Tuneable Continuous Topology Optimization Using Cartesian Grids
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Currently, Standard Topological Optimization tools are able to propose an optimal material distribution for the component, but when small topological details are required (i.e. trabecular-type structures) the computational cost becomes excessive. In order to overcome this drawback, the present work proposes a two-level topology optimization method in three main steps. The first one subdivides the whole component in cells and generates a coarse optimized low-definition material distribution through the well-known SIMP method. At this point, a range of density thresholds [ρmin, ρmax] have been prescribed in order to convert the cells with extreme relative densities into completely void or solid in the final solution. Thus, the manufacturing cost can be reduced and properly tuned by the designer. The second step uses an equilibrating technique that provides tractions continuity between adjacent cells, thus ensuring the material inter-cell continuity after the cells optimization process. Finally, each cell is optimized at fine scale taking as input data the densities and the equilibrated tractions obtained from the coarse problem via the SIMP method again. The main goal of this work is to obtain efficiently optimized trabecular structures using density-based methods, which would be unaffordable with standard computing facilities with the current methodologies.
