crash testCrashworthiness

Ph.D. student: Chandan Mozumder,
Post-doc: Palani Ramu

The field of topology optimization has been developed extensively over the past two decades. In some respects, topology optimization can be viewed as a method for developing an initial, or concept design. The objective of traditional topology optimization is to redistribute the material within a specified design domain in order to maximize some desired mechanical performance under specified constraints. In topology sizing optimization, the objective is to redistribute element thickness to meet the desired performance constraints. The continuous design domain is discretized into a large number of finite elements whose densities/thicknesses are selectively altered to achieve the optimum performance. In this process, the number of elements and hence the number of the design variables depend on the size of the design domain and the desired resolution of the final structure. Classical gradient based optimization techniques seem to be impractical due to large number of design variables even for small design domains. Higher computational time and cost were major issues, which motivated the researchers to adopt specialized numerical methods such as approximation techniques, methods of moving asymptotes (MMA) and optimality criteria. However a relatively new approach for topology optimization has been inspired by a phenomenological model to simulate bone functional. This method is referred to as Hybrid Cellular Automaton (HCA) Algorithm. This method utilizes the cellular automata (CA) computing paradigm and nonlinear transient finite element analyses (FEA). In this method, the design domain is discretized into a regular lattice of CA. Each CA in the design domain is able to sense the internal energy density (IED) to within certain proximity. Depending upon the IED level, the CA then activates the process of increasing or decreasing the design variable to modify the structure around it. In the world of crashworthiness design, the design problems involve dynamic loading, such as impacts and collisions, geometric and material nonlinearities and the structures often undergo high plastic strains. The existing commercial thickness optimization tools utilize elastic models under static loading conditions because of the complexities associated with dynamic/impact loading. The HCA based topology optimization algorithm employs nonlinear transient analyses (via LS-Dyna) to capture material and geometric nonlinearities that occur during a dynamic crash event. Therefore by applying this method to impact problems, the resulting structure will account for all phenomena involved. The objective in crashworthiness design is to generate energy-absorbing structures, which can be obtained by uniformly distributing internal energy density (IED). The algorithm is able to generate energy absorbing concept designs, which can meet the given performance as well as manufacturing constraints, and also minimize the mass and cost simultaneously. This work facilitates the design of low-weight energy absorbing structures for application in automobile structural body parts for our collaborator Honda America R&D.