Cargando…
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...
Autores principales: | , , |
---|---|
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 |
_version_ | 1783422548136951808 |
---|---|
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. |
format | Online Article Text |
id | pubmed-6540126 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
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 |
work_keys_str_mv | AT shijiajia akrigingsurrogatemodelforuncertaintyanalysisofgraphenebasedonafiniteelementmethod AT chuliu akrigingsurrogatemodelforuncertaintyanalysisofgraphenebasedonafiniteelementmethod AT braunrobin akrigingsurrogatemodelforuncertaintyanalysisofgraphenebasedonafiniteelementmethod AT shijiajia krigingsurrogatemodelforuncertaintyanalysisofgraphenebasedonafiniteelementmethod AT chuliu krigingsurrogatemodelforuncertaintyanalysisofgraphenebasedonafiniteelementmethod AT braunrobin krigingsurrogatemodelforuncertaintyanalysisofgraphenebasedonafiniteelementmethod |