedure here reported and applied starts from the Reverse Engineering acquisition in order to obtain the 3D model of each retrieval, also comprehending color and texture information. After that, exhibition and preservation requirements, given by heritage experts, are translated into engineering requirements, with the usage of an immersive Virtual Reality environment. With these inputs, the developed Generative Design Method (GDM), using CAD, CAE and optimization tools synergically, can optimize the configuration of supporting interfaces with the artifact and then can generate a lightweight conceptual design through a generative design process. In this way, we can take into account all the given requirements, obtaining a lightweight support, topologically optimized, highly customized, non-invasive, possibly pleasant, able to resist in safety, and additively manufacturable. In this paper, the procedure is applied on different retrievals from Museo Civico dell’Agrocimino of Soriano nel Cimino, Italy, with different scales and materials, proving the robustness of the method.