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http://dx.doi.org/10.7734/COSEIK.2017.30.2.153

Topology Optimization based on Monte Carlo Analysis  

Kim, Dae Young (Department of Civil and Environmental Engineering, Sejong Univ.)
Noh, Hyuk Chun (Department of Civil and Environmental Engineering, Sejong Univ.)
Publication Information
Journal of the Computational Structural Engineering Institute of Korea / v.30, no.2, 2017 , pp. 153-158 More about this Journal
Abstract
In this paper, we take into account topology optimization problems considering spatial randomness in the material property of elastic modulus. Based on 88 lines MATLAB Code, Monte Carlo analysis has been performed for MBB(messerschmidt-$b{\ddot{o}}lkow$-blohm) model using 5,000 random sample fields which are generated by using the spectral representation scheme. The random elastic modulus is assumed to be Gaussian in the spatial domain of the structure. The variability of the volume fraction of the material, which affects the optimum topology of the given problem, is given in terms of correlation distance of the random material. When the correlation distance is small, the randomness in the topology is high and vice versa. As the correlation distance increases, the variability of the volume fraction of the material decreases, which comply with the feature of the linear static analysis. As a consequence, it is suggested that the randomness in the material property is need to be considered in the topology optimization.
Keywords
topology optimization; compliance; probabilistic analysis; correlation distance;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
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