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Precursor damage state quantification can be helpful for safety and operation of aircraft and defense equipment’s. Damage develops in the composite material in the form of matrix cracking, fiber breakages and deboning, etc. However, detection and quantification of the damage modes at their very early stage is not possible unless modifications of the existing indispensable techniques are conceived, particularly for the quantification of multiscale damages at their early stage. Here, we present a novel nonlocal mechanics based damage detection technique for precursor damage state quantification. Micro-continuum physics is used by modifying the Christoffel equation. American society of testing and materials (ASTM) standard woven carbon fiber (CFRP) specimens were tested under Tension-Tension fatigue loading at the interval of 25,000 cycles until 500,000 cycles. Scanning Acoustic Microcopy (SAM) and Optical Microscopy (OM) were used to examine the damage development at the same interval. Surface Acoustic Wave (SAW) velocity profile on a representative volume element (RVE) of the specimen were calculated at the regular interval of 50,000 cycles. Nonlocal parameters were calculated form the micromorphic wave dispersion curve at a particular frequency of 50 MHz. We used a previously formulated parameter called “Damage entropy” which is a measure of the damage growth in the material calculated with the loading cycle. Damage entropy (DE) was calculated at every pixel on the RVE and the mean of DE was plotted at the loading interval of 25,000 cycle. Growth of DE with fatigue loading cycles was observed. Optical Imaging also performed at the interval of 25,000 cycles to investigate the development of damage inside the materials. We also calculated the mean value of the Surface Acoustic Wave (SAW) velocity and plotted with fatigue cycle which is correlated further with Damage Entropy (DE). Statistical analysis of the Surface Acoustic Wave profile (SAW) obtained at different fatigue cycles was performed to extract the useful information about the damage state. This study has potential to investigate progressive damage evolution and to quantify at different fatigue cycles.
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