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- 저자 : Sareh Pooya (검색결과 2 건)
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Structural design with dynamic constraints using weighted chaos game optimization
Goodarzimehr Vahid,Talatahari Siamak,Shojaee Saeed,Hamzehei-Javaran Saleh,Sareh Pooya 한국CDE학회 2022 Journal of computational design and engineering Vol.9 No.6
The chaos game optimization (CGO) algorithm is a recently developed metaheuristic inspired by chaos theory and fractal configurations. In CGO, possible optimal solutions are defined as seeds and the searching process is performed using some simple equations. In this paper, weighted chaos game optimization (WCGO) is proposed and implemented to optimize engineering structures with dynamic constraints. In this method, an inertia weight coefficient based on the minimum and maximum values of the objective function is introduced to create a better balance between exploration and exploitation during the searching process. By applying the inertia weight coefficient to the seeds, their positions can be controlled accurately. To evaluate the performance of WCGO, a wide range of mathematical benchmark functions, as well as several structural design optimization problems under dynamic constraints, are computationally investigated using the new algorithm. In order to demonstrate the efficiency and robustness of WCGO, its results have been compared with those obtained by some conventional methods from the literature. Additionally, a Friedman rank test is conducted to perform a statistical study on the performance of the considered algorithms. The findings indicate that WCGO performs better than its rivals in solving these structural optimization problems with dynamic constraints.
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Intelligent computational design of scalene-faceted flat-foldable tessellations
Chen Yao,Lu Chenhao,Yan Jiayi,Feng Jian,Sareh Pooya 한국CDE학회 2022 Journal of computational design and engineering Vol.9 No.5
Origami tessellations can be folded from a given planar pattern into a three-dimensional object with specific geometric properties, inspiring developments in various fields of science and engineering such as deployable structures, energy absorption devices, reconfigurable robots, and metamaterials. However, the range of existing origami patterns with functional properties such as flat-foldability is rather scant, as analytical solutions to constraint equations arising in the design process are generally highly complicated. In this paper, we tackle the challenging problem of automated design of scalene-faceted flat-foldable origami tessellations using an efficient metaheuristic algorithm. To this end, this study establishes constraint curves based on compatibility conditions for all six-fold (i.e., degree-6) vertices. Subsequently, a graphical method and a particle swarm optimization (PSO) method are adopted to produce optimal origami patterns. Moreover, mountain-valley assignments for the obtained geometric designs are determined using a computational approach based on mixed-integer linear programming. It turns out that the flat-foldable internal vertices of each C2-symmetric unit fragment (UF) exist as C2-symmetric pairs about the centroid of the UF. Furthermore, numerical experiments are carried out to examine the feasibility and compare the accuracy, computational efficiency, and global convergence of the proposed methods. The results of numerical experiments demonstrated that, in comparison with the graphical method, the proposed PSO method has not only a higher accuracy but also a significantly lower computational cost, enabling us to develop an intelligent computational platform to efficiently design scalene-faceted flat-foldable origami tessellations.
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