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Stochastic static analysis of functionally graded sandwich nanoplates based on a novel stochastic meshfree computational framework

Baikuang Chen, Zhanjun Shao, Adesola Ademiloye Orcid Logo, Delei Yang, Xuebing Zhang, Ping Xiang

Advances in Engineering Software, Volume: 198

Swansea University Author: Adesola Ademiloye Orcid Logo

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DOI (Published version): 10.1016/j.advengsoft.2024.103780

Abstract

In this study, the spatial variability of materials is incorporated into the static analysis of functionally graded sandwich nanoplates to achieve higher accuracy. Utilising a modified point estimation method and the radial point interpolation method, we develop a novel stochastic meshfree computati...

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Published in: Advances in Engineering Software
ISSN: 0965-9978 1873-5339
Published: Elsevier 2024
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URI: https://cronfa.swan.ac.uk/Record/cronfa67875
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Utilising a modified point estimation method and the radial point interpolation method, we develop a novel stochastic meshfree computational framework to deal with the material uncertainty. Higher-order shear deformation theory is employed to establish the displacement field of the plates. The elastic modulus of ceramic and metal (Ec and Em) are treated as separate random fields and discretized through the Karhunen-Loève expansion (KLE) method. To improve the performance of procedure, the Wavelet-Galerkin method is introduced to solve the second type of Fredholm integral equation. Subsequently, substituting the random variables obtained by KLE into the stochastic computational framework, a high accuracy stochastic response of structures can be acquired. By comparing computed findings with those of Monte Carlo simulation, the accuracy and efficiency of developed framework are verified. Moreover, the results indicate that the plate's deflection exhibits varying sensitivities to the random fields Ec and Em. Also, the sandwich configuration as well as power-law exponents affect the stochastic response of structures. 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spelling v2 67875 2024-10-01 Stochastic static analysis of functionally graded sandwich nanoplates based on a novel stochastic meshfree computational framework e37960ed89a7e3eaeba2201762626594 0000-0002-9741-6488 Adesola Ademiloye Adesola Ademiloye true false 2024-10-01 EAAS In this study, the spatial variability of materials is incorporated into the static analysis of functionally graded sandwich nanoplates to achieve higher accuracy. Utilising a modified point estimation method and the radial point interpolation method, we develop a novel stochastic meshfree computational framework to deal with the material uncertainty. Higher-order shear deformation theory is employed to establish the displacement field of the plates. The elastic modulus of ceramic and metal (Ec and Em) are treated as separate random fields and discretized through the Karhunen-Loève expansion (KLE) method. To improve the performance of procedure, the Wavelet-Galerkin method is introduced to solve the second type of Fredholm integral equation. Subsequently, substituting the random variables obtained by KLE into the stochastic computational framework, a high accuracy stochastic response of structures can be acquired. By comparing computed findings with those of Monte Carlo simulation, the accuracy and efficiency of developed framework are verified. Moreover, the results indicate that the plate's deflection exhibits varying sensitivities to the random fields Ec and Em. Also, the sandwich configuration as well as power-law exponents affect the stochastic response of structures. These findings offer valuable insights for the optimized design of functionally graded sandwich nanoplates. Journal Article Advances in Engineering Software 198 Elsevier 0965-9978 1873-5339 Functionally graded sandwich nanoplate, radial point interpolation method, random field, Karhunen-Loève expansion method, modified point estimation method 1 12 2024 2024-12-01 10.1016/j.advengsoft.2024.103780 COLLEGE NANME Engineering and Applied Sciences School COLLEGE CODE EAAS Swansea University This work was funded by the Key R&D Projects of Hunan Province (No.2024AQ2018), the open fund of Shanghai High Performance Fibers and Composites Center and Center for Civil Aviation Composites, Donghua University, 2024, the 2023 Hunan Province Transportation Science and Technology Progress and Innovation Project (202305), the Henan Province Science and Technology Key Research Project (242102521034), the Hunan Provincial Natural Science Foundation Project (No. 2024JJ9067), Key Scientific Research Project of Hunan Provincial Department of Education, Project (21A0073), Taishan Program (tsqn202306278). 