Thin-walled structures are of great importance in automotive crashworthiness design, because of their high crash energy absorption capability and their high potential for light weighting. To identify the best compromise between these two requirements, numerical optimization is needed. Size and shape optimization is relatively well explored while topology optimization for crash is still an open issue. Hence, this paper proposes an approach based on hybrid cellular automata (HCA) for crashworthiness topology optimization with a special focus on thin-walled structures. First approaches have been published, e.g. Duddeck et al. (Struct Multidiscip Optim 54(3):415---428, 2016), using a simple rule to define the target mass for the inner loop of the HCA. To improve the performance, a modified scheme is proposed here for the outer optimization loop, which is based on a bi-section search with limited length. In the inner loop, hybrid updating rules are used to redistribute the mass and a mass correction technique is proposed to make the real mass converge to the target mass strictly. The efficiency and correctness of the proposed method is compared with LS-OPT for axial crash case. Two different methods of defining the target mass in the outer loop are studied, the proposed bi-section search with limited length shows its advantage in two types of three-point bending crash optimization cases. Another advantage of this method is that it requires no significantly increasing number of evaluations when the number of design variables increases. This is demonstrated by applying this method to a crashworthiness optimization problem with 380 design variables.

Improved hybrid cellular automata for crashworthiness optimization of thin-walled structures

This paper explores the effects of replacing the baseline steel with lightweight magnesium alloy parts on crashworthiness characteristics and optimum design of a full-vehicle model. Full frontal, offset frontal and side crash simulations are performed on a validated 1996 Dodge Neon model using explicit nonlinear transient dynamic finite element analyses in LS-DYNA to obtain vehicle responses such as crash pulse, intrusion distance, peak acceleration and internal energy. Twenty-two parts of the vehicle body structure are converted into AZ31 magnesium alloy with adjustable wall thickness while the remaining parts are kept intact. The magnesium alloy material model follows a piecewise linear plasticity law considering separate tension and compression properties and maximum plastic strain failure criterion. Six different metamodelling techniques including optimised ensemble are developed and tuned for predictions of crash-induced responses within the design optimisation process. The crashworthiness optimisati...

Crashworthiness optimisation of vehicle structures with magnesium alloy parts

Meta-heuristic and hyperheuristic algorithms are milestones that make the topology optimization practical for dynamic and nonlinear problems. However, researchers are continuing to improve these methods to get better results. Plastic behavior, complex deformation, and load-dependent material properties of the vehicle components during a crash event are challenging issues that are faced in this context. This research focuses on enhancing search efficiency of the hybrid cellular automata (HCA) algorithm with the aim of improving the energy absorption of vehicle structures exposed to high-impact collisions. An attempt is made to utilize an ideal amount of material in the structures to obtain a more uniform distribution of the plastic strain. Thus, the design is based on this criterion throughout the whole structure during the entire collision time. The variable neighborhood radius concept realizes an intelligent search strategy for the modified HCA (MHCA) algorithm. This innovation, applied here to topology optimization design, makes the MHCA algorithm more functional to controlling plastic strain energy. To confirm this, the crash analysis is performed using the finite-element software package LS-DYNA. An additional benefit of using this method is the quick and stable convergence while the energy absorption relative to the mass fraction is remarkably improved.

Topology optimization of energy absorbers under crashworthiness using modified hybrid cellular automata (MHCA) algorithm

Structural design for crashworthiness is a challenging area of research due to large plastic deformations and complex interactions among diverse components of the vehicle. Previous research in this field primarily focused on energy absorbing structures that utilise a desired amount of material. These structures have been shown to absorb a large amount of the kinetic energy generated during the crash event; however, the large plastic strains experienced can lead to material failure and loss of structural integrity. This research introduces a strain-based, dynamical multi-domain topology optimisation algorithm for crashworthy structures undergoing large deformations. This technique makes use of the hybrid cellular automaton framework, which combines transient, non-linear finite-element analysis and local control rules acting on cells. The set of all cells defines the design domain. In the proposed algorithm, the design domain is dynamically divided into two sub-domains for different objectives, i.e., high-strain sub-domain (HSSD) and low-strain sub-domain (LSSD). The distribution of these sub-domains is determined by a plastic strain limit value. During the design process, the material is distributed within the LSSD to distribute internal energy uniformly. In the HSSD, the material is distributed to satisfy a failure criterion given by a maximum strain value. Results show that the new formulation and algorithm are suitable for practical applications. The case study presented demonstrates the potential significance of this work for a wide range of engineering design problems.

