Many metals used in modern engineering exhibit anisotropy. A common assumption when modelling anisotropic metals is that the level of anisotropy is fixed throughout the calculation. As it is well understood that processes such as cold rolling, forging or shock loading change the level of anisotropy, it is clear that this assumption is not accurate when dealing with large deformations. The aim of this project was to develop a tool capable to predict large deformations of a single crystal or crystalline aggregate of a metal of interest and able to trace an evolution of anisotropy within the material. The outcome of this project is a verified computational tool capable of predicting large deformations in metals. This computational tool is built on the Crystal Plasticity Finite Element Method (CPFEM). The CPFEM in this project is an implementation of an existing constitutive model, based on the crystal plasticity theory (the single crystal strength model), into the framework of the FEA software DYNA3D® . Accuracy of the new tool was validated for a large deformation of a single crystal of an annealed OFHC copper at room temperature. The implementation was also tested for a large deformation of a polycrystalline aggregate comprised of 512 crystals of an annealed anisotropic OFHC copper in a uniaxial compression and tension test. Here sufficient agreement with the experimental data was not achieved and further investigation was proposed in order to find out the cause of the discrepancy. Moreover, the behaviour of anisotropic metals during a large deformation was modelled and it was demonstrated that this tool is able to trace the evolution of anisotropy. The main benefit of having this computational tool lies in virtual material testing. This testing has the advantage over experiments in time and cost expenses. This tool and its future improvements, which were proposed, will allow studying evolution of anisotropy in FCC and BCC materials during dynamic finite deformations, which can lead to current material models improvement.

High Pressure Die Casting (HPDC) is low-cost technique for the mass production of complex, non-ferrous parts. Despite its benefits such as dimensional accuracy, surface quality and high production rate / some mechanical drawbacks limit use of HPDC in production of critical parts especially under dynamical loads. This study aims to improve impact resistance and surface hardness of die cast parts by means of tool steel inserts. These inserts act as a barrier between the impactor and die casting alloy, in order to avoid surface deformation and reduce stress localization which leads crack formation. Except the impact surface, whole insert is embedded into the die casting alloy by placing them on specially machined die casting molds prior to the metal injection. The mentioned method was evaluated by mechanical test and micro-examinations which were applied on AISI D2 tool steel inserted A518.0, A413.2 and Zamak5 alloy samples. To see the effect of inserts on energy absorbance under single destructive loads, both monolithic (conventional) and inserted (produced by mentioned technique) samples were subjected to Charpy impact test. In order to observe its behavior under non-destructive, cyclic, low velocity impacts / a dedicated real rifle part was produced by this method and tested in the real service loads. Explicit Finite Elemental Analysis was also carried out to understand how the inserts increases the energy absorbance and protect the die cast body by simulating both destructive and non-destructive impact loads. In addition to these, micro-examinations were also conducted especially on insert-die casting alloy interface for chemical and physical interactions, defects and stability. In regards of experimental findings, mechanical feasibility of the method was achieved. It was proved that steel inserts improve energy absorbance, stress distribution and impact-surface hardness of die cast products.

By applying the finite element approach to the design and analysis of the impact diffusion helmet, many helmet configurations were able to be analyzed. Initially it was important to determine what design variables had an influence on the impact reducing abilities of the helmet design. The helmet was run through a series of Abaqus simulations that determined that a design with two oval shaped channels running along the length of the helmet was best. Next, these options were optimized to generate the helmet that produced the greatest impact reduction. The optimization simulations determined that a helmet that pushed the channels as far from the impact zone as possible reported the lowest acceleration. This indicated that removing the channels from play was most advantageous from an impact reduction perspective. Finally, a 3-D printed experimental helmet was impact tested and compared to a 3-D printed control helmet. The experimental helmet brought the channels back into the impact zone in order to judge if they had a physical effect on the acceleration. Both the simulations and the subsequent physical testing indicated that the Impact Diffusion Helmet design has a negative influence on the concussion reducing properties of a football helmet.

In the automobile industry, there is a big push for the automotive car manufacturers to base engineering decisions on the results of Computer Aided Engineering (CAE) solutions, and to transform the prototyping and testing, from a costly iterative process to a final verification and validation step. The variability in components material properties and environmental conditions together with the lack of knowledge about the underlying physics of complex systems often make it impractical to make reliable predictions based on only deterministic CAE models. One such area is the CAE modelling of cast aluminium components. These cast aluminium components have gained a huge relevance in the automobile industries due to their commendable mechanical properties. The advantage of the cast aluminium alloys are being a well-established alloy system in manufacturing processes, their functional integrity and relatively low weight. However, the presence of pores and micro-voids obtained during the manufacturing process constitutes a specific material behaviour and establishes a challenge in modelling of the cast materials. Furthermore, the low ductility of the materialdemands for the advanced numerical model to predict the failure. The main focus of this master thesis work is to investigate modelling technique of a cast aluminium alloy component, a spring tower, for a drop tower test and validate the predicted behaviour with the physical test results. Volvo Car Corporation currently uses a material model provided by MATFEM for cast aluminium parts which are explored in this thesis work, to validate the material model for component level testing. The methodology used to achieve this objective was to develop a boundary condition to perform component level tests in the drop tower and to correlate these with the obtained results found by using various modelling techniques in the explicit solver LS-DYNA. Therefore, precise and realistic modelling of the drop tower is crucial because the simulation results can be influenced by major design changes. A detailed finite element model for the spring tower has been developed from the observations made during the physical testing. The refined model showed good agreement with the existing model for the spring tower and observations from physical tests.