No Cover Image

Journal article 608 views 99 downloads

Nonintrusive reduced order model for parametric solutions of inertia relief problems

Fabiola Cavaliere, Sergio Zlotnik, Rubén Sevilla Orcid Logo, Xabier Larráyoz, Pedro Díez

International Journal for Numerical Methods in Engineering, Volume: 122, Issue: 16, Pages: 4270 - 4291

Swansea University Author: Rubén Sevilla Orcid Logo

  • 56712.pdf

    PDF | Version of Record

    © 2021 The Authors. This is an open access article under the terms of the Creative Commons Attribution License

    Download (4.31MB)

Check full text

DOI (Published version): 10.1002/nme.6702

Abstract

The Inertia Relief (IR) technique is widely used by industry and produces equilibrated loads allowing to analyze unconstrained systems without resorting to the more expensive full dynamic analysis. The main goal of this work is to develop a computational framework for the solution of unconstrained p...

Full description

Published in: International Journal for Numerical Methods in Engineering
ISSN: 0029-5981 1097-0207
Published: Wiley 2021
Online Access: Check full text

URI: https://cronfa.swan.ac.uk/Record/cronfa56712
first_indexed 2021-04-21T07:38:32Z
last_indexed 2022-01-05T04:23:44Z
id cronfa56712
recordtype SURis
fullrecord <?xml version="1.0"?><rfc1807><datestamp>2022-01-04T17:42:34.0718294</datestamp><bib-version>v2</bib-version><id>56712</id><entry>2021-04-21</entry><title>Nonintrusive reduced order model for parametric solutions of inertia relief problems</title><swanseaauthors><author><sid>b542c87f1b891262844e95a682f045b6</sid><ORCID>0000-0002-0061-6214</ORCID><firstname>Rub&#xE9;n</firstname><surname>Sevilla</surname><name>Rub&#xE9;n Sevilla</name><active>true</active><ethesisStudent>false</ethesisStudent></author></swanseaauthors><date>2021-04-21</date><deptcode>ACEM</deptcode><abstract>The Inertia Relief (IR) technique is widely used by industry and produces equilibrated loads allowing to analyze unconstrained systems without resorting to the more expensive full dynamic analysis. The main goal of this work is to develop a computational framework for the solution of unconstrained parametric structural problems with IR and the Proper Generalized Decomposition (PGD) method. First, the IR method is formulated in a parametric setting for both material and geometric parameters. A reduced order model using the encapsulated PGD suite is then developed to solve the parametric IR problem, circumventing the so-called curse of dimensionality. With just one offline computation, the proposed PGD-IR scheme provides a computational vademecum that contains all the possible solutions for a predefined range of the parameters. The proposed approach is nonintrusive and it is therefore possible to be integrated with commercial finite element (FE) packages. The applicability and potential of the developed technique is shown using a three-dimensional test case and a more complex industrial test case. The first example is used to highlight the numerical properties of the scheme, whereas the second example demonstrates the potential in a more complex setting and it shows the possibility to integrate the proposed framework within a commercial FE package. In addition, the last example shows the possibility to use the generalized solution in a multi-objective optimization setting.</abstract><type>Journal Article</type><journal>International Journal for Numerical Methods in Engineering</journal><volume>122</volume><journalNumber>16</journalNumber><paginationStart>4270</paginationStart><paginationEnd>4291</paginationEnd><publisher>Wiley</publisher><placeOfPublication/><isbnPrint/><isbnElectronic/><issnPrint>0029-5981</issnPrint><issnElectronic>1097-0207</issnElectronic><keywords>inertia relief; nonintrusive; proper generalized decomposition; reduced order model; shape optimization</keywords><publishedDay>30</publishedDay><publishedMonth>8</publishedMonth><publishedYear>2021</publishedYear><publishedDate>2021-08-30</publishedDate><doi>10.1002/nme.6702</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>SU Library paid the OA fee (TA Institutional Deal)</apcterm><funders>UKRI Engineering and Physical Sciences Research Council; Generalitat de Catalunya; H2020 Marie Sk&#x142;odowska-Curie Actions; Ministerio de Econom&#xED;a y Competitividad</funders><projectreference>EP/P033997/1; 2017-SGR-1278; 764636; DPI2017-85139-C2-2-R</projectreference><lastEdited>2022-01-04T17:42:34.0718294</lastEdited><Created>2021-04-21T08:35:14.6937273</Created><path><level id="1">Faculty of Science and Engineering</level><level id="2">School of Aerospace, Civil, Electrical, General and Mechanical Engineering - Civil Engineering</level></path><authors><author><firstname>Fabiola</firstname><surname>Cavaliere</surname><order>1</order></author><author><firstname>Sergio</firstname><surname>Zlotnik</surname><order>2</order></author><author><firstname>Rub&#xE9;n</firstname><surname>Sevilla</surname><orcid>0000-0002-0061-6214</orcid><order>3</order></author><author><firstname>Xabier</firstname><surname>Larr&#xE1;yoz</surname><order>4</order></author><author><firstname>Pedro</firstname><surname>D&#xED;ez</surname><order>5</order></author></authors><documents><document><filename>56712__20585__c6b2a0261fb247eb88e8e9fb1be4489b.pdf</filename><originalFilename>56712.pdf</originalFilename><uploaded>2021-08-09T15:35:48.2354192</uploaded><type>Output</type><contentLength>4516613</contentLength><contentType>application/pdf</contentType><version>Version of Record</version><cronfaStatus>true</cronfaStatus><documentNotes>&#xA9; 2021 The Authors. This is an open access article under the terms of the Creative Commons Attribution License</documentNotes><copyrightCorrect>true</copyrightCorrect><language>eng</language><licence>http://creativecommons.org/licenses/by/4.0/</licence></document></documents><OutputDurs/></rfc1807>
