Distributed sensing based real‐time process monitoring of shape memory polymer components
Shape memory polymer (SMP) materials have the capacity to undergo large deformations imposed by mechanical loading, hold a temporary shape, and then recover their original shape upon exposure to a particular external stimulus. The fiber reinforced shape memory polymer composites (SMPCs) with enhance...
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description | Shape memory polymer (SMP) materials have the capacity to undergo large deformations imposed by mechanical loading, hold a temporary shape, and then recover their original shape upon exposure to a particular external stimulus. The fiber reinforced shape memory polymer composites (SMPCs) with enhanced structural performances give a boost to breakthrough technologies for large‐scale engineering applications. This article presents a novel technique for distributed optical fiber sensor (DOFS) embedded SMPCs intended for real‐time process monitoring of large‐scale engineering applications such as deployable space structures. Herein a carbon fiber reinforced SMPC was tested under a three‐point flexural shape memory process and the DOFS data were acquired through optical backscatter reflectometry. Experiments were conducted in a temperature controlled thermal chamber coupled with a 10 kN electromechanical testing system. DOFSs offered unique advantages for spatially distributed dynamic temperature and strain measurements during the shape memory process. Compared to the standard test method dynamic mechanical analysis, larger samples can be tested effectively by using a single DOFS with large strain levels and shape complexity. The proposed technique demonstrated the ability of embedded DOFSs for in‐situ shape memory characterization such as shape fixity ratio, shape recovery ratio and recovery rate. This technique will eliminate the challenges hindering the process monitoring and performance evaluation of large SMPC components operating in their real working environments.
Shape memory polymer composites (SMPCs) have a wide range of applications from micro‐scale to large‐scale engineering. However, real‐time process monitoring and performance evaluation of SMPC components operating in their real working environment is challenging. This paper presents a novel technique for distributed optical fiber sensor embedded SMPCs. The heat transferring behaviors and the shape memory characteristics of the SMPC components can be determined by distributed sensing for any intended location over the embedded sensor length. |
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Shape memory polymer composites (SMPCs) have a wide range of applications from micro‐scale to large‐scale engineering. However, real‐time process monitoring and performance evaluation of SMPC components operating in their real working environment is challenging. This paper presents a novel technique for distributed optical fiber sensor embedded SMPCs. The heat transferring behaviors and the shape memory characteristics of the SMPC components can be determined by distributed sensing for any intended location over the embedded sensor length.</description><identifier>ISSN: 0021-8995</identifier><identifier>EISSN: 1097-4628</identifier><identifier>DOI: 10.1002/app.52247</identifier><language>eng</language><publisher>Hoboken, USA: John Wiley & Sons, Inc</publisher><subject>Aerospace environments ; applications ; Backscattering ; Carbon fibers ; characterization ; composites ; Data acquisition ; Dynamic mechanical analysis ; Fiber reinforced polymers ; Materials science ; Monitoring ; Optical fibers ; Performance evaluation ; Polymer matrix composites ; Polymers ; Recovery ; Shape memory ; stimuli‐sensitive polymers ; viscoelasticity</subject><ispartof>Journal of applied polymer science, 2022-06, Vol.139 (22), p.n/a</ispartof><rights>2022 Wiley Periodicals LLC.