Structural Optimization of Thin-Walled Tubular Structures for Progressive Collapse Using Hybrid Cellular Automaton with a Prescribed Response Field 2019-01-0837
The design optimization of thin-walled (TW) tubular structures is of relevance in automotive, naval and aerospace industries due to their low cost, ease of manufacturing and installation, and high-energy absorption efficiency. This study presents a methodology to design thin-walled (TW) structures for crashworthiness applications. The buckling behavior of TW components depends on several factors like the constitutive material, structural geometry, and loading conditions. Under impact loading, TW structures might undergo progressive buckling, global buckling or mixed buckling. For crashworthiness, the most desirable collapse mode is progressive buckling due to its stable progressive deformation, low peak crash force and high-energy absorption efficiency. Unfortunately, the possibility of obtaining progressive buckling is affected by the complexity of the TW component (material and geometry) and the impact angle. In a crash event, TW structures are often subjected to oblique impact that leads to global buckling. The design methodology presented in this paper expands the current state-of-art Hybrid Cellular Automata (HCA) formulations for crashworthiness by prescribing a response field that drives the optimization process. In this manner, the algorithm obtains designs whose response fields are similar to the initially prescribed field. Therefore, a suitable prescribed field generates designs with progressive collapse behavior. Additionally, the algorithm provides the capability of obtaining multifunctional TW components in which separate zones with high stiffness and progressive collapse can be defined. The nonlinear explicit finite element code LS-DYNA is used to simulate the TW structures under crash loading. The algorithm is used to design long straight and S-rail tubes whose crashworthiness characteristics are compared with linearly graded structures widely used in automotive applications.
Homero Valladares, Joel Najmon, Andres Tovar
Purdue University, Indiana Univ Purdue Univ Indianapolis