The Convergence and Algorithm Factors Analysis of Topology Optimization for Crashworthiness Based on Hybrid Cellular Automata

Author(s):  
LianShui Guo ◽  
Jun Huang ◽  
Xuan Zhou ◽  
Andres Tovar

Structural design for crashworthiness is a challenging area of research due to large plastic deformations and complex interactions among diverse components of the vehicle. A notable idea in topology optimization is the hybrid cellular automaton (HCA) method capable of topology synthesis for crashworthiness design. The HCA algorithm was inspired by the structural adaptation of bones to their ever changing mechanical environment. This methodology has been shown to be an effective topology synthesis tool. The objective of this investigation is to examine the convergence and algorithm factors analysis of topology optimization for crashworthiness based on hybrid cellular automata paradigm. The orthogonal test is also proposed to study the effects of the algorithm factors on the dependent variables of the structure with new optimized topology. To demonstrate the convergence properties influenced by factors of the HCA algorithm in dynamic problems, the HCA framework is developed to a methodology for crashworthiness, which combines transient, non-linear finite-element analysis and local control rules acting on cells, and some simple cantilevered beam examples are utilized.

2013 ◽  
Vol 135 (3) ◽  
Author(s):  
Soobum Lee ◽  
Andrés Tovar

An earlier study introduced the concept of piezoelectric energy-harvesting skin (EHS) to harvest energy by attaching thin piezoelectric patches onto a vibrating skin. This paper presents a methodology for the optimum design of EHS with the use of an efficient topology optimization method referred to as the hybrid cellular automaton (HCA) algorithm. The design domain of the piezoelectric material is discretized into cellular automata (CA), and the response of each CA is measured using high-fidelity finite-element analysis of a vibrating structure. The CA properties are parameterized using nonlinear interpolation functions that follow the principles of the SIMP model. The HCA algorithm finds the optimal densities and polarizing directions at each CA that maximize the output power from the EHS. The performance of this approach is demonstrated for the optimal design of EHS in two real-world case studies.


2006 ◽  
Vol 128 (6) ◽  
pp. 1205-1216 ◽  
Author(s):  
Andrés Tovar ◽  
Neal M. Patel ◽  
Glen L. Niebur ◽  
Mihir Sen ◽  
John E. Renaud

The hybrid cellular automaton (HCA) algorithm is a methodology developed to simulate the process of structural adaptation in bones. This methodology incorporates a distributed control loop within a structure in which ideally localized sensor cells activate local processes of the formation and resorption of material. With a proper control strategy, this process drives the overall structure to an optimal configuration. The controllers developed in this investigation include two-position, proportional, integral and derivative strategies. The HCA algorithm combines elements of the cellular automaton (CA) paradigm with finite element analysis (FEA). This methodology has proved to be computationally efficient to solve topology optimization problems. The resulting optimal structures are free of numerical instabilities such as the checkerboarding effect. This investigation presents the main features of the HCA algorithm and the influence of different parameters applied during the iterative optimization process.


2014 ◽  
Vol 8 (3) ◽  
pp. 365-375 ◽  
Author(s):  
Wonho Lee ◽  
◽  
Jinhoon Kim ◽  
Changbae Park

Foam shock-absorbing structures such as cushioned packages are often utilized to protect various products from mechanical shock and vibration during transportation. The goal of packaging design engineers is to design a cushioned package structure that improves the shock-absorbing performance and minimizes the volume of the package. Some optimization techniques, combined with computational simulation, provide engineers with a way to design an optimal structure. In this paper, we propose a modified topology optimization method suitable for a polymeric foam shock-absorbing structure under dynamic drop loads in multiple directions. Our approach uses a heuristic topology optimization method, known as the Hybrid Cellular Automata (HCA). The HCA algorithm uniformly distributes internal energy density and controls the relative density of Cellular Automata (CAs) making up the design space. This allows the algorithm to maintain or increase the performance of shock absorption and to decrease the amount of material. In particular, this paper presents a modified Solid IsotropicMaterial with Penalization (SIMP) model for foam materials, which parameterizes the design region and interpolates the material properties. We attempt to optimize a simple bottom-cushioned package for a refrigerator by using the proposed foam SIMP model with commercial software: LS-DYNA for drop dynamic simulation and LS-OPT/Topology for the HCA algorithm. Drop simulation and topology optimization are performed considering multiple drop-directions. As a result, our method removes elements that are not related to the shock-absorption performance and provide an optimal cushioning structure using foam material.


2009 ◽  
Vol 40 (1-6) ◽  
pp. 271-282 ◽  
Author(s):  
C. L. Penninger ◽  
L. T. Watson ◽  
A. Tovar ◽  
J. E. Renaud

2019 ◽  
Author(s):  
Sajjad Raeisi ◽  
Prasad Tapkir ◽  
Andres Tovar ◽  
Chandan Mozumder ◽  
Simon Xu

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