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A Kriging Surrogate Model for Uncertainty Analysis of Graphene Based on a Finite Element Method

Due to the inevitable presence of random defects, unpredictable grain boundaries in macroscopic samples, stress concentration at clamping points, and unknown load distribution in the investigation of graphene sheets, uncertainties are crucial and challenging issues that require more exploration. The...

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Detalles Bibliográficos
Autores principales: Shi, Jiajia, Chu, Liu, Braun, Robin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6540126/
https://www.ncbi.nlm.nih.gov/pubmed/31085983
http://dx.doi.org/10.3390/ijms20092355
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author Shi, Jiajia
Chu, Liu
Braun, Robin
author_facet Shi, Jiajia
Chu, Liu
Braun, Robin
author_sort Shi, Jiajia
collection PubMed
description Due to the inevitable presence of random defects, unpredictable grain boundaries in macroscopic samples, stress concentration at clamping points, and unknown load distribution in the investigation of graphene sheets, uncertainties are crucial and challenging issues that require more exploration. The application of the Kriging surrogate model in vibration analysis of graphene sheets is proposed in this study. The Latin hypercube sampling method effectively propagates the uncertainties in geometrical and material properties of the finite element model. The accuracy and convergence of the Kriging surrogate model are confirmed by a comparison with the reported references. The uncertainty analysis for both Zigzag and Armchair graphene sheets are compared and discussed.
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spelling pubmed-65401262019-06-04 A Kriging Surrogate Model for Uncertainty Analysis of Graphene Based on a Finite Element Method Shi, Jiajia Chu, Liu Braun, Robin Int J Mol Sci Article Due to the inevitable presence of random defects, unpredictable grain boundaries in macroscopic samples, stress concentration at clamping points, and unknown load distribution in the investigation of graphene sheets, uncertainties are crucial and challenging issues that require more exploration. The application of the Kriging surrogate model in vibration analysis of graphene sheets is proposed in this study. The Latin hypercube sampling method effectively propagates the uncertainties in geometrical and material properties of the finite element model. The accuracy and convergence of the Kriging surrogate model are confirmed by a comparison with the reported references. The uncertainty analysis for both Zigzag and Armchair graphene sheets are compared and discussed. MDPI 2019-05-13 /pmc/articles/PMC6540126/ /pubmed/31085983 http://dx.doi.org/10.3390/ijms20092355 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Shi, Jiajia
Chu, Liu
Braun, Robin
A Kriging Surrogate Model for Uncertainty Analysis of Graphene Based on a Finite Element Method
title A Kriging Surrogate Model for Uncertainty Analysis of Graphene Based on a Finite Element Method
title_full A Kriging Surrogate Model for Uncertainty Analysis of Graphene Based on a Finite Element Method
title_fullStr A Kriging Surrogate Model for Uncertainty Analysis of Graphene Based on a Finite Element Method
title_full_unstemmed A Kriging Surrogate Model for Uncertainty Analysis of Graphene Based on a Finite Element Method
title_short A Kriging Surrogate Model for Uncertainty Analysis of Graphene Based on a Finite Element Method
title_sort kriging surrogate model for uncertainty analysis of graphene based on a finite element method
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6540126/
https://www.ncbi.nlm.nih.gov/pubmed/31085983
http://dx.doi.org/10.3390/ijms20092355
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