In recent decades, thin-walled composite components have been widely used in the automotive industry due to their high specific energy absorption. A large number of experimental and numerical studies have been conducted to characterize the energy absorption mechanism and failure criteria for different composite tubes. Their results indicate that the energy absorption characteristics depend highly on the failure modes that occur during the impact. And failure mechanism is dependent on fiber material, matrix material, fiber angle, the layout of the fibers, as well as the geometry of structure and load condition. In this paper, first, the finite element (FE) model of the CFRP tube was developed using the Tsai-Wu failure criterion to model the crush characteristics. The FE results were validated using the published experimental. Then, a series of FE simulations were conducted considering different fiber directions and the number of layers to generate enough data for constructing the GMDH-type neural network. The polynomial expression of the three outputs (energy absorption, maximum force, and critical buckling force) was extracted using the GMDH algorithm and was used to perform the Pareto-based multi-objective optimizations. Finally, the failure mechanism of the optimum design point was simulated in LS-DYNA. The main contribution of this study was to successfully model the CFRP tube and damage mechanism using appropriate material constitutive model’s parameters and present the multi-objective method to find the optimum crashworthy design of the CFRP tube.
A Study of Multi-Objective Crashworthiness Optimization of the Thin-Walled Composite Tube under Axial Load