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Full-field Strain Measurements for Microstructurally Small Fatigue Crack Propagation Using Digital Image Correlation Method
Published on: January 16, 2019
Analysis of the Tensile Failure Process of TRC Based on Load-Displacement Curves and DIC Full-Field Strain:
Feiting Shi1,2, Shuangcheng Wu1, Li Li1
1School of Civil Engineering, Yancheng Institute of Technology, Yancheng 224051, China.
Abstract:
This study systematically investigates the effects of reinforcement ratio, textile orientation, and interface treatment on the tensile behavior of carbon fiber textile-reinforced concrete (TRC) through uniaxial tensile tests and numerical simulation. The experimental results indicate that as the reinforcement ratio increases from 0.44% to 1.33%, the ultimate tensile stress rises from 1.86 MPa to 4.08 MPa (an increase of 119%), the ultimate tensile strain increases from 0.86% to 1.72% (an increase of 100%), and the average crack spacing decreases from 24.3 mm to 8.7 mm (a reduction of 64%). Correspondingly, the failure mode transitions from brittle single-crack fracture to multi-crack quasi-ductile failure. Compared with transverse orientation, the longitudinal orientation yields a 32.7% increase in ultimate tensile stress and a 46.2% increase in ultimate tensile strain, primarily attributable to a 35-45% enhancement in interfacial frictional stress. Under the longitudinal configuration, carbon-glue interfacial treatment further improves the ultimate tensile stress by 36.9% and the ultimate tensile strain by 42.1%, while reducing the average crack spacing to 8.1 mm and shifting the failure mode toward fiber rupture-dominated failure. Digital image correlation (DIC) analysis reveals that the strain inhomogeneity index decreases from 0.65-0.78 to 0.28-0.35. The finite element simulation results indicate that the error in peak load remains below 5%, and the error in crack spacing remains below 10%. This study establishes a quantitative regulatory framework encompassing reinforcement ratio, textile orientation, and interface treatment, thereby providing a basis for performance prediction and optimization of TRC.
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