2024-10-04T10:20:54.6175078 2024-10-01T15:01:45.6778093 Faculty of Science and Engineering School of Engineering and Applied Sciences - Biomedical Engineering Baikuang Chen 1 Zhanjun Shao 2 Adesola Ademiloye 0000-0002-9741-6488 3 Delei Yang 4 Xuebing Zhang 5 Ping Xiang 6 67875__31527__9047a1f135ba465c9e725080c133a0a8.pdf 67875.pdf 2024-10-03T15:28:35.2097447 Output 1329872 application/pdf Accepted Manuscript true © 2024 The Author(s). Author accepted manuscript document released under the terms of a Creative Commons CC-BY licence using the Swansea University Research Publications Policy (rights retention). true eng https://creativecommons.org/licenses/by/4.0/
title Stochastic static analysis of functionally graded sandwich nanoplates based on a novel stochastic meshfree computational framework
spellingShingle Stochastic static analysis of functionally graded sandwich nanoplates based on a novel stochastic meshfree computational framework
Adesola Ademiloye
title_short Stochastic static analysis of functionally graded sandwich nanoplates based on a novel stochastic meshfree computational framework
title_full Stochastic static analysis of functionally graded sandwich nanoplates based on a novel stochastic meshfree computational framework
title_fullStr Stochastic static analysis of functionally graded sandwich nanoplates based on a novel stochastic meshfree computational framework
title_full_unstemmed Stochastic static analysis of functionally graded sandwich nanoplates based on a novel stochastic meshfree computational framework
title_sort Stochastic static analysis of functionally graded sandwich nanoplates based on a novel stochastic meshfree computational framework
author_id_str_mv e37960ed89a7e3eaeba2201762626594
author_id_fullname_str_mv e37960ed89a7e3eaeba2201762626594_***_Adesola Ademiloye
author Adesola Ademiloye
author2 Baikuang Chen
Zhanjun Shao
Adesola Ademiloye
Delei Yang
Xuebing Zhang
Ping Xiang
format Journal article
container_title Advances in Engineering Software
container_volume 198
publishDate 2024
institution Swansea University
issn 0965-9978
1873-5339
doi_str_mv 10.1016/j.advengsoft.2024.103780
publisher Elsevier
college_str Faculty of Science and Engineering
hierarchytype
hierarchy_top_id facultyofscienceandengineering
hierarchy_top_title Faculty of Science and Engineering
hierarchy_parent_id facultyofscienceandengineering
hierarchy_parent_title Faculty of Science and Engineering
department_str School of Engineering and Applied Sciences - Biomedical Engineering{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Engineering and Applied Sciences - Biomedical Engineering
document_store_str 1
active_str 0
description In this study, the spatial variability of materials is incorporated into the static analysis of functionally graded sandwich nanoplates to achieve higher accuracy. Utilising a modified point estimation method and the radial point interpolation method, we develop a novel stochastic meshfree computational framework to deal with the material uncertainty. Higher-order shear deformation theory is employed to establish the displacement field of the plates. The elastic modulus of ceramic and metal (Ec and Em) are treated as separate random fields and discretized through the Karhunen-Loève expansion (KLE) method. To improve the performance of procedure, the Wavelet-Galerkin method is introduced to solve the second type of Fredholm integral equation. Subsequently, substituting the random variables obtained by KLE into the stochastic computational framework, a high accuracy stochastic response of structures can be acquired. By comparing computed findings with those of Monte Carlo simulation, the accuracy and efficiency of developed framework are verified. Moreover, the results indicate that the plate's deflection exhibits varying sensitivities to the random fields Ec and Em. Also, the sandwich configuration as well as power-law exponents affect the stochastic response of structures. These findings offer valuable insights for the optimized design of functionally graded sandwich nanoplates.
published_date 2024-12-01T10:20:53Z
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score 11.031177

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