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Structural engineering in the automotive industry has moved towards weight reduction and passive safety whilst maintaining a good structural performance. The development of Additive Manufacturing (AM) technologies has boosted design freedom, leading to a wide range of geometries and integrating functionally-graded lattice structures. This paper presents three AM-oriented numerical optimization methods, aimed at optimizing components made of: i) bulk material, ii) a combination of bulk material and graded lattice structures; iii) an integration of solid, lattice and thin-walled structures. The optimization methods were validated by considering the steering column support of a mid-rear engine sports car, involving complex loading conditions and shape. The results of the three methods are compared, and the advantages and disadvantages of the solutions are discussed. The integration between solid, lattice thin-walled structures produced the best results, with a mass reduction of 49.7% with respect to the existing component.
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Mantovani et al. (2020) studied this question.
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