Strain-based topology optimisation for crashworthiness using hybrid cellular automata

by Chandan K Mozumder The objective in crashworthiness design is to generate plastically deformable energy absorbing structures which can satisfy the prescribed force-displacement (FD) response The FD behavior determines the reaction force, displacement and the internal energy that the structure should withstand However, attempts to include this requirement in structural optimization problems remain scarce The existing commercial optimization tools utilize models under static loading conditions because of the complexities associated with dynamic/impact loading Due to the complexity of a crash event and the consequent time required to numerically analyze the dynamic response of the structure, classical methods (ie, gradient-based and direct) are not well developed to solve this undertaking This work presents an approach under the framework of the hybrid cellular automaton (HCA) method to solve the above challenge The HCA method has been successfully applied to nonlinear transient topology optimization for crashworthiness design In this work, the HCA algorithm has been utilized to develop an efficient methodology for synthesizing shell-based sheet metal structures with optimal material thickness distribution under a dynamic loading event using topometry optimization This method utilizes the cellular automata (CA) computing paradigm Chandan K Mozumder and nonlinear transient finite element analysis (FEA) via ls-dyna In this method, a set field variables is driven to their target states by changing a convenient set of design variables (eg, thickness) These rules operate locally in cells within a lattice that only know local conditions The field variables associated with the cells are driven to a setpoint to obtain the desired structure This methodology is used to design for structures with controlled energy absorption with specified buckling zones The peak reaction force and the maximum displacement are also constrained to meet the desired safety level according to passenger safety regulations Design for prescribed FD response by minimizing the error between the actual response and desired FD curve is implemented With the use of HCA rules, manufacturability constraints (eg, rolling) and structures which can be manufactured by special techniques, such as, tailor-welded blanks (TWB), have also been implemented This methodology is applied to shock-absorbing structural components for passengers in a crashing vehicle These results are compared to previous designs showing the benefits of the method introduced in this work

Topometry optimization of sheet metal structures for crashworthiness design using hybrid cellular automata

The hybrid cellular automaton (HCA) method has been successfully applied to nonlinear transient topology optimization for crashworthiness design. This method utilizes the cellular automata (CA) computing paradigm and nonlinear transient nite element analyses (FEA). The objective in crashworthiness design is to generate energy absorbing structures which can be obtained by uniformly distributing internal energy density (IED). In this paper, the HCA algorithm has been utilized to develop an ecien t methodology for synthesizing shell-based structures with optimal material thickness distribution under a dynamic loading event using a thickness based topology optimization. The objective of traditional topology optimization is to redistribute the material within a specied design domain in order to maximize some desired mechanical performance under specied constraints. In thickness based topology optimization, the objective is to redistribute element thickness to meet the desired performance constraints. This methodology is used to tackle complicated problems that involve dynamic events, such as impacts and collisions. The existing commercial thickness optimization tools utilize models under static loading conditions because of the complexities associated with dynamic/impact loading. The HCA based thickness 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 eectiv eness of the algorithm is demonstrated using a at plate and C-section rail example problem subjected to dynamic impact loading. The structures synthesized by the HCA algorithm are able to meet the manufacturing as well as performance constraints.

Thickness based Topology Optimization for Crashworthiness Design using Hybrid Cellular Automata

The hybrid cellular automaton (HCA) method has been successfully applied to nonlinear transient topology sizing optimization for crashworthiness design. This method utilizes the cellular automata (CA) computing paradigm and nonlinear transient nite element analyses (FEA). In earlier eorts, the HCA algorithm has been used to develop an ecien t methodology for synthesizing sheet metal structures with optimal material thickness distribution under a dynamic loading event using a thickness based topology sizing optimization. In thickness based topology optimization, the objective is to redistribute element thickness to meet the desired performance constraints. The objective in crashworthiness design is to generate energy absorbing structures which can be obtained by uniformly distributing internal energy density (IED). In this paper, the HCA algorithm is utilized to do simultaneous thickness and cost optimization for structures suitable to be manufactured by the tailor welded blank (TWB) technology for signican t mass savings. The sheet metal structure can have dieren t material parts, and the optimum distribution of the material and thickness is obtained to meet the desired performance using nonlinear transient analysis. This methodology is used to tackle complicated problems that involve dynamic events, such as impacts and collisions. The existing commercial thickness optimization tools utilize models under static loading conditions because of the complexities associated with dynamic/impact loading and they are not suitable for design with multiple material and thickness distribution simultaneously. The HCA based thickness optimization algorithm employs nonlinear transient analysis (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 eectiv eness of the algorithm is demonstrated using a at plate and C-section rail example problem subjected to single or multiple dynamic impact loading. The structures synthesized by the HCA algorithm are able to meet the manufacturing as well as performance constraints.

Cost and Mass Optimization for Crashworthiness Design of Shell-based Structure using Hybrid Cellular Automata

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Thickness based Topology Optimization for Crashworthiness Design using Hybrid Cellular Automata

Cost and Mass Optimization for Crashworthiness Design of Shell-based Structure using Hybrid Cellular Automata