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Topological structural optimization is a powerful computational tool that enhances the structural efficiency of mechanical components. It achieves this by reducing mass without significantly altering stiffness. This study combines the Natural-Neighbour Radial-Point Interpolation Method (NNRPIM) with a bio-inspired bi-evolutionary bone-remodelling algorithm. This combination enables non-linear topological optimization analyses and achieves solutions with optimal stiffness-to-mass ratios. The NNRPIM discretizes the problem using an unstructured nodal distribution. Background integration points are constructed using the Delaunay triangulation concept. Nodal connectivity is then imposed through the natural neighbour concept. To construct shape functions, radial point interpolators are employed, allowing the shape functions to possess the delta Kronecker property. To evaluate the numerical performance of NNRPIM, its solutions are compared with those obtained using the standard Finite Element Method (FEM). The structural optimization process was applied to a practical example: a vehicle’s suspension control arm. This research is divided into two phases. In the first phase, the optimization algorithm is applied to a standard suspension control arm, and the results are closely evaluated. The findings show that NNRPIM produces topologies with suitable truss connections and a higher number of intermediate densities. Both aspects can enhance the mechanical performance of a hypothetical additively manufactured part. In the second phase, four models based on a solution from the optimized topology algorithm are analyzed. These models incorporate established design principles for material removal commonly used in vehicle suspension control arms. Additionally, the same models, along with a solid reference model, undergo linear static analysis under identical loading conditions used in the optimization process. The structural performance of the generated models is analyzed, and the main differences between the solutions obtained with both numerical techniques are identified. Full article

This work investigates the mechanical behaviour of sandwich beams with cellular cores using a multiscale approach combined with a meshless method, the Natural Neighbour Radial Point Interpolation Method (NNRPIM). The analysis is divided into two steps, aiming to analyse the efficiency of NNRPIM formulation when combined with homogenisation techniques for a multiscale computational framework of large-scale sandwich beam problems. In the first step, the cellular core material undergoes a controlled modification process in which circular holes are introduced into bulk polyurethane foam (PUF) to create materials with varying volume fractions. Subsequently, a homogenisation technique is combined with NNRPIM to determine the homogenised mechanical properties of these PUF materials with different porosities. In this step, NNRPIM solutions are compared with high-order FEM simulations. While the results demonstrate that RPIM can approximate high-order FEM solutions, it is observed that the computational cost increases significantly when aiming for comparable smoothness in the approximations. The second step applies the homogenised mechanical properties obtained in the first step to analyse large-scale sandwich beam problems with both homogeneous and functionally graded cores. The results reveal the capability of NNRPIM to closely replicate the solutions obtained from FEM analyses. Furthermore, an analysis of stress distributions along the beam thickness highlights a tendency for some NNRPIM formulations to yield slightly lower stress values near the domain boundaries. However, convergence towards agreement among different formulations is observed with mesh refinement. The findings of this study show that NNRPIM can be used as an alternative numerical method to FEM for analysing sandwich structures. Full article