Issue 66

B. Chahira et al, Frattura ed Integrità Strutturale, 66 (2023) 207-219; DOI: 10.3221/IGF-ESIS.66.13

R EFERENCES

[1] Gholizadeh, S. (2016). A review of non-destructive testing methods of composite materials. Procedia structural integrity, 1, pp. 50-57. [2] Dwivedi, S. K., Vishwakarma, M. and Soni, A. (2018). Advances and researches on non destructive testing: A review. Materials Today: Proceedings, 5(2), pp. 3690-3698. [3] Garnier, C., Pastor, M. L., Eyma, F. and Lorrain, B. (2011). The detection of aeronautical defects in situ on composite structures using Non Destructive Testing. Composite structures, 93(5), pp. 1328-1336. [4] Usamentiaga, R., Venegas, P., Guerediaga, J., Vega, L., Molleda, J. and Bulnes, F. G. (2014). Infrared thermography for temperature measurement and non-destructive testing. Sensors, 14(7), pp. 12305-12348. [5] Jolly, M. R., Prabhakar, A., Sturzu, B., Hollstein, K., Singh, R., Thomas, S., ... & Shaw, A. (2015). Review of non destructive testing (NDT) techniques and their applicability to thick walled composites. Procedia CIRP, 38, pp. 129 136. [6] Oesch, T., Weise, F. and Bruno, G. (2020). Detection and quantification of cracking in concrete aggregate through virtual data fusion of X-ray computed tomography images. Materials, 13(18), 3921. [7] Abu-Mahfouz, I. and Banerjee, A. (2017). Crack detection and identification using vibration signals and fuzzy clustering. Procedia Computer Science, 114, pp. 266-274. [8] Agathos, K., Chatzi, E. and Bordas, S. P. (2016). Stable 3D extended finite elements with higher order enrichment for accurate non planar fracture. Computer Methods in Applied Mechanics and Engineering, 306, pp. 19-46. [9] Agathos, K., Chatzi, E. and Bordas, S. P. (2018). Multiple crack detection in 3D using a stable XFEM and global optimization. Computational mechanics, 62, pp. 835-852. [10] Broumand, P. (2021). Inverse problem techniques for multiple crack detection in 2D elastic continua based on extended finite element concepts. Inverse Problems in Science and Engineering, 29(12), pp. 1702-1728. [11] Nobahari, M. and Seyedpoor, S. M. (2011). Structural damage detection using an efficient correlation-based index and a modified genetic algorithm. Mathematical and Computer modelling, 53(9-10), pp. 1798-1809. [12] Gomes, G. F., Mendez, Y. A. D., da Silva Lopes Alexandrino, P., da Cunha, S. S. and Ancelotti, A. C. (2019). A review of vibration based inverse methods for damage detection and identification in mechanical structures using optimization algorithms and ANN. Archives of computational methods in engineering, 26, pp. 883-897. [13] Saeed, R. A., Galybin, A. N. and Popov, V. (2012). Crack identification in curvilinear beams by using ANN and ANFIS based on natural frequencies and frequency response functions. Neural computing and applications, 21, pp. 1629-1645. [14] Jena, P. K., Thatoi, D. N. and Parhi, D. R. (2013). Differential evolution: an inverse approach for crack detection. Advances in Acoustics and Vibration. [15] Boukellif, R. and Ricoeur, A. (2020). Identification of crack parameters and stress intensity factors in finite and semi infinite plates solving inverse problems of linear elasticity. Acta Mechanica, 231(2), pp. 795-813. [16] Khatir, S., Dekemele, K., Loccufier, M., Khatir, T. and Wahab, M. A. (2018). Crack identification method in beam-like structures using changes in experimentally measured frequencies and Particle Swarm Optimization. Comptes Rendus Mécanique, 346(2), pp. 110-120. [17] Zenzen, R., Belaidi, I., Khatir, S. and Wahab, M. A. (2018). A damage identification technique for beam-like and truss structures based on FRF and Bat Algorithm. Comptes Rendus Mécanique, 346(12), pp. 1253-1266. [18] Al-Wazni, S. and Azainul-abideen, A. Y. (2019, August). Intelligent non-destructive technique for crack existence inspection in a structure using Particle Swarm Optimization (PSO). In IOP Conference Series: Materials Science and Engineering, 584(1), p. 012046. [19] Amoura, N., Kebir, H., Rechak, S. and Roelandt, J. M. (2010). Axisymmetric and two-dimensional crack identification using boundary elements and coupled quasi-random downhill simplex algorithms. Engineering analysis with boundary elements, 34(6), pp. 611-618. [20] Amoura, N., Kebir, H. and Benzerdjeb, A. (2022). 3D crack identification using the Nelder-Mead Simplex algorithm combined with a random generation of crack positions. Frattura ed Integrità Strutturale, 16(59), pp. 243-255. [21] Benaissa, B., Köppen, M., Wahab, M. A. and Khatir, S. (2017, May). Application of proper orthogonal decomposition and radial basis functions for crack size estimation using particle swarm optimization. In Journal of Physics: Conference Series, 842(1), p. 012014). IOP Publishing. [22] Jena, P. K. and Parhi, D. R. (2015). A modified particle swarm optimization technique for crack detection in cantilever beams. Arabian Journal for Science and Engineering, 40, pp. 3263-3272.

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