Optimal Structural Topology Design for Energy Absorption: A Heuristic Approach

Author(s):  
Ciro A. Soto

Abstract A new approach to design the topology for structures under crash events is presented. The approach is heuristic in essence, but numerical experiments have shown its uses in real problems. Using an interpolation between porous and solid (non-porous) materials plus a re-design rule to by-pass gradient computations the new approach is able to determine better locations of material and density in a given structural domain for kinetic energy dissipation. An example is presented to illustrate the methodology.

2020 ◽  
Vol 46 ◽  
pp. 101162
Author(s):  
Dennis P.H. Claessens ◽  
Sjonnie Boonstra ◽  
Hèrm Hofmeyer

2000 ◽  
Vol 17 (6) ◽  
pp. 715-734 ◽  
Author(s):  
Qing Li ◽  
Grant P. Steven ◽  
Osvaldo M. Querin ◽  
Y.M. Xie

Author(s):  
Ciro A. Soto

This paper presents a methodology to perform structural topology design optimization for crashworthiness considering a prescribed and safe structural behavior through the dynamic equilibrium equation. This implementation, called here controlled crash behavior, or CCB, is very useful for design engineers in the automotive industry since it allows them to ‘prescribe’ a structural behavior of the vehicle at given locations of interest. The methodology is based on previous work from the author where the optimum topology is determined using a heuristic (optimality) criterion to attain a design with prescribed levels of plastic strains and stresses. The paper includes a simple beam example to demonstrate the CCB approach. Results are consistent with the formulation of the optimization problem.


Author(s):  
Xu Guo ◽  
Kang Zhao ◽  
Michael Yu Wang

In the present paper, a new approach for structural topology optimization based on implicit topology description function (TDF) is proposed. TDF is used to describe the shape/topology of a structure, which is approximated in terms of the nodal values. Then a relationship is established between the element stiffness and the values of the topology description function on its four nodes. In this way and with some non-local treatments of the design sensitivities, not only the shape derivative but also the topological derivative of the optimal design can be incorporated in the numerical algorithm in a unified way. Numerical experiments demonstrate that by employing this approach, the computational efforts associated with TDF (and level set) based algorithms can be saved. Clear optimal topologies and smooth structural boundaries free from any sign of numerical instability can be obtained simultaneously and efficiently.


1996 ◽  
Vol 118 (1) ◽  
pp. 89-98 ◽  
Author(s):  
C. D. Chapman ◽  
M. J. Jakiela

The genetic algorithm (GA), an optimization technique based on the theory of natural selection, is applied to structural topology design problems. After reviewing the genetic algorithm and previous research in structural topology optimization, we detail the chromosome-to-design representation which enables the genetic algorithm to perform structural topology optimization. Extending our prior investigations, this article first compares our genetic-algorithm-based technique with homogenization methods in the minimization of a structure’s compliance subject to a maximum volume constraint. We then use our technique to generate topologies combining high structural performance with a variety of material connectivity characteristics which arise directly from our discretized design representation. After discussing our findings, we describe potential future work.


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