Structural Topology optimization is attracting increasing attention as a complement to additive manufacturing techniques. The optimization algorithms usually employ continuum-based Finite Element analyses, but some important materials and processes are better described by discrete models, for example granular materials, powder-based 3D printing, or structural collapse. To address these systems, we adapt the established framework of SIMP Topology optimization to address a system modelled with the Discrete Element Method. We consider a typical problem of strain energy minimization, for which we define objective function and related sensitivity for the Discrete Element framework. The method is validated for simply supported beams discretized as interacting particles, whose predicted optimum solutions match those from a classical continuum-based algorithm. A parametric study then highlights the effects of mesh dependence and filtering. An advantage of the Discrete Element Method is that geometric nonlinearity is captured without additional complexity; this is illustrated when changing the beam supports from rollers to hinges, which indeed generates different optimum structures. The proposed Discrete Element Topology Optimization method enables future incorporation of nonlinear interactions, as well discontinuous processes such as during fracture or collapse.
Structural Topology Optimization typically features continuum-based descriptions of the investigated systems.In Part 1 we have proposed a Topology Optimization method for discrete systems and tested it on quasi-static 2D problems of energy minimization, assuming linear elastic material.However, discrete descriptions become particularly convenient in the failure and post-failure regimes, where discontinuous processes take place, such as fracture, fragmentation, and collapse. Here we take a first step towards failure problems, testing Discrete Element Topology Optimization for systems with nonlinear material responses. The incorporation of material nonlinearity does not require any change to the optimisation method, only using appropriately rich interaction potentials between the discrete elements. Three simple problems are analysed, to show how various combinations of material nonlinearity in tension and compression can impact the optimum geometries. We also quantify the strength loss when a structure is optimized assuming a certain material behavior, but then the material behaves differently in the actual structure. For the systems considered here, assuming weakest material during optimization produces the most robust structures against incorrect assumptions on material behavior. Such incorrect assumptions, instead, are shown to have minor impact on the serviceability of the optimized structures.
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