No Cover Image

Journal article 1332 views 219 downloads

Effect of cutout on stochastic natural frequency of composite curved panels

S. Dey, T. Mukhopadhyay, S.K. Sahu, S. Adhikari, Sondipon Adhikari Orcid Logo

Composites Part B: Engineering, Volume: 105, Pages: 188 - 202

Swansea University Author: Sondipon Adhikari Orcid Logo

Check full text

DOI (Published version): 10.1016/j.compositesb.2016.08.028

Abstract

The present computational study investigates on stochastic natural frequency analyses of laminated composite curved panels with cutout based on support vector regression (SVR) model. The SVR based uncertainty quantification (UQ) algorithm in conjunction with Latin hypercube sampling is developed to...

Full description

Published in: Composites Part B: Engineering
ISSN: 1359-8368)
Published: 2016
Online Access: Check full text

URI: https://cronfa.swan.ac.uk/Record/cronfa29688
first_indexed 2016-09-01T12:52:38Z
last_indexed 2018-02-09T05:14:57Z
id cronfa29688
recordtype SURis
fullrecord <?xml version="1.0"?><rfc1807><datestamp>2017-03-01T12:02:25.8247136</datestamp><bib-version>v2</bib-version><id>29688</id><entry>2016-09-01</entry><title>Effect of cutout on stochastic natural frequency of composite curved panels</title><swanseaauthors><author><sid>4ea84d67c4e414f5ccbd7593a40f04d3</sid><ORCID>0000-0003-4181-3457</ORCID><firstname>Sondipon</firstname><surname>Adhikari</surname><name>Sondipon Adhikari</name><active>true</active><ethesisStudent>false</ethesisStudent></author></swanseaauthors><date>2016-09-01</date><deptcode>ACEM</deptcode><abstract>The present computational study investigates on stochastic natural frequency analyses of laminated composite curved panels with cutout based on support vector regression (SVR) model. The SVR based uncertainty quantification (UQ) algorithm in conjunction with Latin hypercube sampling is developed to achieve computational efficiency. The convergence of the present algorithm for laminated composite curved panels with cutout is validated with original finite element (FE) analysis along with traditional Monte Carlo simulation (MCS). The variations of input parameters (both individual and combined cases) are studied to portray their relative effect on the output quantity of interest. The performance of the SVR based uncertainty quantification is found to be satisfactory in the domain of input variables in dealing low and high dimensional spaces. The layer-wise variability of geometric and material properties are included considering the effect of twist angle, cutout sizes and geometries (such as cylindrical, spherical, hyperbolic paraboloid and plate). The sensitivities of input parameters in terms of coefficient of variation are enumerated to project the relative importance of different random inputs on natural frequencies. Subsequently, the noise induced effects on SVR based computational algorithm are presented to map the inevitable variability in practical field of applications.</abstract><type>Journal Article</type><journal>Composites Part B: Engineering</journal><volume>105</volume><paginationStart>188</paginationStart><paginationEnd>202</paginationEnd><publisher/><issnPrint>1359-8368)</issnPrint><keywords/><publishedDay>15</publishedDay><publishedMonth>11</publishedMonth><publishedYear>2016</publishedYear><publishedDate>2016-11-15</publishedDate><doi>10.1016/j.compositesb.2016.08.028</doi><url/><notes/><college>COLLEGE NANME</college><department>Aerospace, Civil, Electrical, and Mechanical Engineering</department><CollegeCode>COLLEGE CODE</CollegeCode><DepartmentCode>ACEM</DepartmentCode><institution>Swansea University</institution><apcterm/><lastEdited>2017-03-01T12:02:25.8247136</lastEdited><Created>2016-09-01T12:00:13.2319735</Created><path><level id="1">Faculty of Science and Engineering</level><level id="2">School of Engineering and Applied Sciences - Uncategorised</level></path><authors><author><firstname>S.</firstname><surname>Dey</surname><order>1</order></author><author><firstname>T.</firstname><surname>Mukhopadhyay</surname><order>2</order></author><author><firstname>S.K.</firstname><surname>Sahu</surname><order>3</order></author><author><firstname>S.</firstname><surname>Adhikari</surname><order>4</order></author><author><firstname>Sondipon</firstname><surname>Adhikari</surname><orcid>0000-0003-4181-3457</orcid><order>5</order></author></authors><documents><document><filename>0029688-01092016120103.pdf</filename><originalFilename>dey2016.pdf</originalFilename><uploaded>2016-09-01T12:01:03.2170000</uploaded><type>Output</type><contentLength>1726438</contentLength><contentType>application/pdf</contentType><version>Accepted Manuscript</version><cronfaStatus>true</cronfaStatus><embargoDate>2017-08-31T00:00:00.0000000</embargoDate><copyrightCorrect>false</copyrightCorrect></document></documents><OutputDurs/></rfc1807>
