|dc.description.abstract||This thesis outlines a study on the multi-scale modeling and optimization of lightweight aluminum front rails for automotive crashworthiness applications. This research is aimed to enhance the crashworthiness characteristics of aluminum front crush rail for mass-production mid-size vehicles. Understanding the performance of these components during a collision is critical to the successful implementation of aluminum into crashworthiness applications. Accurate simulation of energy absorption structures during crush is a challenging task due to large and various strain paths that the structure undergoes during collapse. Material anisotropy that is introduced from manufacturing presents an additional complexity that affects the deformation development. Furthermore, current methods that predict a material's initial microstructure and the evolution are not feasible in a component-scale simulation due to current computational limitations. Thus, new knowledge in optimization with advanced constitutive modeling for crashworthiness is required.
In this thesis, optimization techniques, using artificial intelligence techniques (neural networks, genetic algorithms, and adaptive simulated annealing) are used to study and identify elastic-plastic characteristics that are best suited for energy absorption in axial crush. New definitions and analytical equations for crush efficiency and energy absorption are developed and calibrated with the axial crush simulations to develop a framework for optimal material selection for axial crush. This work shows that the yield stress increases the energy absorption, peak crush force and steady state crush force, while tending to decrease the crush efficiency. Lightweight alloys with a low yield stress that have significant work hardening capabilities outperform materials with a high yield stress and low work hardening in terms of energy absorption when a constraint is imposed on the peak crushing force.
The effects of anisotropy on the axial crush response are studied using advanced phenomenological constitutive models. Dynamic crush simulations of tubes are performed using different yield surface shapes calibrated to the same experimental anisotropy. Simulations of axial crush show that the yield surface shape affects the collapse mode and predicted energy absorption characteristics of the crush tube. The analysis indicates that the deformation is predominately controlled by balanced biaxial deformation. However, characterization of both the plane strain and pure shear points on the yield surface for energy absorption are also important. The shape and the area of the yield function governs the loading condition, which dictates the deformation and energy absorption.
A novel framework for structural optimization is developed to design an optimized front rail that maximizes crash energy absorption characteristics. The new design is coupled with material and process development to provide a component with superior energy absorption and strength characteristics that are commercially sustainable. Simulations are compared to the dynamic crush results for this new design. The size of the structure is optimized using the response surface methodology to enhance the specific energy absorption (SEA) of the structure. An analytical relationship that relates the SEA function to the crush efficiency is derived to show that a single optimization function parameter may be sufficient for mass minimization. The new optimization framework can increase the mean crush force and energy absorption by 21.9% and 26.7% more energy absorption than baseline geometries. Coupling the optimization framework with advanced constitutive models to can further enhance the energy absorption characteristics energy absorption and mean crush force of +4.2% and +2.5% respectively. Relaxing mass constraints, combined with anisotropic yield functions, can enhance SEA by +10%.
Finally, a framework for multi-scale modeling that bridges crystal plasticity to phenomenological plasticity is developed to study the significance of microstructural evolution on the enhancement of aluminum structures. Crystal plasticity is used to calibrate yield functions and microstructural evolution through the phenomenological-based texture evolution (PBTE) model. Simulations show that microstructural evolution can impact localization behaviour and ultimately, the energy absorption behaviour of the structure. The results of this thesis highlight the importance of coupling mechanical properties, such as initial anisotropy, microstructure evolution and flow stress behaviour with optimization of axial crush rails.||en