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c2977-5d6ea0318552e417ce1dcf603273736ca0888f7d90e76dce378973b880acdc753</citedby><cites>FETCH-LOGICAL-c2977-5d6ea0318552e417ce1dcf603273736ca0888f7d90e76dce378973b880acdc753</cites><orcidid>0000-0002-6796-0802</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1002%2Fapp.52247$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1002%2Fapp.52247$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>314,780,784,1417,27924,27925,45574,45575</link.rule.ids></links><search><creatorcontrib>Herath, Madhubhashitha</creatorcontrib><creatorcontrib>Emmanuel, Chris</creatorcontrib><creatorcontrib>Jeewantha, Janitha</creatorcontrib><creatorcontrib>Epaarachchi, Jayantha</creatorcontrib><creatorcontrib>Leng, Jinsong</creatorcontrib><title>Distributed sensing based real‐time process monitoring of shape memory polymer components</title><title>Journal of applied polymer science</title><description>Shape memory polymer (SMP) materials have the capacity to undergo large deformations imposed by mechanical loading, hold a temporary shape, and then recover their original shape upon exposure to a particular external stimulus. The fiber reinforced shape memory polymer composites (SMPCs) with enhanced structural performances give a boost to breakthrough technologies for large‐scale engineering applications. This article presents a novel technique for distributed optical fiber sensor (DOFS) embedded SMPCs intended for real‐time process monitoring of large‐scale engineering applications such as deployable space structures. Herein a carbon fiber reinforced SMPC was tested under a three‐point flexural shape memory process and the DOFS data were acquired through optical backscatter reflectometry. Experiments were conducted in a temperature controlled thermal chamber coupled with a 10 kN electromechanical testing system. DOFSs offered unique advantages for spatially distributed dynamic temperature and strain measurements during the shape memory process. Compared to the standard test method dynamic mechanical analysis, larger samples can be tested effectively by using a single DOFS with large strain levels and shape complexity. The proposed technique demonstrated the ability of embedded DOFSs for in‐situ shape memory characterization such as shape fixity ratio, shape recovery ratio and recovery rate. This technique will eliminate the challenges hindering the process monitoring and performance evaluation of large SMPC components operating in their real working environments.
Shape memory polymer composites (SMPCs) have a wide range of applications from micro‐scale to large‐scale engineering. However, real‐time process monitoring and performance evaluation of SMPC components operating in their real working environment is challenging. This paper presents a novel technique for distributed optical fiber sensor embedded SMPCs. The heat transferring behaviors and the shape memory characteristics of the SMPC components can be determined by distributed sensing for any intended location over the embedded sensor length.</description><subject>Aerospace environments</subject><subject>applications</subject><subject>Backscattering</subject><subject>Carbon fibers</subject><subject>characterization</subject><subject>composites</subject><subject>Data acquisition</subject><subject>Dynamic mechanical analysis</subject><subject>Fiber reinforced polymers</subject><subject>Materials science</subject><subject>Monitoring</subject><subject>Optical fibers</subject><subject>Performance evaluation</subject><subject>Polymer matrix composites</subject><subject>Polymers</subject><subject>Recovery</subject><subject>Shape memory</subject><subject>stimuli‐sensitive polymers</subject><subject>viscoelasticity</subject><issn>0021-8995</issn><issn>1097-4628</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><recordid>eNp1kL9OwzAQhy0EEqUw8AaWmBjSnu04dsaq_JUq0QEmBst1LpAqiYOdCmXjEXhGnoRAWZlOp_vu7qePkHMGMwbA57brZpLzVB2QCYNcJWnG9SGZjDOW6DyXx-Qkxi0AYxKyCXm-qmIfqs2ux4JGbGPVvtCNjWMX0NZfH5991SDtgncYI218W_U-_EC-pPHVdkgbbHwYaOfrocFAnW8632Lbx1NyVNo64tlfnZKnm-vH5V2yeri9Xy5WieO5UoksMrQgmJaSY8qUQ1a4MgPBlVAicxa01qUqckCVFQ6F0rkSG63BusIpKabkYn93TPm2w9ibrd-FdnxpeJZqSKXIYaQu95QLPsaApelC1dgwGAbmx50Z3ZlfdyM737PvVY3D_6BZrNf7jW_2anI4</recordid><startdate>20220610</startdate><enddate>20220610</enddate><creator>Herath, Madhubhashitha</creator><creator>Emmanuel, Chris</creator><creator>Jeewantha, Janitha</creator><creator>Epaarachchi, Jayantha</creator><creator>Leng, Jinsong</creator><general>John Wiley & Sons, Inc</general><general>Wiley Subscription Services, Inc</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7SR</scope><scope>8FD</scope><scope>JG9</scope><orcidid>https://orcid.org/0000-0002-6796-0802</orcidid></search><sort><creationdate>20220610</creationdate><title>Distributed sensing based real‐time process monitoring of shape memory polymer components</title><author>Herath, Madhubhashitha ; Emmanuel, Chris ; Jeewantha, Janitha ; Epaarachchi, Jayantha ; Leng, Jinsong</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c2977-5d6ea0318552e417ce1dcf603273736ca0888f7d90e76dce378973b880acdc753</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Aerospace