Strumenti e Metodi di Progettazione per le Tecnologie Additive

The additive manufacturing (AM) technologies allow producing components layer upon layer in a completely different way with respect to the traditional techniques. This new approach in building the parts enables unprecedented design freedom; indeed, objects with complex shapes, cellular solids, internal features, and multiple materials can be easily produced. However, even though the manufacturing technologies are ready for producing such components, the literature emphasized that the available design tools are not appropriate and do not allow taking full advantage of the AM capabilities. For instance, the geometric modeling of structures with a lot of elements requires high computational resources, Boolean operations often fail, and the methods are not robust; the modeling of multi-material parts require new approaches able to describe the model at each point of the volume, and not only on the external surface. This research project aims to overcome some of the highlighted limitations by developing new geometric modeling methods suitable for exploiting the capabilities offered by AM. To reach the objective, several research topics have been addressed. Methods for the geometric modeling and optimization were proposed; approaches for the generation of conformal wireframes and for the size and multi-objective optimization of lattice structures were presented. A geometric modeling method based on meshes and subdivision surface algorithms that allows obtaining smooth surfaces without sharp edges was developed; more, the possibility of introducing internal walls and external skins to lattice structures was implemented. These approaches were then introduced in a more comprehensive optimization workflow for AM, dealing with the embodiment design phase and including the possibility of performing size and topology optimization. The proposed geometric mesh modeling method was then numerically validated, and experimental campaigns on both bulk samples and lattice structures produced by several powder bed fusion AM technologies were conducted. The results showed that the proposed mesh modeling method, together with the subdivision surface algorithm, is suitable to design lattice structures efficiently, requiring low computational resources and, at the same time, offering a good dimensional accuracy with respect to reference models. The C2 curvature continuity of the model allows reducing the stress concentration at the nodal points of the lattice if compared to similar structures obtained by traditional CAD software. Furthermore, the possibility of introducing internal walls makes it possible to create optimized ducts and paths and can locally modify the properties of the component. Due to the versatility of AM, the outcomes of the research can be adopted in different fields, as shown by the presented test cases: in the automotive field where lightweight and energy absorption components are used for reducing the fuel consumption and increasing the performance and safety of the vehicles; in the aerospace field, where lightweight components are required; in high-performance heat exchangers, microfluidic applications, and biomedical scaffolds where fluid dynamics plays a key role; and in consumer goods such as sports apparel and equipment.The additive manufacturing (AM) technologies allow producing components layer upon layer in a completely different way with respect to the traditional techniques. This new approach in building the parts enables unprecedented design freedom; indeed, objects with complex shapes, cellular solids, internal features, and multiple materials can be easily produced. However, even though the manufacturing technologies are ready for producing such components, the literature emphasized that the available design tools are not appropriate and do not allow taking full advantage of the AM capabilities. For instance, the geometric modeling of structures with a lot of elements requires high computational resources, Boolean operations often fail, and the methods are not robust; the modeling of multi-material parts require new approaches able to describe the model at each point of the volume, and not only on the external surface. This research project aims to overcome some of the highlighted limitations by developing new geometric modeling methods suitable for exploiting the capabilities offered by AM. To reach the objective, several research topics have been addressed. Methods for the geometric modeling and optimization were proposed; approaches for the generation of conformal wireframes and for the size and multi-objective optimization of lattice structures were presented. A geometric modeling method based on meshes and subdivision surface algorithms that allows obtaining smooth surfaces without sharp edges was developed; more, the possibility of introducing internal walls and external skins to lattice structures was implemented. These approaches were then introduced in a more comprehensive optimization workflow for AM, dealing with the embodiment design phase and including the possibility of performing size and topology optimization. The proposed geometric mesh modeling method was then numerically validated, and experimental campaigns on both bulk samples and lattice structures produced by several powder bed fusion AM technologies were conducted. The results showed that the proposed mesh modeling method, together with the subdivision surface algorithm, is suitable to design lattice structures efficiently, requiring low computational resources and, at the same time, offering a good dimensional accuracy with respect to reference models. The C2 curvature continuity of the model allows reducing the stress concentration at the nodal points of the lattice if compared to similar structures obtained by traditional CAD software. Furthermore, the possibility of introducing internal walls makes it possible to create optimized ducts and paths and can locally modify the properties of the component. Due to the versatility of AM, the outcomes of the research can be adopted in different fields, as shown by the presented test cases: in the automotive field where lightweight and energy absorption components are used for reducing the fuel consumption and increasing the performance and safety of the vehicles; in the aerospace field, where lightweight components are required; in high-performance heat exchangers, microfluidic applications, and biomedical scaffolds where fluid dynamics plays a key role; and in consumer goods such as sports apparel and equipment