Conference Agenda

With an aim to fill the gaps in the current 3D‐printing technology to digitally fabricate medical assistive devices with significant user benefit, well‐being, and availability; we develop a design methodology that enables the optimization of lightweight multi-material lattice structures in order to enhance the design of prostheses and rehabilitation devices. This is done by firstly developing a suitable multi-variable mathematical model for topology optimization of two-scale structures and secondly demonstrating it on an outer shaft of prostheses (lower limb prostheses shaft). We develop a two-scale gradient-based optimization algorithm procedure of multiple design variables that generates functionally graded structures having excellent performance. Our design methodology employs three families of predefined micro-structures that share similar geometric features. Those two additional families thwart the convergence of our gradient-based algorithm to the global minima and we aim at presenting a computational framework that enhances multi-variable optimizations by avoiding the unfavorable local minima.

Recently, there has been a development of innovative materials that imitate the strong and lightweight properties of natural structures, such as bones, honeycombs and sponges. These materials have a porous microstructure that alternates between solid and void, and are being used in various fields, especially in healthcare, thanks to advanced manufacturing techniques like 3D printing. However, the production time of 3D printed objects can vary depending on factors such as material rigidity, infill pattern, and printing parameters. To address this issue, a computational tool was developed, integrating numerical homogenization and topological optimization in ANSYS Mechanical. The study used computational homogenization to simulate the mechanical properties of the insoles' infill, investigating various infill patterns in terms of mechanical properties and printing performance. The calculated properties were assigned to the insoles' geometries, and different loading scenarios were analysed, considering therapeutic and usage frameworks. Using the results of these structural simulations, several topology optimization analyses were performed with the objective of reducing the frontal part of the insole's compliance while staying within a specified mass threshold. The study aimed to find a distribution of mass that minimized material use and printing time while maintaining a satisfactory structural response during insole insertion into the shoe. Additionally, this computational approach can optimize the material distribution in various orthopaedic devices, making 3D printing production more effective and reducing printing time.

Through recent advances in modern production techniques, particularly in the field of additive manufacturing, new previously unthinkable geometries have become feasible. This vast realm of new possibilities cannot be adequately addressed by classical methods in engineering, which is why numerical design techniques are becoming more and more valuable. In this context, this work aims to present concepts that exploit the emerging possibilities and facilitate numerical optimization.

The numerical optimization is built on a microstructured grid, where the geometry is constructed by means of functional composition between splines, resulting in a regular pattern of building blocks. Here, a macro-spline defines the outer contour, a micro-geometry sets the individual tiles and a parameter-spline controls the local parametrization of the microstructure, e.g., acting on the thickness or material density in a specific region. This approach opens up a broad design space, where the adaptivity of the resulting microstructure can be easily extended by increasing the number of control variables in the parameters-spline via h- or p-refinement. The geometric representation uses volume splines, on the one hand providing full compatibility with CAD/CAM and on the other hand facilitating the use of Isogeometric Analysis (IGA). To fully utilize the potential of this type of geometry parameterization, gradient-based optimization algorithms are employed in combination with analytical derivatives of the geometry and adjoint methods.

We will present first results in two fields of application, namely passive heat regulation and an elasticity problem. Here, we demonstrate how optimized microstructures can compensate for irregular boundary conditions and how compliance can be minimized using these lattice-like structures for major weight reduction.

This research has been supported by European Union's Horizon 2020 research and innovation program under agreement No. 862025.