environments</topic><topic>applications</topic><topic>Backscattering</topic><topic>Carbon fibers</topic><topic>characterization</topic><topic>composites</topic><topic>Data acquisition</topic><topic>Dynamic mechanical analysis</topic><topic>Fiber reinforced polymers</topic><topic>Materials science</topic><topic>Monitoring</topic><topic>Optical fibers</topic><topic>Performance evaluation</topic><topic>Polymer matrix composites</topic><topic>Polymers</topic><topic>Recovery</topic><topic>Shape memory</topic><topic>stimuli‐sensitive polymers</topic><topic>viscoelasticity</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Herath, Madhubhashitha</creatorcontrib><creatorcontrib>Emmanuel, Chris</creatorcontrib><creatorcontrib>Jeewantha, Janitha</creatorcontrib><creatorcontrib>Epaarachchi, Jayantha</creatorcontrib><creatorcontrib>Leng, Jinsong</creatorcontrib><collection>CrossRef</collection><collection>Engineered Materials Abstracts</collection><collection>Technology Research Database</collection><collection>Materials Research Database</collection><jtitle>Journal of applied polymer science</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Herath, Madhubhashitha</au><au>Emmanuel, Chris</au><au>Jeewantha, Janitha</au><au>Epaarachchi, Jayantha</au><au>Leng, Jinsong</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Distributed sensing based real‐time process monitoring of shape memory polymer components</atitle><jtitle>Journal of applied polymer science</jtitle><date>2022-06-10</date><risdate>2022</risdate><volume>139</volume><issue>22</issue><epage>n/a</epage><issn>0021-8995</issn><eissn>1097-4628</eissn><abstract>Shape memory polymer (SMP) materials have the capacity to undergo large deformations imposed by mechanical loading, hold a temporary shape, and then recover their original shape upon exposure to a particular external stimulus. The fiber reinforced shape memory polymer composites (SMPCs) with enhanced structural performances give a boost to breakthrough technologies for large‐scale engineering applications. This article presents a novel technique for distributed optical fiber sensor (DOFS) embedded SMPCs intended for real‐time process monitoring of large‐scale engineering applications such as deployable space structures. Herein a carbon fiber reinforced SMPC was tested under a three‐point flexural shape memory process and the DOFS data were acquired through optical backscatter reflectometry. Experiments were conducted in a temperature controlled thermal chamber coupled with a 10 kN electromechanical testing system. DOFSs offered unique advantages for spatially distributed dynamic temperature and strain measurements during the shape memory process. Compared to the standard test method dynamic mechanical analysis, larger samples can be tested effectively by using a single DOFS with large strain levels and shape complexity. The proposed technique demonstrated the ability of embedded DOFSs for in‐situ shape memory characterization such as shape fixity ratio, shape recovery ratio and recovery rate. This technique will eliminate the challenges hindering the process monitoring and performance evaluation of large SMPC components operating in their real working environments.
Shape memory polymer composites (SMPCs) have a wide range of applications from micro‐scale to large‐scale engineering. However, real‐time process monitoring and performance evaluation of SMPC components operating in their real working environment is challenging. This paper presents a novel technique for distributed optical fiber sensor embedded SMPCs. The heat transferring behaviors and the shape memory characteristics of the SMPC components can be determined by distributed sensing for any intended location over the embedded sensor length.</abstract><cop>Hoboken, USA</cop><pub>John Wiley & Sons, Inc</pub><doi>10.1002/app.52247</doi><tpages>11</tpages><orcidid>https://orcid.org/0000-0002-6796-0802</orcidid></addata></record> |
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subjects | Aerospace environments applications Backscattering Carbon fibers characterization composites Data acquisition Dynamic mechanical analysis Fiber reinforced polymers Materials science Monitoring Optical fibers Performance evaluation Polymer matrix composites Polymers Recovery Shape memory stimuli‐sensitive polymers viscoelasticity |
title | Distributed sensing based real‐time process monitoring of shape memory polymer components |
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