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Time reversal damage localization in concrete based on two-dimensional meso-scale modeling

Autor(en):



Medium: Fachartikel
Sprache(n): Englisch
Veröffentlicht in: Structural Health Monitoring, , n. 1, v. 20
Seite(n): 188-201
DOI: 10.1177/1475921720918374
Abstrakt:

In this article, a damage localization method in concrete materials based on time reversal theory and meso-scale finite element simulation considering random heterogeneous properties is developed. In this article, concrete is regarded as a multiphase composite material consisting of cement mortar matrix, coarse aggregates, and interface transition zones. Compared to other methods, which assume that concrete is homogeneous, the meso-scale model considers the intricacies of concrete inhomogeneity and can therefore better characterize the interaction between stress waves and internal structures of concrete material. Through the meso-scale method, acoustic phenomena including reflection, transmission, and diffraction among internal structures of concrete can be modeled. Furthermore, a novel time reversal based, damage imaging method is developed using the envelope of the refocused damage scattering signal to monitor the health condition of concrete. The scattered signal received by each sensor is time reversed and reemitted via numerical computation. To decrease the dispersion effect, the autocorrelation function of the refocused signals is computed to generate an image of the estimated damage. A time correction factor is introduced to decrease the influence of the elongated wave packet. Numerical and experimental results indicate that the proposed damage imaging method can locate damage with high spatial resolution in heterogeneous concrete material. Moreover, owing to the meso-scale modeling, the propagation of high-frequency stress waves in concrete can be analyzed more accurately.

Structurae kann Ihnen derzeit diese Veröffentlichung nicht im Volltext zur Verfügung stellen. Der Volltext ist beim Verlag erhältlich über die DOI: 10.1177/1475921720918374.
  • Über diese
    Datenseite
  • Reference-ID
    10562444
  • Veröffentlicht am:
    11.02.2021
  • Geändert am:
    19.02.2021
 
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