PSI - Issue 37

Available online at www.sciencedirect.com Structural Int grity Procedia 00 (2019) 000 – 000 Available online at www.sciencedirect.com ScienceDirect Structural Integrity Procedia 00 (2019) 000 – 000 Available online at www.sciencedirect.com ScienceDirect

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Procedia Structural Integrity 37 (2022) 684–691

ICSI 2021 The 4th International Conference on Structural Integrity Identification of material properties of green laminate composite plates ICSI 2021 The 4th International Conference on Structural Integrity Identification of material properties of green laminate composite plates

using bio-inspired optimization algorithms A. F. F. Rodrigues a , J. V. Araújo dos Santos b* , H. Lopes c a Instituto Superior Tecnico, Universidade de Lisboa, Lisboa, Portugal b IDMEC, Instituto Superior Tecnico, Universidade de Lisboa, Lisboa, Portugal c DEM-ISEP, Instituto Politecnico do Porto, Porto, Portugal using bio-inspired optimization algorithms A. F. F. Rodrigues a , J. V. Araújo dos Santos b* , H. Lopes c a Instituto Superior Tecnico, Universidade de Lisboa, Lisboa, Portugal b IDMEC, Instituto Superior Tecnico, U iversidade de Lisb a, Lisbo , Portugal c DEM-ISEP, Instituto Politecnico do Porto, Porto, Portugal

© 2022 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0) Peer-review under responsibility of Pedro Miguel Guimaraes Pires Moreira Abstract This work proposes a non-destructive method for the identification of material properties of composite materials. The proposed optimization problems have for design variables the material elastic constants and make use of nature-inspired metaheuristic optimization algorithms. The objective functions relate experimental natural frequencies with computationally obtained ones. The nature-inspired metaheuristic optimization algorithms used are the: (1) Genetic algorithm, (2) Particle Swarm Optimization algorithm, (3) Grey Wolf Optimization algorithm, (4) Firefly algorithm, and (5) Cuckoo Search algorithm. The study is focused on laminated composite materials, whether they are synthetic fiber reinforced, such as glass fibers reinforced composites, or natural fibers reinforced like wooden fibers reinforced composites and plywood. The proposed method allows the identification of the elastic constants within an acceptable range compared to other methods, provided that enough natural frequencies are accurately measured. This method presents several advantages in comparison to other methods: (1) it does not require an initial guess of the elastic constants, (2) it does not need the gradient of the objective functions, and (3) it allows the identification of a large range of elastic constants of different materials due to its good adaptability and versatility. © 2022 The Authors. Published by ELSEVIER B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0) Peer-review under responsibility of Pedro Miguel Guimaraes Pires Moreira Abstract This work proposes a non-destructive method for the identification of material properties of composite materials. The proposed opti ization problems have for design variables the material elastic constants and make use of nature-inspired metaheuristic optimization algorithms. The objective functions relate experimental natural frequencies with computationally obtained ones. The nature-inspired metaheuristic optimization algorithms used are the: (1) Genetic algorithm, (2) Particle Swarm Optimization algorithm, (3) Grey Wolf Optimization algorithm, (4) Firefly algorithm, and (5) Cuckoo Search algorithm. The study is focused on laminated composite materials, whether they are synthetic fiber reinforced, such as glass fibers reinforced composites, or natural fibers reinforced like wooden fibers reinforced composites and plywood. The proposed method allows the identification of the elastic constants within an acceptable range compared to other methods, provided that enough natural frequencies are accurately measured. This method presents several advantages in comparison to other methods: (1) it does not require an initial guess of the elastic constants, (2) it does not need the gradient of the objective functions, and (3) it allows the identification of a large range of elastic constants of different materials due to its good adaptability and versatility. © 2022 The Authors. Published by ELSEVIER B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0) Peer-review under responsibility of Pedro Miguel Guimaraes Pires Moreira

Keywords: composite materials; green composites; elastic constants; nature-inspired optimization Keywords: composite materials; green composites; elastic constants; nature-inspired optimization

* Corresponding author. Tel.: +351 218419463; fax: 351 218417915. E-mail address: viriato@tecnico.ulisboa.pt * Correspon ing author. Tel.: +351 218419463; fax: 351 218417915. E-mail address: viriato@tecnico.ulisboa.pt

2452-3216 © 2022 The Authors. Published by ELSEVIER B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0) Peer-review under responsibility of Pedro Miguel Guimaraes Pires Moreira 2452-3216 © 2022 The Authors. Published by ELSEVIER B.V. This is an ope access article under the CC BY-NC-ND lic nse (https://creativecommons.org/licenses/by-nc-nd/4.0) Peer-review under responsibility of Pedro Miguel Guimaraes Pires Moreira

2452-3216 © 2022 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0) Peer-review under responsibility of Pedro Miguel Guimaraes Pires Moreira 10.1016/j.prostr.2022.01.138