Parameter Identification of Fractional Index Viscoelastic Model for Vegetable-Fiber Reinforced Composite
In the present work, parameters for adapting the behavior of the uniaxial three-element viscoelastic constitutive model with integer and fractional index derivatives to the mechanical evolution of an epoxy-composite material reinforced with long random henequen fibers, were determined. Cyclic loadin...
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description | In the present work, parameters for adapting the behavior of the uniaxial three-element viscoelastic constitutive model with integer and fractional index derivatives to the mechanical evolution of an epoxy-composite material reinforced with long random henequen fibers, were determined. Cyclic loading–unloading with 0.1%, 0.2%, 0.3%, …, 1.0% controlled strain and staggered fluency experiments at 5 MPa, 10 MPa, and 15 MPa constant tension were performed in stages, and the obtained data were used to determine and validate the model’s parameter values. The Inverse Method of Identification was used to calculate the parameters, and the Particle Swarm Optimization (PSO) method was employed to achieve minimization of the error function. A comparison between the simulated uniaxial results and the experimental data is demonstrated graphically. There exists a strong dependence between properties of the composite and the fiber content (0 wt%, 9 wt%, 14 wt%, 22 wt%, and 28 wt% weight percentage fiber/matrix), and therefore also of the model parameter values. Both uniaxial models follow the viscoelastic behavior of the material and the fractional index version presents the best accuracy. The latter method was noted to be adequate for determination of the aforementioned constants using non-large experimental data and procedures that are easy to implement. |
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Cyclic loading–unloading with 0.1%, 0.2%, 0.3%, …, 1.0% controlled strain and staggered fluency experiments at 5 MPa, 10 MPa, and 15 MPa constant tension were performed in stages, and the obtained data were used to determine and validate the model’s parameter values. The Inverse Method of Identification was used to calculate the parameters, and the Particle Swarm Optimization (PSO) method was employed to achieve minimization of the error function. A comparison between the simulated uniaxial results and the experimental data is demonstrated graphically. There exists a strong dependence between properties of the composite and the fiber content (0 wt%, 9 wt%, 14 wt%, 22 wt%, and 28 wt% weight percentage fiber/matrix), and therefore also of the model parameter values. Both uniaxial models follow the viscoelastic behavior of the material and the fractional index version presents the best accuracy. The latter method was noted to be adequate for determination of the aforementioned constants using non-large experimental data and procedures that are easy to implement.</description><identifier>ISSN: 2073-4360</identifier><identifier>EISSN: 2073-4360</identifier><identifier>DOI: 10.3390/polym14214634</identifier><identifier>PMID: 36365627</identifier><language>eng</language><publisher>Basel: MDPI AG</publisher><subject>Algorithms ; Composite materials ; Constitutive models ; Cyclic loads ; Deformation ; Epoxy resins ; Error functions ; Fiber composites ; Identification methods ; Inverse method ; Mathematical models ; Mathematical optimization ; Numerical analysis ; Optimization ; Parameter identification ; Particle swarm optimization ; Polymers ; Random variables ; Rheology ; Statistical analysis ; Vegetables ; Viscoelasticity ; Viscosity</subject><ispartof>Polymers, 2022-10, Vol.14 (21), p.4634</ispartof><rights>COPYRIGHT 2022 MDPI AG</rights><rights>2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). 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The latter method was noted to be adequate for determination of the aforementioned constants using non-large experimental data and procedures that are easy to implement.