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J. Park, I. Kang, G. Noh, "Optimization of Design Parameters in Auxetic Lattice Structure for Relieving Surface Stress Concentrations", in B.H.V. Topping, P. Iványi, (Editors), "Proceedings of the Eleventh International Conference on Engineering Computational Technology", Civil-Comp Press, Edinburgh, UK, Online volume: CCC 2, Paper 4.9, 2022, doi:10.4203/ccc.2.4.9

Keywords: auxetic metamaterial, design optimization, deep neural network.

Abstract

An auxetic lattice structure with a negative Poisson’s ratio has excellent energy absorption and high fracture toughness. Unlike conventional metamaterials with Poisson’s ratio, the auxetic lattice structure has been used in various fields from biomechanics to industrial structural applications to improve mechanical properties. We aim to optimize the design parameters of the auxetic unit cell to minimize the stress concentrations on the surface of the metamaterial based on the analysis of the compressive mechanical behavior of the auxetic lattice structure. After parametrizing the design variables for three types of re-entrant structures, the maximum stress on the structure surface and the Poisson's ratio of the structure was measured through a finite element (FE) parametric study. The results of the FE parametric study were used as training and prediction data to construct an artificial neural network (ANN)-based FE surrogate model. Using the design optimization with a deep neural network (DNN)-based surrogate model, we proposed insights into the design parameters of the auxetic unit cell that minimize the surface stress concentrations.

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Front Page Browse CCC CCP CSETS CTR IJRT Other Authors Search Purchase Guide FAQ Contact us	Civil-Comp Conferences ISSN 2753-3239 CCC: 2 PROCEEDINGS OF THE ELEVENTH INTERNATIONAL CONFERENCE ON ENGINEERING COMPUTATIONAL TECHNOLOGY Edited by: B.H.V. Topping and P. Iványi Paper 4.9 Optimization of Design Parameters in Auxetic Lattice Structure for Relieving Surface Stress Concentrations J. Park, I. Kang and G. Noh doi:10.4203/ccc.2.4.9 Full Bibliographic Reference for this paper J. Park, I. Kang, G. Noh, "Optimization of Design Parameters in Auxetic Lattice Structure for Relieving Surface Stress Concentrations", in B.H.V. Topping, P. Iványi, (Editors), "Proceedings of the Eleventh International Conference on Engineering Computational Technology", Civil-Comp Press, Edinburgh, UK, Online volume: CCC 2, Paper 4.9, 2022, doi:10.4203/ccc.2.4.9 Keywords: auxetic metamaterial, design optimization, deep neural network. Abstract An auxetic lattice structure with a negative Poisson’s ratio has excellent energy absorption and high fracture toughness. Unlike conventional metamaterials with Poisson’s ratio, the auxetic lattice structure has been used in various fields from biomechanics to industrial structural applications to improve mechanical properties. We aim to optimize the design parameters of the auxetic unit cell to minimize the stress concentrations on the surface of the metamaterial based on the analysis of the compressive mechanical behavior of the auxetic lattice structure. After parametrizing the design variables for three types of re-entrant structures, the maximum stress on the structure surface and the Poisson's ratio of the structure was measured through a finite element (FE) parametric study. The results of the FE parametric study were used as training and prediction data to construct an artificial neural network (ANN)-based FE surrogate model. Using the design optimization with a deep neural network (DNN)-based surrogate model, we proposed insights into the design parameters of the auxetic unit cell that minimize the surface stress concentrations. download the full-text of this paper (PDF, 3 pages, 164 Kb) go to the previous paper go to the next paper return to the table of contents return to the volume description
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