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http://dx.doi.org/10.7734/COSEIK.2022.35.6.351

Design Optimization for 3D Woven Materials Based on Regression Analysis  

Byungmo, Kim (Deputy Senior Surveyor, Ship and Offshore Technology Team)
Kichan, Sim (Department of Ship and Ocean Engineering, Korea University of Science and Technology)
Seung-Hyun, Ha (Department of Ocean Engineering, Korea Maritime and Ocean University)
Publication Information
Journal of the Computational Structural Engineering Institute of Korea / v.35, no.6, 2022 , pp. 351-356 More about this Journal
Abstract
In this paper, we present the regression analysis and design optimization for improving the permeability of 3D woven materials based on numerical analysis data. First, the parametric analysis model is generated with variables that define the gap sizes between each directional wire of the woven material. Then, material properties such as bulk modulus, thermal conductivity coefficient, and permeability are calculated using numerical analysis, and these material data are used in the polynomial-based regression analysis. The Pareto optimal solution is obtained between bulk modulus and permeability by using multi-objective optimization and shows their trade-off relation. In addition, gradient-based design optimization is applied to maximize the fluid permeability for 3D woven materials, and the optimal designs are obtained according to the various minimum bulk modulus constraints. Finally, the optimal solutions from regression equations are verified to demonstrate the accuracy of the proposed method.
Keywords
3D woven material; regression analysis; design optimization; parameterization; material property;
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Times Cited By KSCI : 2  (Citation Analysis)
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