spelling 2017-03-01T12:02:25.8247136 v2 29688 2016-09-01 Effect of cutout on stochastic natural frequency of composite curved panels 4ea84d67c4e414f5ccbd7593a40f04d3 0000-0003-4181-3457 Sondipon Adhikari Sondipon Adhikari true false 2016-09-01 ACEM The present computational study investigates on stochastic natural frequency analyses of laminated composite curved panels with cutout based on support vector regression (SVR) model. The SVR based uncertainty quantification (UQ) algorithm in conjunction with Latin hypercube sampling is developed to achieve computational efficiency. The convergence of the present algorithm for laminated composite curved panels with cutout is validated with original finite element (FE) analysis along with traditional Monte Carlo simulation (MCS). The variations of input parameters (both individual and combined cases) are studied to portray their relative effect on the output quantity of interest. The performance of the SVR based uncertainty quantification is found to be satisfactory in the domain of input variables in dealing low and high dimensional spaces. The layer-wise variability of geometric and material properties are included considering the effect of twist angle, cutout sizes and geometries (such as cylindrical, spherical, hyperbolic paraboloid and plate). The sensitivities of input parameters in terms of coefficient of variation are enumerated to project the relative importance of different random inputs on natural frequencies. Subsequently, the noise induced effects on SVR based computational algorithm are presented to map the inevitable variability in practical field of applications. Journal Article Composites Part B: Engineering 105 188 202 1359-8368) 15 11 2016 2016-11-15 10.1016/j.compositesb.2016.08.028 COLLEGE NANME Aerospace, Civil, Electrical, and Mechanical Engineering COLLEGE CODE ACEM Swansea University 2017-03-01T12:02:25.8247136 2016-09-01T12:00:13.2319735 Faculty of Science and Engineering School of Engineering and Applied Sciences - Uncategorised S. Dey 1 T. Mukhopadhyay 2 S.K. Sahu 3 S. Adhikari 4 Sondipon Adhikari 0000-0003-4181-3457 5 0029688-01092016120103.pdf dey2016.pdf 2016-09-01T12:01:03.2170000 Output 1726438 application/pdf Accepted Manuscript true 2017-08-31T00:00:00.0000000 false
title Effect of cutout on stochastic natural frequency of composite curved panels
spellingShingle Effect of cutout on stochastic natural frequency of composite curved panels
Sondipon Adhikari
title_short Effect of cutout on stochastic natural frequency of composite curved panels
title_full Effect of cutout on stochastic natural frequency of composite curved panels
title_fullStr Effect of cutout on stochastic natural frequency of composite curved panels
title_full_unstemmed Effect of cutout on stochastic natural frequency of composite curved panels
title_sort Effect of cutout on stochastic natural frequency of composite curved panels
author_id_str_mv 4ea84d67c4e414f5ccbd7593a40f04d3
author_id_fullname_str_mv 4ea84d67c4e414f5ccbd7593a40f04d3_***_Sondipon Adhikari
author Sondipon Adhikari
author2 S. Dey
T. Mukhopadhyay
S.K. Sahu
S. Adhikari
Sondipon Adhikari
format Journal article
container_title Composites Part B: Engineering
container_volume 105
container_start_page 188
publishDate 2016
institution Swansea University
issn 1359-8368)
doi_str_mv 10.1016/j.compositesb.2016.08.028
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 The present computational study investigates on stochastic natural frequency analyses of laminated composite curved panels with cutout based on support vector regression (SVR) model. The SVR based uncertainty quantification (UQ) algorithm in conjunction with Latin hypercube sampling is developed to achieve computational efficiency. The convergence of the present algorithm for laminated composite curved panels with cutout is validated with original finite element (FE) analysis along with traditional Monte Carlo simulation (MCS). The variations of input parameters (both individual and combined cases) are studied to portray their relative effect on the output quantity of interest. The performance of the SVR based uncertainty quantification is found to be satisfactory in the domain of input variables in dealing low and high dimensional spaces. The layer-wise variability of geometric and material properties are included considering the effect of twist angle, cutout sizes and geometries (such as cylindrical, spherical, hyperbolic paraboloid and plate). The sensitivities of input parameters in terms of coefficient of variation are enumerated to project the relative importance of different random inputs on natural frequencies. Subsequently, the noise induced effects on SVR based computational algorithm are presented to map the inevitable variability in practical field of applications.
published_date 2016-11-15T12:58:02Z
_version_ 1821953944738332672
score 11.048149

Similar Items