Topology optimization with efficient rules of cellular automata

Bochenek, Bogdan; Tajs-Zielińska, Katarzyna

doi:10.1108/ec-03-2012-0064

Cited by 12 publications

(5 citation statements)

References 20 publications

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“…Generally, the type of topology optimization may be classified into two categories, i.e. topology optimization of discrete structures (Hajela and Lee, 1995; Rozvany, 1996) and topology optimization of continuum structures (Bendsøe and Kikuchi, 1988; Suzuki and Kikuchi, 1991; Xie and Steven, 1993, 1994, 1997; Andreassen et al , 2011; Huang and Xie, 2010; Zhu et al ., 2015; Wang et al ., 2003; Guest, 2015; Özkal and Uysal, 2016; Maleki and Shariat, 2015; Cai et al ., 2014; Bochenek and Tajs-Zielinska, 2013). The former is to search for the optimal spatial order and connectivity of the bars.…”

Section: Introductionmentioning

confidence: 99%

Robust topology optimization for continuum structures with random loads

Liu

Wen

Qing

et al. 2018

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Purpose This paper aims to tackle the challenge topic of continuum structural layout in the presence of random loads and to develop an efficient robust method. Design/methodology/approach An innovative robust topology optimization approach for continuum structures with random applied loads is reported. Simultaneous minimization of the expectation and the variance of the structural compliance is performed. Uncertain load vectors are dealt with by using additional uncertain pseudo random load vectors. The sensitivity information of the robust objective function is obtained approximately by using the Taylor expansion technique. The design problem is solved using bi-directional evolutionary structural optimization method with the derived sensitivity numbers. Findings The numerical examples show the significant topological changes of the robust solutions compared with the equivalent deterministic solutions. Originality/value A simple yet efficient robust topology optimization approach for continuum structures with random applied loads is developed. The computational time scales linearly with the number of applied loads with uncertainty, which is very efficient when compared with Monte Carlo-based optimization method.

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Section: Introductionmentioning

confidence: 99%

Robust topology optimization for continuum structures with random loads

Liu

Wen

Qing

et al. 2018

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“…In particular, this concept has been successfully applied to topology optimization, which was illustrated in a series of published papers, e.g., [26][27][28][29][30][31]. In particular, the efficiency of the Cellular Automata method is discussed in [32].…”

Section: Topology Optimization Using the Cellular Automata Methodsmentioning

confidence: 99%

CARMA—Cellular Automata with Refined Mesh Adaptation—The Easy Way of Generation of Structural Topologies

Tajs-Zielińska¹,

Bochenek²

2020

Applied Sciences

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This paper is focused on the development of a Cellular Automata algorithm with the refined mesh adaptation technique and the implementation of this algorithm in topology optimization problems. Traditionally, a Cellular Automaton is created based on regular discretization of the design domain into a lattice of cells, the states of which are updated by applying simple local rules. It is expected that during the topology optimization process the local rules responsible for the evaluation of cell states can drive the solution to solid/void resulting structures. In the proposed approach, the finite elements are equivalent to cells of an automaton and the states of cells are represented by design variables. While optimizing engineering structural elements, the important issue is to obtain well-defined solutions: in particular, topologies with smooth boundaries. The quality of the structural topology boundaries depends on the resolution level of mesh discretization: the greater the number of elements in the mesh, the better the representation of the optimized structure. However, the use of fine meshes implies a high computational cost. We propose, therefore, an adaptive way to refine the mesh. This allowed us to reduce the number of design variables without losing the accuracy of results and without an excessive increase in the number of elements caused by use of a fine mesh for a whole structure. In particular, it is not necessary to cover void regions with a very fine mesh. The implementation of a fine grid is expected mainly in the so-called grey regions where it has to be decided whether a cell becomes solid or void. The benefit of the proposed approach, besides the possibility of obtaining high-resolution, sharply resolved fine optimal topologies with a relatively low computational cost, is also that the checkerboard effect, mesh dependency, and the so-called grey areas can be eliminated without using any additional filtering. Moreover, the algorithm presented is versatile, which allows its easy combination with any structural analysis solver built on the finite element method.

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“…A characteristic feature of the CA is the modeling of complex systems using a simple set of local rules. This opportunity attracted researchers from various disciplines, such as physics, biology, social sciences, transport, logistics [5]. CA is a mathematical idealization of physical systems, in which the structure of image is divided into lattices of cells whose states are updated synchronously in discrete time according to some local rules.…”

Section: Methodical Issues Of Forecasting Changes In the Earth's Surfacementioning

confidence: 99%

Software Development for Assessment of the Vegetation Cover Changes Using the Earth Remote Sensing Data

Kovalev¹,

Ковалёв²,

Markov³

et al. 2018

J. Sib. Fed. Univ. Eng. technol.

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The article presents the results of software development for predictive maps modeling of the earth's surface processes based on time-varying satellite data using the probabilistic and spatial characteristics of various types of the earth's surface in the image. The analysis of existing methods for the assessment and modeling of the state of landscapes of various territories using satellite Earth monitoring data is presented. The review of existing systems of the earth's surface dynamics analysis and their main advantages and disadvantages is given. The cellular automata method was used to implement the forecast. This method allows complex systems modeling using a simple set of rules and is the most convenient and accurate method for working with a space images. Algorithms and basic modeling parameters for using this method are described. The developed software makes it possible to forecast the state of the surface of the territories under consideration based on a series of time-varying data, and also to specify various modeling parameters in order to improve the accuracy of forecast maps. The results of the developed software testing with MODIS and Landsat data are presented, the accuracy of the forecast and the influence of simulation parameters on the result were estimated.

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Topology optimization with efficient rules of cellular automata

Cited by 12 publications

References 20 publications

Robust topology optimization for continuum structures with random loads

Robust topology optimization for continuum structures with random loads

CARMA—Cellular Automata with Refined Mesh Adaptation—The Easy Way of Generation of Structural Topologies

Software Development for Assessment of the Vegetation Cover Changes Using the Earth Remote Sensing Data

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