PSI - Issue 47

Mikhail Bannikov et al. / Procedia Structural Integrity 47 (2023) 685–692 Author name / Structural Integrity Procedia 00 (2019) 000–000

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processing acoustic emission data under the conditions of cyclic loading. Furthermore, both clusters exhibit multifractal properties according to the data from processing the distributions of fluctuations of deformation fields using the method of multifractal analysis. Thus, acoustic emission is an experimental method that is more sensitive to multifractal properties. 5. Conclusion The phase portraits observed at different stages of composite failure resemble those observed during dynamic crack propagation in PMMA previously obtained by the authors [13-15]. These portraits reflect the strain localization determined by the stress field in the vicinity of the concentrator and strain field fluctuations due to damage localization. The time phase portraits for deformation, which represent compact sets of points, reflect the hyperbolicity of the stress field in the vicinity of the crack tip in accordance with Irwin's self-similar (singular) solution. The division of the energy of acoustic emission phenomena into clusters under cyclic loading makes it possible to determine the staging of the transition from damage accumulation to destruction. Additionally, it enables one to conclude that there are two self-similar solutions that determine the singular temporal kinetics of the formation of fracture centers (child cracks). The phase portraits in the coordinates "deformation - strain gradient" reflect the role of collective phenomena in the development of damage, taking into account the peculiarities of the stress state. The obtained results on the kinetics of damage development in the presence of two types of self-similar solutions agree with the concepts reflected in the two-parameter failure criteria. The justification of the relationship between structural parameters and fracture mechanics criteria for composite materials involves the use of tomography data on the development of defects at various scale levels. 1. Waddoups M.E., Eisenmann J.R., Kaminski B.E., 1971. Macroscopic fracture mechanics of advanced composite materials. Journal of Composite Materials. 5 (4), 446–454. 2. Susmel L., Taylor D. 2008. On the use of the Theory of Critical Distances to predict static failures in ductile metallic materials containing different geometrical features.Engng. Fract. Mech. 75, 4410–4421. 3. MatvienkoYu.G., Semenova M.M. 2015. The concept of the average stress in the fracture process zone for the search of the crack path.Fracture and Structural Integrity 34, 255–260. 4. Matvienko, Y.G. 2014. Simulation analysis of the fracture mechanics parameters of substandard specimens. Inorg Mater 50, 1521–1527. 5. MatvienkoYu.G. 2020.The effect of crack-tip constraint in some problems of fracture mechanics. Eng. Fail. Anal.110, Р . 104413. 6. MatvienkoYu.G. 2013. Safety factors in structural integrity assessment of components with defects. Int. J. Struct. Integr. 4, 457–476. 7. Meliani H.M., MatvienkoYu.G., Pluvinage G. 2011. Two-parameter fracture criterion (K ρ ,c–Tef,c) based on notch fracture mechanics. Int. J. Fract. 167, 173–182. 8. Nateche T., Hadj Meliani M., Pluvinage G., Khan S.M.A., Merah N., Matvienko Y.G. 2015. Residual harmfulness of a defect after repairing by a composite patch. Eng. Fail. Anal. 48, 166–173. 9. Bannikov M, Sazhenkov N., Balakirev A., Uvarov S., Bayandin Y, Nikitiuk A., Nikhamkin M, Naimark O, 2022. Acoustic emission phase analysis of damage-failure transition staging in composite materials, Procedia Structural Integrity, 41, 518-526, 10. Liu, N., Xu, Z., Zeng, X. J., Ren, P., 2021. An agglomerative hierarchical clustering algorithm for linear ordinal rankings. Information Sciences, 557, 170-193. 11.Jaffard, S., Lashermes, B., Abry, P., 2006. Wavelet leaders in multifractal analysis. In Wavelet analysis and applications (pp. 201-246) Birkhauser Basel. 12. Sutton M.A., Cheng M.Q., Peters W.H. et al. 1986. Application of an optimized digital correlation method to planar deformation analysis M. A. Sutton. Image and vision computing. 4(3), 143-151. Acknowledgements This research was supported by the Russian Science Foundation (grant n. 21-79-30041). References