spelling 2022-01-04T17:42:34.0718294 v2 56712 2021-04-21 Nonintrusive reduced order model for parametric solutions of inertia relief problems b542c87f1b891262844e95a682f045b6 0000-0002-0061-6214 Rubén Sevilla Rubén Sevilla true false 2021-04-21 ACEM The Inertia Relief (IR) technique is widely used by industry and produces equilibrated loads allowing to analyze unconstrained systems without resorting to the more expensive full dynamic analysis. The main goal of this work is to develop a computational framework for the solution of unconstrained parametric structural problems with IR and the Proper Generalized Decomposition (PGD) method. First, the IR method is formulated in a parametric setting for both material and geometric parameters. A reduced order model using the encapsulated PGD suite is then developed to solve the parametric IR problem, circumventing the so-called curse of dimensionality. With just one offline computation, the proposed PGD-IR scheme provides a computational vademecum that contains all the possible solutions for a predefined range of the parameters. The proposed approach is nonintrusive and it is therefore possible to be integrated with commercial finite element (FE) packages. The applicability and potential of the developed technique is shown using a three-dimensional test case and a more complex industrial test case. The first example is used to highlight the numerical properties of the scheme, whereas the second example demonstrates the potential in a more complex setting and it shows the possibility to integrate the proposed framework within a commercial FE package. In addition, the last example shows the possibility to use the generalized solution in a multi-objective optimization setting. Journal Article International Journal for Numerical Methods in Engineering 122 16 4270 4291 Wiley 0029-5981 1097-0207 inertia relief; nonintrusive; proper generalized decomposition; reduced order model; shape optimization 30 8 2021 2021-08-30 10.1002/nme.6702 COLLEGE NANME Aerospace, Civil, Electrical, and Mechanical Engineering COLLEGE CODE ACEM Swansea University SU Library paid the OA fee (TA Institutional Deal) UKRI Engineering and Physical Sciences Research Council; Generalitat de Catalunya; H2020 Marie Skłodowska-Curie Actions; Ministerio de Economía y Competitividad EP/P033997/1; 2017-SGR-1278; 764636; DPI2017-85139-C2-2-R 2022-01-04T17:42:34.0718294 2021-04-21T08:35:14.6937273 Faculty of Science and Engineering School of Aerospace, Civil, Electrical, General and Mechanical Engineering - Civil Engineering Fabiola Cavaliere 1 Sergio Zlotnik 2 Rubén Sevilla 0000-0002-0061-6214 3 Xabier Larráyoz 4 Pedro Díez 5 56712__20585__c6b2a0261fb247eb88e8e9fb1be4489b.pdf 56712.pdf 2021-08-09T15:35:48.2354192 Output 4516613 application/pdf Version of Record true © 2021 The Authors. This is an open access article under the terms of the Creative Commons Attribution License true eng http://creativecommons.org/licenses/by/4.0/
title Nonintrusive reduced order model for parametric solutions of inertia relief problems
spellingShingle Nonintrusive reduced order model for parametric solutions of inertia relief problems
Rubén Sevilla
title_short Nonintrusive reduced order model for parametric solutions of inertia relief problems
title_full Nonintrusive reduced order model for parametric solutions of inertia relief problems
title_fullStr Nonintrusive reduced order model for parametric solutions of inertia relief problems
title_full_unstemmed Nonintrusive reduced order model for parametric solutions of inertia relief problems
title_sort Nonintrusive reduced order model for parametric solutions of inertia relief problems
author_id_str_mv b542c87f1b891262844e95a682f045b6
author_id_fullname_str_mv b542c87f1b891262844e95a682f045b6_***_Rubén Sevilla
author Rubén Sevilla
author2 Fabiola Cavaliere
Sergio Zlotnik
Rubén Sevilla
Xabier Larráyoz
Pedro Díez
format Journal article
container_title International Journal for Numerical Methods in Engineering
container_volume 122
container_issue 16
container_start_page 4270
publishDate 2021
institution Swansea University
issn 0029-5981
1097-0207
doi_str_mv 10.1002/nme.6702
publisher Wiley
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 Aerospace, Civil, Electrical, General and Mechanical Engineering - Civil Engineering{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Aerospace, Civil, Electrical, General and Mechanical Engineering - Civil Engineering
document_store_str 1
active_str 0
description The Inertia Relief (IR) technique is widely used by industry and produces equilibrated loads allowing to analyze unconstrained systems without resorting to the more expensive full dynamic analysis. The main goal of this work is to develop a computational framework for the solution of unconstrained parametric structural problems with IR and the Proper Generalized Decomposition (PGD) method. First, the IR method is formulated in a parametric setting for both material and geometric parameters. A reduced order model using the encapsulated PGD suite is then developed to solve the parametric IR problem, circumventing the so-called curse of dimensionality. With just one offline computation, the proposed PGD-IR scheme provides a computational vademecum that contains all the possible solutions for a predefined range of the parameters. The proposed approach is nonintrusive and it is therefore possible to be integrated with commercial finite element (FE) packages. The applicability and potential of the developed technique is shown using a three-dimensional test case and a more complex industrial test case. The first example is used to highlight the numerical properties of the scheme, whereas the second example demonstrates the potential in a more complex setting and it shows the possibility to integrate the proposed framework within a commercial FE package. In addition, the last example shows the possibility to use the generalized solution in a multi-objective optimization setting.
published_date 2021-08-30T20:13:17Z
_version_ 1821437746039750656
score 11.047609

Similar Items