PSI - Issue 36

Olena Stankevych et al. / Procedia Structural Integrity 36 (2022) 114–121 Olena Stankevych, Valentyn Skalskyi, Bogdan Klym et al. / StructuralIntegrity Procedia 00 (2021) 000 – 000

119

6

Fig. 3. Wave forms (a, c) and the CWT (b, d) of the typical AE signals during fracture of the pain concrete at the initial (a, b) and critical (c, d) stages of fracture.

Table 4. Parameters of local pulses of CWT of AE signals corresponding to different mechanisms of the plain concrete fracture. Fracture mechanisms Type of fracture f max , kHz Δ t , μ s E WT Plastic deformation Ductile 230…250 8…10 0.003…0.008 Microcracking Brittle 90…200 10…33 0.011…0.1 Macrocrack growth Brittle 110…170 20…36 0.104…0.543 According to the energy distribution of the DWT, it was found that about 95% of the main energy of AE signals is concentrated in the frequency bands D4 ( 125…250 kHz) and A4 (0…125 kHz): 65% of these are signals in which the frequency range D4 dominates. They were classified as type I and accompanied the plastic deformation and microcracking in concrete, dominated in them. The frequency range A4 dominates for 35% of AE signals. They were classified as type II. According to the fracture mechanisms identification, the local events that accompanied the abrupt growth of macrocrack dominated. 5.2. AE signals analysis during SFRC fracture As mentioned above, the addition of fiber to concrete increases the number of AE radiation sources during fracture. To identify new sources of AE in SFRC, the CWT and DWT of AE signals recorded during fracture of SFRC with 2% steel fiber were analyzed. The typical load curve (Fig. 4a) was divided into parts between points: 0 А, А - В, B - С, C -D. According to literature data (Li et al. (2018)) part 0-A is characterized by the crack growth in the matrix and a slight sliding of the fiber , А -B – intensive microcracking, slight fiber pull-out and its sliding , В -C – intensive sliding of the fiber and its pull-out , С -D – fiber pull-out from the matrix. To point С the load-deflection curve is convex with respect to the time axis, and after point D the load-deflection curve is stable, characterizing the slow propagation of the main crack. Table 5 shows the results of identification of fracture mechanisms of SFRC on the section 0-A (Fig. 4a). It should be noted that the mechanism of microcracks formation predominates here, which accompanies 63% of AE events. The remaining 37% of events are generated as a result of their coalescence, which ultimately leads to the initiation of the main macrocrack, as evidenced by the drop in load in the vicinity of point A. Table 5. Parameters of local pulses of CWT of AE signals corresponding to different fracture mechanisms of SFRC with steel fibers volume fraction of 2% on the section of the load curve from 0 to point A. Fracture mechanisms Type of fracture f max , kHz Δ t , μ s E WT Microcracking Brittle 140…150 13…25 0.037…0.085 Macrocrack growth Brittle 110…170 18…35 0.15…1.18 Therefore, based on the identification results, it can be concluded that in the selected area there is an intensive propagation of microcracks (in the concrete matrix and at the matrix/fiber interface) and their coalescence into macrocracks, which is consistent with literature (Li et al. (2018)). Note that according to the energy distribution of the DWT, about 98% of the energy of the registered signals is concentrated at the levels of D4 (125… 250 kHz) and A4 (0… 125 kHz). Similar to the case of plain concrete, they