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Modeling Spatially Varying Uncertainty in Composite Structures Using Lamination Parameters

C. Scarth, S. Adhikari, Sondipon Adhikari

AIAA Journal, Volume: 55, Issue: 11, Pages: 3951 - 3965

Swansea University Author: Sondipon Adhikari

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DOI (Published version): 10.2514/1.J055705

Abstract

An approach is presented for modeling spatially varying uncertainty in the ply orientations of composite structures. Lamination parameters are used with the aim of reducing the required number of random variables. Karhunen–Loève expansion is employed to decompose the uncertainty in each ply into a s...

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Published in: AIAA Journal
ISSN: 1533-385X
Published: 2017
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URI: https://cronfa.swan.ac.uk/Record/cronfa36669
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spelling 2017-11-09T12:40:57.8996571 v2 36669 2017-11-08 Modeling Spatially Varying Uncertainty in Composite Structures Using Lamination Parameters 4ea84d67c4e414f5ccbd7593a40f04d3 Sondipon Adhikari Sondipon Adhikari true false 2017-11-08 FGSEN An approach is presented for modeling spatially varying uncertainty in the ply orientations of composite structures. Lamination parameters are used with the aim of reducing the required number of random variables. Karhunen–Loève expansion is employed to decompose the uncertainty in each ply into a sum of random variables and spatially dependent functions. An intrusive polynomial chaos expansion is proposed to approximate the lamination parameters while preserving the separation of the random and spatial dependency. Closed-form expressions are derived for the expansion coefficients in two case studies; an initial example in which uncertainty is modeled using random variables, and a second random field example. The approach is compared against Monte Carlo simulation results for a variety of layups as well as closed-form expressions for the mean and covariance. By summing the polynomial chaos basis functions through the laminate thickness, the separation of the random and spatial dependency may be preserved at a laminate level and the number of random variables reduced for some minimum number of plies. The number of variables increases nonlinearly with the number of Karhunen–Loève expansion terms, and as such, the approach is only beneficial in low-order expansions using relatively few Karhunen–Loève expansion terms. Journal Article AIAA Journal 55 11 3951 3965 1533-385X 31 12 2017 2017-12-31 10.2514/1.J055705 COLLEGE NANME Science and Engineering - Faculty COLLEGE CODE FGSEN Swansea University 2017-11-09T12:40:57.8996571 2017-11-08T14:37:27.7110488 Faculty of Science and Engineering School of Engineering and Applied Sciences - Uncategorised C. Scarth 1 S. Adhikari 2 Sondipon Adhikari 3 0036669-09112017123948.pdf scarth2017.pdf 2017-11-09T12:39:48.2300000 Output 1628790 application/pdf Accepted Manuscript true 2017-11-09T00:00:00.0000000 false eng
title Modeling Spatially Varying Uncertainty in Composite Structures Using Lamination Parameters
spellingShingle Modeling Spatially Varying Uncertainty in Composite Structures Using Lamination Parameters
Sondipon Adhikari
title_short Modeling Spatially Varying Uncertainty in Composite Structures Using Lamination Parameters
title_full Modeling Spatially Varying Uncertainty in Composite Structures Using Lamination Parameters
title_fullStr Modeling Spatially Varying Uncertainty in Composite Structures Using Lamination Parameters
title_full_unstemmed Modeling Spatially Varying Uncertainty in Composite Structures Using Lamination Parameters
title_sort Modeling Spatially Varying Uncertainty in Composite Structures Using Lamination Parameters
author_id_str_mv 4ea84d67c4e414f5ccbd7593a40f04d3
author_id_fullname_str_mv 4ea84d67c4e414f5ccbd7593a40f04d3_***_Sondipon Adhikari
author Sondipon Adhikari
author2 C. Scarth
S. Adhikari
Sondipon Adhikari
format Journal article
container_title AIAA Journal
container_volume 55
container_issue 11
container_start_page 3951
publishDate 2017
institution Swansea University
issn 1533-385X
doi_str_mv 10.2514/1.J055705
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 - Uncategorised{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Engineering and Applied Sciences - Uncategorised
document_store_str 1
active_str 0
description An approach is presented for modeling spatially varying uncertainty in the ply orientations of composite structures. Lamination parameters are used with the aim of reducing the required number of random variables. Karhunen–Loève expansion is employed to decompose the uncertainty in each ply into a sum of random variables and spatially dependent functions. An intrusive polynomial chaos expansion is proposed to approximate the lamination parameters while preserving the separation of the random and spatial dependency. Closed-form expressions are derived for the expansion coefficients in two case studies; an initial example in which uncertainty is modeled using random variables, and a second random field example. The approach is compared against Monte Carlo simulation results for a variety of layups as well as closed-form expressions for the mean and covariance. By summing the polynomial chaos basis functions through the laminate thickness, the separation of the random and spatial dependency may be preserved at a laminate level and the number of random variables reduced for some minimum number of plies. The number of variables increases nonlinearly with the number of Karhunen–Loève expansion terms, and as such, the approach is only beneficial in low-order expansions using relatively few Karhunen–Loève expansion terms.
published_date 2017-12-31T03:45:59Z
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score 11.036116

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