Issue 52

B. E. Sobrinho et alii, Frattura ed Integrità Strutturale, 52 (2020) 51-66; DOI: 10.3221/IGF-ESIS.52.05 51 Differential evolution algorithm for identification of structural damage in steel beams Brunno E. Sobrinho, Gilberto Gomes, Welington V. da Silva, Ramon S. Y. R. C. Silva, Luciano M. Bezerra University of Brasilia, Brazil brunno.emidio@aluno.unb.br , https://orcid.org/0000-0003-4407-7213 ggomes@unb.br , http://orcid.org/0000-0002-8385-9042 welington.vital@aluno.unb.br, ramon@unb.br , lmbz@unb.br Erwin U. L. Palechor University of Cariri Juazeiro do Norte, Ceará, Brazil erwin.lopez@ufca.edu.br A BSTRACT . Problems involving errors and uncertainties from the use of numerical and experimental responses of beams using optimization processes have been studied by many researchers. In this field, to simulate the real behavior of structures, especially in problems involving damage, it is required to have reliable experimental results in order to adjust a numerical model. These difficulties may be associated for example to the modeling of the connection stiffness, support conditions, or relevant parameters in structures involving damages. This paper proposes a new methodology to detect damage in steel beams using the Differential Evolution Technique based on experimental and numerical data. The results show a great potential of the methodology to solve damage detection problems. K EYWORDS . Steel beams; Optimization; Damage identification; Differential Evolution. Citation: Sobrinho, B., Gomes, G., V. Silva, W., Silva, R., Bezerra, L, Palechor, E. Differential Evolution Algorithm for Identification of Structural Damage in Steel Beams, Frattura ed Integrità Strutturale, 52 (2020) 51-66. Received: 19.09.2019 Accepted: 17.01.2020 Published: 01.04.2020 Copyright: © 2020 This is an open access article under the terms of the CC-BY 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. I NTRODUCTION n recent years researchers have dedicated considerable attention to optimization procedures. The real behavior of structures is not easy to be simulated due to the complexity in modeling the stiffness of connections, support conditions and other parameters. Therefore, the damage identification process becomes more difficult. On the other hand, the inverse problems area has a great potentiality to deal with damaged structures. According to [1], the damage identification is done by numerical methods, which seek the identification of geometric parameters of a model adopted for damage, from the structural response (static, dynamic, electrical, thermal excitation, among others). A powerful I