Applying a DOE-ACO Multi-Objective Approach toward Topology Optimization

Thin-walled structures play an important role in absorbing the energy in a low impact crash of vehicles up to saving lives from high impact injury. In this paper, the thin-walled columns by using a hybrid Design of Experiments (DOE) and Ant Colony Optimization (ACO) algorithm has been optimized. The analysis of the behavior of the nonlinear models under bending load is done using finite element ABAQUS software. The objective is to study the performance of geometrical parameters of the columns using DOE-ACO approach. DOE method is applied to determine the effects of cross-sections, material, and thickness on the energy absorption; and the ACO method is used for finding more accurate thickness on energy absorption. Four types of thinwalled cross-sections, i.e., circle, ellipse, hexagon, and square are used in this study. The optimized results of DOE method show that aluminum alloy (Al-6061) and high strength low alloy steel (HSLA) square columns have a higher energy absorption in comparison with the other crosssections. However, the amount of absorbed energy in two types of columns is equal but, 50 percent weight reduction may be seen in Al-6061 columns. The columns are re-optimized by ACO to find the best thickness in the last step. In the following, by topology optimization participation, a new plan is proposed by the same thickness and 50% less weight that has a higher crashworthiness efficiency by increasing Specific Absorbed Energy (SAE) more than 70%. As a result, this plan is bridging the gap between standard topological design and multi-criteria optimization.