</description><subject>Algorithms</subject><subject>Composite materials</subject><subject>Constitutive models</subject><subject>Cyclic loads</subject><subject>Deformation</subject><subject>Epoxy resins</subject><subject>Error functions</subject><subject>Fiber composites</subject><subject>Identification methods</subject><subject>Inverse method</subject><subject>Mathematical models</subject><subject>Mathematical optimization</subject><subject>Numerical analysis</subject><subject>Optimization</subject><subject>Parameter identification</subject><subject>Particle swarm optimization</subject><subject>Polymers</subject><subject>Random variables</subject><subject>Rheology</subject><subject>Statistical analysis</subject><subject>Vegetables</subject><subject>Viscoelasticity</subject><subject>Viscosity</subject><issn>2073-4360</issn><issn>2073-4360</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><recordid>eNpdUcFOGzEQtVARQcCRu6Veelmw1147e6kURQ1EomqFgKtle8fBkXed2hsEf49DUNXUc_Bo5s2beTMIXVJyxVhLrjcxvPWU15QLxo_QaU0kqzgT5Ms__gRd5Lwm5fFGCCpP0IQJJhpRy1P0_Fsn3cMICS87GEbvvNWjjwOODi-StjtfB7wcOnjFTz7bCEHn0Vv8M3YQsIsJP8EKRm0CVAtvCtM9-KHELXR4HvtNzH6Ec3TsdMhw8fmfocfFj4f5bXX362Y5n91VljM6VqYVtoVGA5eOGmOZlG5qODgjSGskbwilNWjBplwU2XyqKeWdsbQWhNrOsTP0fc-72ZoeOls0JR3UJvlepzcVtVeHmcE_q1V8Ua1oOGtlIfj2SZDiny3kUfVFNYSgB4jbrGrJmqkUTdMW6Nf_oOu4TWVdHyguKRW8LqirPWqlA6jdZkpfW6yD3ts4gPMlPpNc7Pq3rBRU-wKbYs4J3N_pKVG7u6uDu7N3g2egoA</recordid><startdate>20221031</startdate><enddate>20221031</enddate><creator>Rodríguez Soto, Angel Alexander</creator><creator>Valín Rivera, José Luís</creator><creator>Sanabio Alves Borges, Lavinia María</creator><creator>Palomares Ruiz, Juan Enrique</creator><general>MDPI AG</general><general>MDPI</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7SR</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>D1I</scope><scope>DWQXO</scope><scope>HCIFZ</scope><scope>JG9</scope><scope>KB.</scope><scope>PDBOC</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>7X8</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0002-1584-6901</orcidid><orcidid>https://orcid.org/0000-0002-3410-4954</orcidid><orcidid>https://orcid.org/0000-0001-7754-7221</orcidid><orcidid>https://orcid.org/0000-0002-5512-9288</orcidid></search><sort><creationdate>20221031</creationdate><title>Parameter Identification of Fractional Index Viscoelastic Model for Vegetable-Fiber Reinforced Composite</title><author>Rodríguez Soto, Angel Alexander ; 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Cyclic loading–unloading with 0.1%, 0.2%, 0.3%, …, 1.0% controlled strain and staggered fluency experiments at 5 MPa, 10 MPa, and 15 MPa constant tension were performed in stages, and the obtained data were used to determine and validate the model’s parameter values. The Inverse Method of Identification was used to calculate the parameters, and the Particle Swarm Optimization (PSO) method was employed to achieve minimization of the error function. A comparison between the simulated uniaxial results and the experimental data is demonstrated graphically. There exists a strong dependence between properties of the composite and the fiber content (0 wt%, 9 wt%, 14 wt%, 22 wt%, and 28 wt% weight percentage fiber/matrix), and therefore also of the model parameter values. Both uniaxial models follow the viscoelastic behavior of the material and the fractional index version presents the best accuracy. The latter method was noted to be adequate for determination of the aforementioned constants using non-large experimental data and procedures that are easy to implement.</abstract><cop>Basel</cop><pub>MDPI AG</pub><pmid>36365627</pmid><doi>10.3390/polym14214634</doi><orcidid>https://orcid.org/0000-0002-1584-6901</orcidid><orcidid>https://orcid.org/0000-0002-3410-4954</orcidid><orcidid>https://orcid.org/0000-0001-7754-7221</orcidid><orcidid>https://orcid.org/0000-0002-5512-9288</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Algorithms Composite materials Constitutive models Cyclic loads Deformation Epoxy resins Error functions Fiber composites Identification methods Inverse method Mathematical models Mathematical optimization Numerical analysis Optimization Parameter identification Particle swarm optimization Polymers Random variables Rheology Statistical analysis Vegetables Viscoelasticity Viscosity |
title | Parameter Identification of Fractional Index Viscoelastic Model for Vegetable-Fiber Reinforced Composite |
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