Advanced voxel-based CAD modelling for FSI simulations for automotive structures design

Additive Manufacturing (AM) is nowadays considered an important alternative to traditional manufacturing processes. AM technology shows several advantages in literature as design flexibility, and its use increases in automotive, aerospace and biomedical applications. As a systematic literature review suggests, AM is sometimes coupled with voxelization, mainly for representation and simulation purposes. Voxelization can be defined as a volumetric representation technique based on the model’s discretization with hexahedral elements, as occurs with pixels in the 2D image. Voxels are used to simplify geometric representation, store intricated details of the interior and speed-up geometric and algebraic manipulation. Compared to boundary representation used in common CAD software, voxel’s inherent advantages are magnified in specific applications such as lattice or topologically structures for visualization or simulation purposes. Those structures can only be manufactured with AM employment due to their complex topology. After an accurate review of the existent literature, this project aims to exploit the potential of the voxelization algorithm to develop optimized Design for Additive Manufacturing (DfAM) tools. The final aim is to manipulate and support mechanical simulations of lightweight and optimized structures that should be ready to be manufactured with AM with particular attention to automotive applications. A voxel-based methodology is developed for efficient structural simulation of lattice structures. Moreover, thanks to an optimized smoothing algorithm specific for voxel-based geometries, a topological optimized and voxelized structure can be transformed into a surface triangulated mesh file ready for the AM process. Moreover, a modified panel code is developed for simple CFD simulations using the voxels as a discretization unit to understand the fluid-dynamics performances of industrial components for preliminary aerodynamic performance evaluation. The developed design tools and methodologies perfectly fit the automotive industry’s needs to accelerate and increase the efficiency of the design workflow from the conceptual idea to the final product.

Molecular modelling of organic functional materials

The investigation of the mechanisms lying behind the (photo-)chemical processes is fundamental to address and improve the design of new organic functional materials. In many cases, dynamics simulations represent the only tool to capture the system properties emerging from complex interactions between many molecules. Despite the outstanding progresses in calculation power, the only way to carry out such computational studies is to introduce several approximations with respect to a fully quantum mechanical (QM) description. This thesis presents an approach that combines QM calculations with a classical Molecular Dynamics (MD) approach by means of accurate QM-derived force fields. It is based on a careful selection of the most relevant molecular degrees of freedom, whose potential energy surface is calculated at QM level and reproduced by the analytic functions of the force field, as well as by an accurate tuning of the approximations introduced in the model of the process to be simulated. This is made possible by some tools developed purposely, that allow to obtain and test the FF parameters through comparison with the QM frequencies and normal modes. These tools were applied in the modelling of three processes: the npi* photoisomerisation of azobenzene, where the FF description was extended to the excited state too and the non-adiabatic events were treated stochastically with Tully fewest switching algorithm; the charge separation in donors-acceptors bulk heterojunction organic solar cells, where a tight-binding Hamiltonian was carefully parametrised and solved by means of a code, also written specifically; the effect of the protonation state on the photoisomerisation quantum yield of the aryl-azoimidazolium unit of the axle molecule of a rotaxane molecular shuttle. In each case, the QM-based MD models that were specifically developed gave noteworthy information about the investigated phenomena, proving to be a fundamental key for a deeper comprehension of several experimental evidences.